SATRIFO v4.1

Forest change

Forest change data measure tree cover loss, tree cover gain, or forest disturbance.

Threshold Settings Info Window

Drag the handle to adjust the minimum tree cover canopy (TCC) density for the visualization and analysis of Hansen/UMD/Google/USGS/NASA tree cover and tree cover loss. TCC density represents the estimated percent of a pixel that was covered by tree canopy in the year 2000, as determined from the analysis of satellite imagery. For the tree cover loss data, TCC density therefore corresponds to the density of tree cover before loss occurred. For example, if you select 25% as the minimum TCC density, you will only see tree cover loss pixels for which the original tree cover density was greater than 25%.

Adjustments to the minimum TCC density only affect Hansen/UMD/Google/USGS/NASA tree cover and tree cover loss data layers. This feature does not pertain to Hansen/UMD/Google/USGS/NASA tree cover gain or to other GFW data layers or statistics. Hansen/UMD/Google/USGS/NASA tree cover gain is displayed with a set minimum TCC density greater than 50%. The minimum TCC density cannot be changed independently for tree cover and tree cover loss. A change made to one data layer will immediately take effect in the other.

This feature is also available for statistics within the country profiles and rankings. However, the adjustment made to the visualization and analysis through the map view will not be automatically reflected in other areas of the website. To adjust the minimum TCC density within the country and country rankings pages, click on the settings icon.
Modelo de riesgo de incendios

Loss of tree cover may occur for many reasons, including deforestation, fire, and logging within the course of sustainable forestry operations. In sustainably managed forests, the “loss” will eventually show up as “gain”, as young trees get large enough to achieve canopy closure.
University of Maryland/Google tree cover loss (annual, 27.8m, global)
Download at project website

Function

Identifies areas of gross tree cover loss

RESOLUTION / SCALE

0.00025 decimal degrees or approximately 27.8 x 27.8 meters at the equator

Geographic coverage

Global land area (excluding Antarctica and other Arctic islands)

Source data

Landsat 5 TM, Landsat 7 ETM+, and Landsat 8 OLI

Frequency of updates

Annual

Date of content

2001–2013

Tree cover canopy density

Varies according to selection (click the gear icon on the map to change the minimum tree cover canopy density threshold)

Cautions

This data layer was updated in January 2015 to extend the tree cover loss analysis to 2013. The 2013 data update included new Landsat 8 data (launched in February 2013) as well as re-processed 2010-2012 data from Landsat TM and ETM+, which increased the amount of change that could be detected, resulting in some changes in calculated tree cover loss for 2011 (global increase of 6%) and 2012 (increase of 22%). Calculated tree cover loss for 2001-2010 remains unchanged. The integrated use of the original 2001-2012 (Version 1.0) data and the updated 2011–2013 data (Version 1.1) should be performed with caution.

For the purpose of this study, “tree cover” was defined as all vegetation taller than 5 meters in height. “Tree cover” is the biophysical presence of trees and may take the form of natural forests or plantations existing over a range of canopy densities. “Loss” indicates the removal or mortality of tree canopy cover and can be due to a variety of factors, including mechanical harvesting, fire, disease, or storm damage. As such, “loss” does not equate to deforestation.

When zoomed out (< zoom level 13), pixels of loss are shaded according to the density of loss at the 30 x 30 meter scale. Pixels with darker shading represent areas with a higher concentration of tree cover loss, whereas pixels with lighter shading indicate a lower concentration of tree cover loss. There is no variation in pixel shading when the data is at full resolution (≥ zoom level 13).

A validation assessment of the 2000 – 2012 Hansen/UMD/Google/USGS/NASA change data was carried out independently from the mapping exercise at the global and biome (tropical, subtropical, temperate, and boreal) scale. A stratified random sample (for no change, loss, and gain) of 1500 blocks, each 120 × 120 meters, was used as validation data. The amount of tree cover loss within each block was estimated using Landsat, MODIS, and Google Earth high-resolution imagery and compared to the map. Overall accuracies for loss were over 99% globally and for all biomes. However, since the overall accuracy calculations are positively skewed due to the high percentage of no change pixels, it is also important to assess the accuracy of the change predictions. The user’s accuracy (i.e. the percentage of pixels labelled as tree cover loss that actually lost tree cover) was 87.0% at the global level. At the biome level, user’s accuracies were 87.0%, 79.3%, 88.2%, and 88.0% for the tropical, subtropical, temperate, and boreal biomes, respectively. A separate test was conducted to determine the temporal accuracy of the tree cover loss data. Within the 1500 blocks, the year of the largest drop in annual MODIS NDVI was compared to the year of tree cover loss from the map. The year of disturbance matched for 75.2% of tree cover loss events, and was within one year for 96.7% of tree cover loss events.
Overview

This data set measures areas of tree cover loss across all global land (except Antarctica and other Arctic islands) at approximately 30 × 30 meter resolution. The data were generated using multispectral satellite imagery from the Landsat 7 thematic mapper plus (ETM+), and Landsat 7 thematic mapper plus (ETM+), and Landsat 8 Operational Land Imager (OLI) sensors. Over 1 million satellite images were processed and analyzed, including over 600,000 Landsat 7 images for the 2000-2012 interval, and approximately 400,000 Landsat 5, 7 and 8 images for the 2010-2013 interval. The clear land surface observations in the satellite images were assembled and a supervised learning algorithm was applied to identify per pixel tree cover loss.

Tree cover loss is defined as “stand replacement disturbance,” or the complete removal of tree cover canopy at the Landsat pixel scale. Tree cover loss may be the result of human activities, including forestry practices such as timber harvesting or deforestation (the conversion of natural forest to other land uses), as well as natural causes such as disease or storm damage. Fire is another widespread cause of tree cover loss, and can be either natural or human-induced.

2015 Update (Version 1.1)

This data set was recently updated and now includes a 2013 loss layer and revised layers for 2011 and 2012. The analysis method has been modified in numerous ways, and the update should be seen as part of a transition to a future “version 2.0” of this data set that is more consistent over the entire 2001 and onward period. Key changes include:
- The use of Landsat 8 data for 2013 and Landsat 5 data for 2010-2011
- The reprocessing of data from 2011 to 2012 in measuring loss
- Improved training data for calibrating the loss model
- Improved per sensor quality assessment models to filter input data
- Improved input spectral features for building and applying the loss model
These changes lead to a different and improved detection of global tree cover loss. However, the years preceding 2011 have not yet been reprocessed with the revised analysis methods, and users will notice inconsistencies between versions 1.0 (2001-2012) and 1.1 (2001-2013) as a result. It must also be noted that a full validation of the results incorporating Landsat 8 has not been undertaken. Such an analysis may reveal a more sensitive ability to detect and map forest disturbance using Landsat 8 data. If this is the case then there will be a more fundamental limitation to the consistency of this data set before and after the inclusion of Landsat 8 data. Validation of Landsat 8-incorporated loss detection is planned.

Some examples of improved change detection in the 2011–2013 update include the following:
- Improved detection of boreal forest loss due to fire
- Improved detection of smallholder rotation agricultural clearing in dry and humid tropical forests
- Improved detection of selective logging
These are examples of dynamics that may be differentially mapped over the 2001-2013 period in Version 1.1. A version 2.0 reprocessing of the 2001 and onward record is planned, but no delivery date is yet confirmed.

The original version 1.0 data remains available for download here.

Citation: Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend. 2013. “High-Resolution Global Maps of 21st-Century Forest Cover Change.” Science 342 (15 November): 850–53. Data available online from: http://earthenginepartners.appspot.com/science-2013-global-forest.

Suggested citations for data as displayed on GFW:Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend. 2013. “Hansen/UMD/Google/USGS/NASA Tree Cover Loss and Gain Area.” University of Maryland, Google, USGS, and NASA. Accessed through Global Forest Watch on [date]. incendios.fan-bo.orf.

Learn more or download data
PRODES tree cover loss (annual, 30m, Brazilian Amazon, INPE)

Function

Deforestation monitoring system for the Brazilian Amazon used by the Brazilian government to establish public policy

RESOLUTION / SCALE

30 × 30 meters, minimum mapping unit of 6.25 hectares

Geographic coverage

Brazilian Amazon

Source data

Landsat, supplemented with CBERS, Resourcesat, and UK2-DMC

Frequency of updates

Annual

Date of content

2000–2014

Cautions

TPRODES only identifies forest clearings of 6.25 hectares or larger, so forest degradation or smaller clearings from fire or selective logging are not detected.

Frequent cloud cover over areas of the Amazon may change the reported year of deforestation. The year reported is the first year deforestation is identified by analysts, but this does not necessarily correspond to the year of deforestation if the landscape has been covered by clouds in previous years.

License

Creative Commons BY SA 3.0

Overview

The PRODES project monitors clear cut deforestation in the Brazilian Legal Amazon, and has produced annual deforestation rates for the region since 1988. The Brazilian government uses these figures to establish public policy, including defining access to credit in the Amazon biome, establishing deforestation reduction goals, and soliciting funds to reduce deforestation. PRODES historically used Landsat 5 images, but now also incorporates imagery from Landsat 7 and 8, CBERS-2, CBERS-2B, Resourcesat-1, and UK2-DMC. PRODES is operated by the National Institute of Space Research (INPE) in collaboration with the Ministry of the Environment (MMA) and the Brazilian Institute of Environment and Renewable Natural Resources (IBAMA). Since 2002, all PRODES data is publicly available online.

Input images for each of the 220 Landsat footprints that cover the Brazilian Amazon are selected based on their lack of cloud cover and their capture date. The PRODES system uses the seasonal year, starting on August 1st, to calculate annual deforestation, so images are selected as near to this date as possible (generally from July, August, and September). From 2003 to 2005, analysts used image transformation to determine the components of vegetation, soil, and shadow using the program SPRING. These components were segmented and classified into the classes of forest, non-forest, deforestation in the target year, previous deforestation, clouds, and water, which are then manually corrected by experts. Starting in 2005, a new methodology was implemented which makes use of the open source TerraAmazon platform. The platform allows the PRODES analysis to be more uniform and can incorporate imagery from a variety of satellites. As before, images are selected to be as cloud free as possible. The images are then masked to exclude non-forest, previous deforestation, and water using the previous year’s analysis. Analysts then delineate deforested polygons in the intact forest of the previous year. More information on the methodology can be found on the PRODES website.

This data set shows deforestation from 1997-2000, and annual deforestation between 2000 and 2014.

National Institute of Space Research (INPE). “PRODES.” 2014.

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PRODES geographic coverage

Function

Displays the geographic coverage of PRODES deforestation.

RESOLUTION / SCALE

Regional

Geographic coverage

This layer displays the geographic coverage of PRODES monitoring, which only covers the Brazilian Amazon.

University of Maryland/Google tree cover gain (12 years, 30m, global)

Download at project website

Function

Identifies areas of tree cover gain

RESOLUTION / SCALE

30 × 30 meters

Geographic coverage

Global land area (excluding Antarctica and other Arctic islands)

Source data

Landsat 7 ETM+

Frequency of updates

Every three years

Date of content

2001–2012

Tree cover canopy density

>50%

Cautions

For the purpose of this study, “tree cover” was defined as all vegetation taller than 5 meters in height. “Tree cover” is the biophysical presence of trees and may take the form of natural forests or plantations existing over a range of canopy densities. “Loss” indicates the removal or mortality of tree canopy cover and can be due to a variety of factors, including mechanical harvesting, fire, disease, or storm damage. As such, “loss” does not equate to deforestation.

When zoomed out (< zoom level 13), pixels of gain are shaded according to the density of gain at the 30 x 30 meter scale. Pixels with darker shading represent areas with a higher concentration of tree cover gain, whereas pixels with lighter shading indicate a lower concentration of tree cover gain. There is no variation in pixel shading when the data is at full resolution (≥ zoom level 13).

A validation assessment of the 2000 – 2012 Hansen/UMD/Google/USGS/NASA change data was carried out independently from the mapping exercise at the global and biome (tropical, subtropical, temperate, and boreal) scale. A stratified random sample (for no change, loss, and gain) of 1500 blocks, each 120 × 120 meters, was used as validation data. The amount of tree cover gain within each block was estimated using Landsat, MODIS, and Google Earth high-resolution imagery and compared to the map. Overall accuracies for gain were over 99.5% globally and for all biomes. However, since the overall accuracy calculations are positively skewed due to the high percentage of no change pixels, it is also important to assess the accuracy of the change predictions. The user’s accuracy (i.e. the percentage of pixels labelled as tree cover gain that actually gained tree cover) was 87.8% at the global level. At the biome level, user’s accuracies were 81.9%, 85.5%, 62.0%, and 76.7% for the tropical, subtropical, temperate, and boreal biomes, respectively.

Overview

This data set measures areas of tree cover gain across all global land (except Antarctica and other Arctic islands) at 30 × 30 meter resolution, displayed as a 12-year cumulative layer. The data were generated using multispectral satellite imagery from the Landsat 7 thematic mapper plus (ETM+) sensor. Over 600,000 Landsat 7 images were compiled and analyzed using Google Earth Engine, a cloud platform for earth observation and data analysis. The clear land surface observations (30 × 30 meter pixels) in the satellite images were assembled and a supervised learning algorithm was then applied to identify per pixel tree cover gain.

Tree cover gain was defined as the establishment of tree canopy at the Landsat pixel scale in an area that previously had no tree cover. Tree cover gain may indicate a number of potential activities, including natural forest growth or the crop rotation cycle of tree plantations.

Citation: Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend. 2013. “High-Resolution Global Maps of 21st-Century Forest Cover Change.” Science 342 (15 November): 850–53. Data available on-line from: http://earthenginepartners.appspot.com/science-2013-global-forest.

Suggested citations for data as displayed on GFW: Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend. 2013. “Hansen/UMD/Google/USGS/NASA Tree Cover Loss and Gain Area.” University of Maryland, Google, USGS, and NASA. Accessed through Global Forest Watch on [date]. incendios.fa-bo.org.

Learn more or download data

University of Maryland/Google tree cover loss (annual, 30m, global)

Download at project website

Function

Identifies areas of gross tree cover loss

RESOLUTION / SCALE

0.00025 decimal degrees or approximately 27.8 x 27.8 meters at the equator

Geographic coverage

Global land area (excluding Antarctica and other Arctic islands)

Source data

Landsat 5 TM, Landsat 7 ETM+, and Landsat 8 OLI

Frequency of updates

Annual

Date of content

2001–2013

Tree cover canopy density

Varies according to selection (click the gear icon on the map to change the minimum tree cover canopy density threshold)

Cautions

This data layer was updated in January 2015 to extend the tree cover loss analysis to 2013. The 2013 data update included new Landsat 8 data (launched in February 2013) as well as re-processed 2010-2012 data from Landsat TM and ETM+, which increased the amount of change that could be detected, resulting in some changes in calculated tree cover loss for 2011 (global increase of 6%) and 2012 (increase of 22%). Calculated tree cover loss for 2001-2010 remains unchanged. The integrated use of the original 2001-2012 (Version 1.0) data and the updated 2011–2013 data (Version 1.1) should be performed with caution.

For the purpose of this study, “tree cover” was defined as all vegetation taller than 5 meters in height. “Tree cover” is the biophysical presence of trees and may take the form of natural forests or plantations existing over a range of canopy densities. “Loss” indicates the removal or mortality of tree canopy cover and can be due to a variety of factors, including mechanical harvesting, fire, disease, or storm damage. As such, “loss” does not equate to deforestation.

When zoomed out (< zoom level 13), pixels of loss are shaded according to the density of loss at the 30 x 30 meter scale. Pixels with darker shading represent areas with a higher concentration of tree cover loss, whereas pixels with lighter shading indicate a lower concentration of tree cover loss. There is no variation in pixel shading when the data is at full resolution (≥ zoom level 13).

Overview

This data set measures areas of tree cover loss across all global land (except Antarctica and other Arctic islands) at approximately 30 × 30 meter resolution. The data were generated using multispectral satellite imagery from the Landsat 7 thematic mapper plus (ETM+), and Landsat 7 thematic mapper plus (ETM+), and Landsat 8 Operational Land Imager (OLI) sensors. Over 1 million satellite images were processed and analyzed, including over 600,000 Landsat 7 images for the 2000-2012 interval, and approximately 400,000 Landsat 5,7 and 8 images for the 2010-2013 interval . The clear land surface observations in the satellite images were assembled and a supervised learning algorithm was applied to identify per pixel tree cover loss.

Tree cover loss is defined as “stand replacement disturbance,” or the complete removal of tree cover canopy at the Landsat pixel scale. Tree cover loss may be the result of human activities, including forestry practices such as timber harvesting or deforestation (the conversion of natural forest to other land uses), as well as natural causes such as disease or storm damage. Fire is another widespread cause of tree cover loss, and can be either natural or human-induced.

2015 Update (Version 1.1)

This data set was recently updated and now includes a 2013 loss layer and revised layers for 2011 and 2012. The analysis method has been modified in numerous ways, and the update should be seen as part of a transition to a future “version 2.0” of this data set that is more consistent over the entire 2001 and onward period. Key changes include:

The use of Landsat 8 data for 2013 and Landsat 5 data for 2010-2011

The reprocessing of data from 2011 to 2012 in measuring loss

Improved training data for calibrating the loss model

Improved per sensor quality assessment models to filter input data

Improved input spectral features for building and applying the loss model

These changes lead to a different and improved detection of global tree cover loss. However, the years preceding 2011 have not yet been reprocessed with the revised analysis methods, and users will notice inconsistencies between versions 1.0 (2001-2012) and 1.1 (2001-2013) as a result. It must also be noted that a full validation of the results incorporating Landsat 8 has not been undertaken. Such an analysis may reveal a more sensitive ability to detect and map forest disturbance using Landsat 8 data. If this is the case then there will be a more fundamental limitation to the consistency of this data set before and after the inclusion of Landsat 8 data. Validation of Landsat 8-incorporated loss detection is planned.

Some examples of improved change detection in the 2011–2013 update include the following:

Improved detection of boreal forest loss due to fire

Improved detection of smallholder rotation agricultural clearing in dry and humid tropical forests

Improved detection of selective logging

These are examples of dynamics that may be differentially mapped over the 2001-2013 period in Version 1.1. A version 2.0 reprocessing of the 2001 and onward record is planned, but no delivery date is yet confirmed.

The original version 1.0 data remains available for download here.

Citation: Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend. 2013. “High-Resolution Global Maps of 21st-Century Forest Cover Change.” Science 342 (15 November): 850–53. Data available online from: http://earthenginepartners.appspot.com/science-2013-global-forest.

Suggested citations for data as displayed on GFW:Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend. 2013. “Hansen/UMD/Google/USGS/NASA Tree Cover Loss and Gain Area.” University of Maryland, Google, USGS, and NASA. Accessed through Global Forest Watch on [date]. incendios.fan-bo.org.

Learn more or download data

Forma alerts (monthly, 500m, humid tropics)

Download

Function

Detects areas where tree cover loss is likely to have recently occurred

RESOLUTION / SCALE

500 × 500 meters

Geographic coverage

Humid tropical forest biome

Source data

MODIS

Frequency of updates

Displayed on the GFW site as monthly alerts, but available for download in 16-day increments

Date of content

January 2006-present

Cautions

Viewing data for the first period available via the time slider may include alerts that reflect detections from the February 2000 to December 2005 training period as the algorithm "catches up" post-training.

The GFW team has clipped out some data in regions where data quality is suspected to be low because of persistent cloud cover over identified ecoregions. This covers parts of Liberia, Venezuela, Guyana, Vietnam, Laos, and Burma/Myanmar. The current extent of the FORMA alerts is available for viewing here—FORMA geographic extent.

The algorithm behind the FORMA alerts is constantly evolving to fix bugs and improve accuracy. As a result, what appears on the site and the results of analyses conducted on the site may change over time. It is important to always include the access date when citing FORMA. Analysis of FORMA alerts on the map should be considered definitive, as analysis is based on raw FORMA data, whereas the data on the map are optimized for visual display. For questions, please join the GFW discussion forum or email us.

For the purpose of this study, “tree cover” was defined as areas with greater than 25% canopy cover (as determined by the Vegetation Continuous Fields data set), and change was measured without regard to forest land use. Tree cover assemblages that meet the 25% threshold include intact forests, plantations, and forest regrowth.

When zoomed out, this data layer displays some degree of inaccuracy because the data points must be collapsed to be visible on a larger scale. Zoom in for greater detail.

Overview

FORMA is a near real-time tree cover loss alert system. It uses a cloud computing algorithm to analyze frequently updated satellite imagery along with complementary information on factors that affect tree cover loss, such as fires and precipitation. The system generates twice-monthly “alerts” for the world’s humid tropical forests that identify 500 × 500 meter areas where new, large-scale loss is likely to have occurred.

FORMA is designed for quick identification of new areas of tree cover loss. The system analyzes data gathered daily by the MODIS sensor, which operates on NASA’s Terra and Aqua satellites. The FORMA alerts system then detects pronounced changes in vegetation cover over time, as measured by the Normalized Difference Vegetation Index (NDVI), a measure of vegetation greenness. These pronounced changes in vegetation cover are likely to indicate forest being cleared, burned, or defoliated.

FORMA alerts only appear in areas where the probability of tree cover loss is greater than or equal to 50%.

Upcoming upgrades to FORMA include improving the resolution to 250 × 250 meters, and expanding coverage to tropical dry forest and eventually to other biomes across the global scale.

Citation: Hammer, Dan, Robin Kraft, and David Wheeler. 2013. “FORMA Alerts.” World Resources Institute and Center for Global Development. Accessed through Global Forest Watch on [date]. incendios.fan-bo.org.

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Methodology

This data set uses freely available satellite imagery, collected by the Moderate Resolution Imaging Spectroradiometer (MODIS), which operates on NASA's Terra and Aqua (EOS PM) satellite platforms and views the entire Earth’s surface every 1 to 2 days. The images help to reveal notable changes in vegetation cover over time using an indicator that measures vegetation intensity called the Normalized Difference Vegetation Index (NDVI). By applying an automated algorithm to this input and in combination with complementary data inputs for fire hotspots and global precipitation averages, areas where tree cover loss is likely to have occurred are therefore identified. The algorithm also employs parallel processing in a remote server system the cloud that enables the rapid analysis of these very large data sets.

Explanation

Tree cover loss alerts appear when and where new, large-scale loss is likely to have occurred after 2005. Thus the alerts should not be interpreted as an analysis of total tree cover loss area but rather as an indication of an area that has a high probability of having experienced tree cover loss or disturbance over time. The system employs advanced statistical techniques to achieve the best fit to scientifically validate information on loss, measured as a probability. On the GFW website, alerts appear only for areas where there is a 50% or higher probability of tree cover loss. That is, alerts appear for a particular period when there has been significant loss in the area during or before that period.

Temporal and spatial resolution

FORMA alerts are displayed on the GFW site as monthly data, and the site is updated each month. Users who download data for analysis will find that the underlying data set is actually available at 16-day intervals, intervals that do not line up perfectly with calendar months. Data is displayed at a monthly resolution on GFW due to the monthly availability of precipitation data input. Users can manipulate the GFW time slider to view trends in loss alerts from December 2005 to present.

The alert system currently identifies 500 × 500 meter areas where loss is statistically likely to have occurred. Alerts for a 250-meter resolution version are currently being developed on Google’s Earth Engine platform and will be available in 2014.

Geographic extent

FORMA alerts are currently available only for humid tropical forests (as defined by Hansen et al. (2008), based on WWF’s terrestrial ecoregions) spanning portions of 89 countries. The development team is working to incorporate additional data to extend the geographic coverage beyond the current extent. To visualize the geographic extent of the alerts on the map, switch on the “Humid Tropical Forest Biome” layer.

Data applications

The alerts have been designed for quick identification of tree cover loss as it happens. This allows for rapid response and prioritization of scarce financial and human resources dedicated to forest conservation or sustainable forest management. Armed with this information, stakeholders can use preemptive methods such as on-the-ground visits or aerial inspection with high-resolution satellite imagery (less than 5-meter pixel resolution) to investigate suspected tree cover loss areas.

In addition, the alerts may be of value to a variety of researchers who study both temporal and spatial patterns related to tree cover loss areas.

Using the GFW platform, the alerts can be compared against other relevant data layers, such as protected areas and concessions boundaries, to evaluate the effectiveness of forest management practices across time and spatial extent.

Accuracy and validation

Inaccuracies are an inherent part of remote sensing analysis. FORMA alerts appear in areas with a greater than 50% probability of tree cover loss, based on the algorithm described under Methodology. However, persistent cloud cover is a continuous issue in the tropics, and extreme flooding can also produce unreliable remotely sensed data that will result in tree cover loss “false positives” (alerts where no actual tree cover loss has occurred). Furthermore, the alerting system cannot detect all forest cover loss, whether due to the small size of the loss area, persistent cloud cover, or other explanations still being identified through GFW validation efforts.

The major instances of false positives may occur as the following:

A random, "speckled" distribution of alerts across an ecoregion, or complete filling of a small ecoregion. Caused by limited or sparse training data, particularly in small ecoregions, which makes it difficult to tune the model there. As a result, alerts cannot be reliably detected. In a normal ecoregion, alerts are usually clustered.

A rapid explosion of alerts over 1-3 months covering a relatively large area. Caused by a significant, persistent drop in detected vegetation levels due to persistent cloud cover along coastlines, in mountains, or elsewhere.

Alerts in water. Caused by shifting water bodies. These alerts should be considered not necessarily as false positives but rather as ambiguous alerts requiring additional data for corroboration.

The GFW team is working aggressively to address potential inaccuracies in the data through rigorous validation methods. Specifically, the GFW team is comparing the growing data set of historical alerts to other validated data sets, which are being used for similar applications.

This issue brief demonstrates the spatial correlation of the alerts with the PRODES and DETER data sets, produced by the Brazilian Space Agency for the Amazon. The conclusions from the working paper help to illustrate the potential pitfalls of the algorithm, along with its strengths. Through future refinement and proposed crowdsourcing efforts, the GFW team expects the data quality of the FORMA Alerts will continue to improve.

Additional resources on FORMA

Working Papers:

FORMA: Forest Monitoring for Action – Rapid Identification of Pan-tropical Deforestation Using Moderate-Resolution Remotely Sensed Data (CGD Working Paper 192, November 2009) [pdf]

From REDD to Green: A Global Incentive System to Stop Tropical Forest Clearing (CGD Working Paper 282, December 2011) [pdf]

Forest Clearing in the Pantropics: December 2005-2011 (CGD Working Paper 283, December 2011) [pdf] Data Set for Working Paper 283

FORMA and fCPR: Accelerating a Performance-Based Payment System for REDD+ (CGD Policy Paper 006, June 2012) [pdf]

Satellite-Based Forest Clearing Detection in the Brazilian Amazon: FORMA, DETER, and PRODES (WRI Working Paper, February 2014)

GitHub Repositories:

REDD Metrics FORMA page

Geographic coverage of FORMA alerts
Download

Function

Displays the geographic coverage of FORMA alerts

RESOLUTION / SCALE

Regional

Geographic coverage

This data layer shows the geographic coverage of FORMA alerts, which largely corresponds to the extent of the humid tropical forest biome, as defined by Hansen et al. (2008), and based on WWF’s terrestrial ecoregions. The biome illustrated by this layer includes a number of smaller forest ecoregions, which span portions of 89 countries.

Source data

MODIS, validated with Landsat and CBERS

Date of content

2001

Citation: Olson, D. M., E. Dinerstein, E. D. Wikramanayake, N. D. Burgess, G. V. N. Powell, E. C. Underwood, J. A. D’Amico, I. Itoua, H. E. Strand, J. C. Morrison, C. J. Loucks, T. F. Allnutt, T. H. Ricketts, Y. Kura, J. F. Lamoreux, W.W. Wettengel, P. Hedao, and K. R. Kassem. 2001. “Terrestrial Ecoregions of the World: A New Map of Life on Earth.” BioScience 51, no. 11 (November): 933–38.

Download from CartoDB

forma geographic coverage

Function

Displays the geographic coverage of FORMA alerts

RESOLUTION / SCALE

Regional

Geographic coverage

This data layer shows the geographic coverage of FORMA alerts, which largely corresponds to the extent of the humid tropical forest biome, as defined by Hansen et al. (2008), and based on WWF’s terrestrial ecoregions. The biome illustrated by this layer includes a number of smaller forest ecoregions, which span portions of 89 countries.

Source data

MODIS, validated with Landsat and CBERS

Date of content

2001

Citation: Olson, D. M., E. Dinerstein, E. D. Wikramanayake, N. D. Burgess, G. V. N. Powell, E. C. Underwood, J. A. D’Amico, I. Itoua, H. E. Strand, J. C. Morrison, C. J. Loucks, T. F. Allnutt, T. H. Ricketts, Y. Kura, J. F. Lamoreux, W.W. Wettengel, P. Hedao, and K. R. Kassem. 2001. “Terrestrial Ecoregions of the World: A New Map of Life on Earth.” BioScience 51, no. 11 (November): 933–38.

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Imazon SAD alerts (monthly, 250m, Brazilian Amazon)

Download at project website

Function

Deforestation alert system that monitors forest cover loss and forest degradation

RESOLUTION / SCALE

250 × 250 meters

Geographic coverage

Brazilian Amazon

Source data

MODIS, validated with Landsat and CBERS

Frequency of updates

Monthly

Date of content

January 2007–present

Cautions

When zoomed out, this data layer displays some degree of inaccuracy because the data points must be collapsed to be visible on a larger scale. Zoom in for greater detail.

Overview

The Deforestation Alert System (Sistema de Alerta de Desmatamento—SAD) is a monthly alert that monitors forest cover loss and forest degradation in the Brazilian Amazon. The system generates information that is published monthly by Imazon, a Brazilian NGO, through its Forest Transparency Bulletin. The monthly alerts are derived from a temporal mosaic of MODIS daily images that are scaled down from 500 × 500 meter to 250 × 250 meter resolution. The monthly results are then validated using medium resolution images from the China-Brazil Earth Resources Satellite (CBERS) and NASA Landsat data in order to “ground-truth” the results being reported.

Citation: Souza, C. M., S. Hayashi, and A. Veríssimo. 2009. “Near Real-Time Deforestation Detection for Enforcement of Forest Reserves in Mato Grosso.” FIG—Land Governance in Support of the MDGS: Responding to New Challenges. www.fig.net/pub/fig_wb_2009/papers/trn/trn_2_souza.pdf.

Suggested citation for data as displayed on GFW: “SAD Alerts.” Imazon. Accessed through Global Forest Watch on [date].incendios.fan-bo.org.

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Geographic coverage of Imazon SAD alerts
Download

The geographic coverage of Imazon SAD alerts is the Legal Amazon (political) excluding the Brazilian state of Maranhão.

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Imazon geographic coverage

This layer displays the geographic coverage of SAD alerts, which only cover the Brazilian Amazon.

QUICC alerts (quarterly, 5km, <37 degrees north)

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Function

Identifies areas of land that have lost at least 40% of their green vegetation cover from the previous quarterly product

RESOLUTION / SCALE

5 × 5 kilometers

Geographic coverage

Global, except for areas >37 degrees north

Source data

MODIS

Frequency of updates

Quarterly (April, July, October, January)

Date of content

October 2011–present

Cautions

The data represents an indicator of vegetation cover change, not necessarily tree or forest cover loss.

When zoomed out, this data layer displays some degree of inaccuracy because the data points must be collapsed to be visible on a larger scale. Zoom in for greater detail.

Overview

The Quarterly Indicator of Cover Change (QUICC) product was developed at the NASA Ames Research Center by the CASA ecosystem modeling team. QUICC compares the MODIS global vegetation index (VI) images at the exact same time period each year on a quarterly basis (end of March, June, September, and December) and identifies land areas that have lost at least 40% of their green vegetation from the previous product and over the past year. This level of green vegetation loss is commonly associated with major forest or tree cover loss.

The CASA team updates the global QUICC products as soon as the newest quarterly MODIS worldwide VI image is produced. After September (Q3) 2012, the data were adjusted to exclude forest areas located >37 degrees north as a result of confusion caused by year-to-year variations in seasonal snow cover.

Citation: NASA-CASA Project. “CASA ‘Quarterly Indicator of Cover Change’ (QUICC).” Accessed on [date].geo.arc.nasa.gov/sge/casa/latest.html.

Suggested citation for data as displayed on GFW: “QUICC Alerts.” NASA Ames Research Center and California State University. Accessed through Global Forest Watch on [date].incendios.fan-bo.org.

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Geographic coverage of QUICC alerts

The geographic coverage of QUICC alerts is global, except for areas >37 degrees north.

quicc geographic coverage

This layer displays the geographic coverage of QUICC alerts, which is all areas <37 degrees north.

NASA active fires (daily, 1km, global)

Download at project website

Function

Displays fire alert data for the past 7 days

RESOLUTION / SCALE

1 × 1 kilometer

Geographic coverage

Global

Source data

MODIS

Frequency of updates

Daily

Date of content

Past 7 days

Cautions

Not all fires are detected. There are several reasons why MODIS may not have detected a certain fire. The fire may have started and ended between satellite overpasses. The fire may have been too small or too cool to be detected in the (approximately) 1 km² pixel. Cloud cover, heavy smoke, or tree canopy may completely obscure a fire.

It is not recommended to use active fire locations to estimate burned area due to spatial and temporal sampling issues.

When zoomed out, this data layer displays some degree of inaccuracy because the data points must be collapsed to be visible on a larger scale. Zoom in for greater detail.

Overview

The Fire Information for Resource Management System (FIRMS) delivers global MODIS-derived hotspots and fire locations. The active fire locations represent the center of a 1-kilometer pixel that is flagged by the MOD14/MYD14 Fire and Thermal Anomalies Algorithm as containing one or more fires within the pixel.

The near real-time active fire locations are processed by the NASA Land and Atmosphere Near Real-Time Capability for EOS (LANCE) using the standard MODIS Fire and Thermal Anomalies product (MOD14/MYD14). Data older than the past 7 days can be obtained from the Archive Download Tool. The tool provides near real-time data and, as it becomes available and is replaced with the standard NASA (MCD14ML) fire product.

More information on active fire data is available from the NASA FIRMS website.

Citation:NASA FIRMS. “NASA Fire Information for Resource Management System (FIRMS).” Accessed on [date]. earthdata.nasa.gov/data/near-real-time-data/firms.

Suggested citation for data as displayed on GFW: “NASA Active Fires.” NASA FIRMS. Accessed through Global Forest Watch on [date]. incendios.fan-bo.org.

Learn more or download data at the NASA FIRMS website

Terra-i Alerts (monthly, 250m, Latin America)

Download at project website

Function

Detects areas in Latin American where tree cover loss is likely to have recently occurred

Resolution/scale

250 × 250 meters

Geographic coverage

Latin America

Source data

Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices and water body’ presence data; Tropical Rainfall Measuring Mission (TRMM) precipitation data

Frequency of updates

Monthly

Date of content

2004 – present

Cautions

Given the lack of ground-based data, the methodology was validated using data from other forest monitoring systems such as PRODES (http://www.obt.inpe.br/prodes/index.php) which have been validated separately.

All clouds, water, and mist were masked based on MODIS Quality Assessment and MOD35 products and their values changed to “No Data”.

The Terra-i algorithm for change detection does not automatically identify events that occurred because of wild fires or within secondary forests or oil palm plantations. Furthermore, the moderate resolution of the MODIS sensor does not detect small scale events (<5ha). Terra-i is intended to be used to quickly identify deforestation hotspots which should then be more thoroughly investigated with higher resolution imagery or field validation.

Overview

Terra-i is a near real-time monitoring system that detects land cover changes in Latin America. It uses satellite data from MODIS vegetation indices (MOD13Q1 and NDVI) and products related to presence of water bodies (MOD35) as well as Tropical Rainfall Measuring Mission (TRMM) precipitation data to detect anthropogenic changes in vegetation cover every 16 days. Terra-i is a collaboration between the International Center for Tropical Agriculture (CIAT - DAPA), CGIAR’s Research Program on Forestry, Trees and Agroforestry (FTA), The Nature Conservancy (TNC), the University of Applied Sciences Western Switzerland (HEIG-VD), and King’s College London (KCL).

The system, which uses a computational algorithm similar to FORMA (http://incendios.fan-bo.org/sources/forest_change#forma), is based on the premise that natural vegetation follows a predictable pattern of change in greenness from one date to the next, brought about by site-specific land and climatic conditions over the same period. The model is trained to understand the normal pattern of changes in vegetation greenness in relation to terrain and rainfall for a site, which allows for prediction of what the next vegetation response should be based on the historical data. If the prediction is significantly different from the historical responses in relation to pattern of rainfall and lasts for two 16-day periods in a row, the pixel is marked as potentially having changed by anthropogenic means.

Citation:Reymondin, Louis, Andrew Jarvis, Andres Perez-Uribe, Jerry Touval, Karolina Argote, Julien Rebetez, Edward Guevara, and Mark Mulligan. 2012. “Terra-i: A methodology for near real-time monitoring of habitat change at continental scales using MODIS-NDVI and TRMM.” CIAT-Terra-i. http://terra-i.org/dms/docs/reports/Terra-i-Method/Terra-i%20Method.pdf.

Suggested citation for data as displayed on GFW: Reymondin, Louis, Andrew Jarvis, Andres Perez-Uribe, Jerry Touval, Karolina Argote, Julien Rebetez, Edward Guevara, and Mark Mulligan. 2012. “Terra-i alerts." CIAT-Terra-i. Accessed through Global Forest Watch on [date].incendios.fan-bo.org.

Learn more or download data at the Terra-i website

terra-i geographic coverage

This layer displays the geographic coverage of Terra-i alerts.

Forest cover

Forest cover data measure the extent of forests, forest ecosystems, and related features such as carbon stocks.

Tree cover

Download at project website

Function

Identifies areas of tree cover

RESOLUTION / SCALE

30 × 30 meters

Geographic coverage

Global land (excluding Antarctica and Arctic islands)

Source data

Landsat 7 ETM+

Date of content

2000

Tree cover canopy density

Varies according to selection (click the gear icon on the map to change the minimum tree cover canopy density threshold)

Cautions

For the purpose of this study, “tree cover” was defined as all vegetation taller than 5 meters in height. “Tree cover” is the biophysical presence of trees and may take the form of natural forests or plantations existing over a range of canopy densities.

Overview

This data set displays tree cover over all global land (except for Antarctica and a number of Arctic islands) for the year 2000 at 30 × 30 meter resolution. “Percent tree cover” is defined as the density of tree canopy coverage of the land surface and is color-coded by density bracket (see legend).

Data in this layer were generated using multispectral satellite imagery from the Landsat 7 thematic mapper plus (ETM+) sensor. The clear surface observations from over 600,000 images were analyzed using Google Earth Engine, a cloud platform for earth observation and data analysis, to determine per pixel tree cover using a supervised learning algorithm.

Citation: Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend. 2013. “High-Resolution Global Maps of 21st-Century Forest Cover Change.” Science 342 (15 November): 850–53. Data available on-line from: http://earthenginepartners.appspot.com/science-2013-global-forest.

Suggested citation for data as displayed on GFW: Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend. 2013. “Tree Cover.” University of Maryland, Google, USGS, and NASA. Accessed through Global Forest Watch on [date]. incendios.fan-bo.org.

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Tropical forest carbon stocks

Function

Shows total carbon stock values in live biomass across the tropics

RESOLUTION / SCALE

1 × 1 kilometer (100 ha)

Geographic coverage

Tropics

Source data

ICESAT GLAS Lidar and other radar satellite imagery

Date of content

Early 2000s

Cautions

The forest above and below ground biomass were produced at 1 × 1 kilometer (100 ha) spatial resolution. The values for each pixel (1 × 1 km) refer to the biomass of forests remaining within the pixel and can be used directly to estimate total carbon stock in forests within one pixel. Along with the biomass values, there is an error map at the same spatial resolution providing the uncertainty in biomass estimation. It is recommended that both biomass and uncertainty values be used together for carbon assessments and verifications. The map will provide accurate estimates of total carbon stock and carbon density when aggregated to large areas (5,000-10,000 ha) for project and regional level assessments. The biomass value of a single pixel may have large uncertainty when compared with small plots for verification.

Overview

The Tropical Forest Carbon Stocks data layer shows a “benchmark” map of biomass carbon stocks for more than 2.5 billion hectares of forests on three continents, encompassing all tropical forests, for the early 2000s. Researchers from NASA’s Jet Propulsion Laboratory (JPL) and Winrock International developed the layer by collecting data from more than 4,000 in situ inventory plots, plus optical and microwave imagery (1 km resolution) to extrapolate the amount of calculated carbon stocks from forests distributed over the South American, Southeast Asia, and the sub-Saharan African regions. Further data on tree height and landscape characteristics across the tropics were derived using satellite light detection and ranging (Lidar) data from the ICESAT GLAS Lidar. This data set also helps illustrate regional patterns and provides methodologically comparable estimates of carbon stocks for 75 developing countries where previous assessments were either poor or incomplete.

Citation: Saatchi, S.S., N.L. Harris, S. Brown, M. Lefsky, E. Mitchard, W. Salas, B. Zutta, W. Buermann, S. Lewis, S. Hagen, S. Petrova, L. White, M. Silman, and A. Morel. 2011. “Benchmark map of forest carbon stocks in tropical regions across three continents.” Proceedings of the National Academy of Sciences vol 108, no. 24, pp 9899-9904. DOI: 10.1073/pnas.1019576108.

Learn more or download data at the NASA Jet Propulsion Laboratory website.
Intact Forest Landscapes 2000/2013

Download at project website

Function

Identifies the world’s last remaining undisturbed forest areas, large enough to retain all native biodiversity and showing no signs of human activity as of the year 2013 and reduction in their extent from 2000-2013.

RESOLUTION / SCALE

Approximately 1:100,000

Geographic coverage

Global

Source data

Landsat TM/ETM+

Frequency of updates

2014 update; 2006 original publication

Date of content

2013

Cautions

The world IFL map was created through visual interpretation of Landsat images by experts. The map may contain inaccuracies due to limitations in the spatial resolution of the imagery and lack of ancillary information about local land-use practices in some regions. In addition, the methodology assumes that fire scars in proximity to roads or other infrastructure have been caused by humans, and therefore constitute a form of significant human activity. This assumption could result in an underestimation of IFL extent in the boreal ecozone. The attribution of forest fires to human influence across boreal forest landscapes is disputed.

Overview

The Intact Forest Landscapes (IFL) data set identifies unbroken expanses of natural ecosystems within the zone of forest extent that show no signs of significant human activity and are large enough that all native biodiversity, including viable populations of wide-ranging species, could be maintained. To map IFL areas, a set of criteria was developed and designed to be globally applicable and easily replicable, the latter to allow for repeated assessments over time as well for verification. IFL areas were defined as unfragmented landscapes, at least 50,000 hectares in size, and with a minimum width of 10 kilometers. These were then mapped and identified from Landsat satellite imagery for the year 2013.

Changes in the extent of IFLs were identified by contrasting the map for 2013 with the analogous map for 2000, adjusted for consistency. Areas identified as “reduction in extent” met the IFL criteria in 2000, but no longer met the criteria in 2013. The main causes of change were industrial activity such as logging and mining, and fragmentation due to infrastructure and new roads, and fires assumed to be caused by humans.

This data can be used to assess forest intactness, alteration, and degradation at global and regional scales. More information about the data set and methodology is available on www.intactforests.org

Citation: Potapov, P., A. Yaroshenko, S. Turubanova, M. Dubinin, L. Laestadius, C. Thies, D. Aksenov, A. Egorov, Y. Yesipova, I. Glushkov, M. Karpachevski, A. Kostickova, A. Manisha, E. Tsybikova, and I. Zhuravleva. 2008. “Mapping the World’s Intact Forest Landscapes by Remote Sensing.” Ecology and Society 13, no. 2: Art. 51. www.ecologyandsociety.org/vol13/iss2/art51.

Suggested citations for data as displayed on GFW: Greenpeace, University of Maryland, World Resources Institute and Transparent World. 2014. Intact Forest Landscapes: update and reduction in extent from 2000-2013. Accessed through Global Forest Watch on [date]. incendios.fan-bo.org

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Intact Forest Landscapes 2000/2013

Download at project website

Function

Identifies the world’s last remaining undisturbed forest areas, large enough to retain all native biodiversity and showing no signs of human activity as of the year 2013 and reduction in their extent from 2000-2013.

RESOLUTION / SCALE

Approximately 1:100,000

Geographic coverage

Global

Source data

Landsat TM/ETM+

Frequency of updates

2014 update; 2006 original publication

Date of content

2013

Cautions

The world IFL map was created through visual interpretation of Landsat images by experts. The map may contain inaccuracies due to limitations in the spatial resolution of the imagery and lack of ancillary information about local land-use practices in some regions. In addition, the methodology assumes that fire scars in proximity to roads or other infrastructure have been caused by humans, and therefore constitute a form of significant human activity. This assumption could result in an underestimation of IFL extent in the boreal ecozone. The attribution of forest fires to human influence across boreal forest landscapes is disputed.

Overview

The Intact Forest Landscapes (IFL) data set identifies unbroken expanses of natural ecosystems within the zone of forest extent that show no signs of significant human activity and are large enough that all native biodiversity, including viable populations of wide-ranging species, could be maintained. To map IFL areas, a set of criteria was developed and designed to be globally applicable and easily replicable, the latter to allow for repeated assessments over time as well for verification. IFL areas were defined as unfragmented landscapes, at least 50,000 hectares in size, and with a minimum width of 10 kilometers. These were then mapped and identified from Landsat satellite imagery for the year 2013.

Changes in the extent of IFLs were identified by contrasting the map for 2013 with the analogous map for 2000, adjusted for consistency. Areas identified as “reduction in extent” met the IFL criteria in 2000, but no longer met the criteria in 2013. The main causes of change were industrial activity such as logging and mining, and fragmentation due to infrastructure and new roads, and fires assumed to be caused by humans.

This data can be used to assess forest intactness, alteration, and degradation at global and regional scales. More information about the data set and methodology is available on www.intactforests.org

Citation: Potapov, P., A. Yaroshenko, S. Turubanova, M. Dubinin, L. Laestadius, C. Thies, D. Aksenov, A. Egorov, Y. Yesipova, I. Glushkov, M. Karpachevski, A. Kostickova, A. Manisha, E. Tsybikova, and I. Zhuravleva. 2008. “Mapping the World’s Intact Forest Landscapes by Remote Sensing.” Ecology and Society 13, no. 2: Art. 51.www.ecologyandsociety.org/vol13/iss2/art51.

Suggested citations for data as displayed on GFW: Greenpeace, University of Maryland, World Resources Institute and Transparent World. 2014. Intact Forest Landscapes: update and reduction in extent from 2000-2013. Accessed through Global Forest Watch on [date]. incendios.fan-bo.org

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Indonesia primary forest

Download at project website

Function

Identifies the location of intact and degraded primary forests across Indonesia as of the year 2000

RESOLUTION / SCALE

30 × 30 meters

Geographic coverage

Indonesia

Source data

Landsat

Date of content

2000

Cautions

This layer represents a draft visualization of the data. Artifacts such as white vertical lines, or visually degraded pixels may occur temporarily. Also note that definition of primary forests used to create this layer may not match other definitions of primary forests. See the overview section for details.

Overview

This data set indicates the location of intact and degraded primary forests across Indonesia as of the year 2000. Primary forest consist of mature natural forest cover that has not been completely cleared in recent history (30 years or more) and consisted of a contiguous block of 5 ha or more. Primary forest cover was mapped using Landsat composites and multi-temporal metrics as input data to a two-step supervised classification. The first step was a per-pixel classification of areas with tree canopy cover of 30% and above for the 2000 reference year.

A second per-pixel classification procedure was performed to separate primary forest from other tree cover for 2000; contiguous areas of 5 ha and greater were retained as primary forest. A limited editing of this classification was performed to remove older plantations and adjust other forest formations that could not be identified using the per-pixel classifier, but could be identified in photo-interpretive contexts. Primary forests were subsequently characterized into primary intact and primary degraded subclasses using the GIS-based buffering approach of the Intact Forest Landscapes (IFL). To create the IFL layer, buffers of roads, settlements and other signs of human landscape alteration were used to identify degraded areas within zones of primary forest cover. IFL mapping employed cloud-free Landsat mosaics to quantify changes in primary intact forest extent. The map of primary intact and primary degraded forest cover types corresponds to the Indonesia Ministry of Forestry’s primary and secondary forest cover types.

Citation: Margono, B. Primary forest cover loss in Indonesia over 2000–2012. Nature Climate Change,doi:10.1038/nclimate2277. Retrieved June 30, 2014, from Nature

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Mangroves

Download at project website

Function

This data set shows the global distribution of mangrove forests, derived from earth observation satellite imagery

RESOLUTION / SCALE

Mapped from 30m Landsat imagery

Geographic coverage

Global

Source data

Landsat Global Land Survey Collection

Frecuency of updates

None planned

Date of content

1997-2000

Cautions

Results were validated using existing distribution data and published literature.
Note that small patches (< 900-2,700 sq-m) of mangrove forests cannot be identified using this approach. This methodological approach had a number of challenges, such as cloud cover and noise. There may also be areas where land cover was misclassified.
As the data set may still contain overlapping polygons, a dissolve operation (within a GIS) might be needed before surface area calculations are carried out.

Overview

To improve scientific understanding of the extent and distribution of mangrove forests of the world the status and distribution of global mangroves were mapped using recently available Global Land Survey (GLS) data and the Landsat archive.The project interpreted approximately 1000 Landsat scenes using hybrid supervised and unsupervised digital image classification techniques. Results were validated using existing GIS data and the published literature to map ‘true mangroves’.

The total area of mangroves in the year 2000 was 137,760 km2 in 118 countries and territories in the tropical and subtropical regions of the world. Approximately 75% of world's mangroves are found in just 15 countries, and only 6.9% are protected under the existing protected areas network (IUCN I-IV). Our study confirms earlier findings that the biogeographic distribution of mangroves is generally confined to the tropical and subtropical regions and the largest percentage of mangroves is found between 5° N and 5° S latitude.

The remaining area of mangrove forest in the world is less than previously thought; the estimate provided in this study is 12.3% smaller than the most recent estimate by the Food and Agriculture Organization (FAO) of the United Nations. This data set presents the most comprehensive, globally consistent and highest resolution (30 m) global mangrove database ever created

Citation: Giri C, Ochieng E, Tieszen LL, Zhu Z, Singh A, Loveland T, Masek J, Duke N (2011). Status and distribution of mangrove forests of the world using earth observation satellite data. Global Ecology and Biogeography 20: 154-159.

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USA land cover

Function

Identifies land cover for the United States, utilizing the National Land Cover Database (NLCD) for 2011

RESOLUTION / SCALE

30 × 30 meters

Geographic coverage

Contiguous United States (excluding Alaska and Hawaii)

Source data

Landsat

Frequency of updates

Every 5 years

Date of content

2011

Cautions

NLCD land cover products have been published for 2001, 2006, and 2011. A formal accuracy assessment has not been conducted for NLCD 2011 Land Cover.

An assessment of accuracy for the NLCD land cover product found overall accuracies for the 2001 and 2006 products were 79% and 78%, respectively, with accuracies exceeding 80% for water, high density urban, all upland forest classes, shrubland, and cropland for both dates.

License

U.S. Federal data is offered for free and without restriction. https://project-open-data.cio.gov/policy-memo/

Overview

The National Land Cover Database 2011 (NLCD 2011) is the most recent national data product created by the United States Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC is a group of federal agencies who coordinate and generate consistent and relevant land cover information at the national scale for a wide variety of environmental, land management, and modeling applications. NLCD 2011 provides - for the first time - the capability to assess wall-to-wall, spatially explicit, national land cover changes and trends across the United States from 2001 to 2011. As with two previous NLCD land cover products NLCD 2011 keeps the same 16-class land cover classification scheme that has been applied consistently across the United States at a spatial resolution of 30 meters. NLCD 2011 is based primarily on a decision-tree classification of circa 2011 Landsat satellite data.

The 2011 land cover layer is one of five primary data products produced as part of the NLCD 2011: 1) NLCD 2011 Land Cover 2) NLCD 2006/2011 Land Cover Change Pixels labeled with the 2011 land cover class 3) NLCD 2011 Percent Developed Imperviousness 4) NLCD 2006/2011 Percent Developed Imperviousness Change Pixels 5) NLCD 2011 Tree Canopy Cover.

Land cover class categories include forest, planted/cultivated lands, wetland, grassland, water, developed areas and barren land. Land cover information is critical for local, state, and federal managers and officials to assist them with issues such as assessing ecosystem status and health, modeling nutrient and pesticide runoff, understanding spatial patterns of biodiversity, land use planning, deriving landscape pattern metrics, and developing land management policies.

Citation: Jin, S., Yang, L., Danielson, P., Homer, C., Fry, J., and Xian, G. 2013. “A comprehensive change detection method for updating the National Land Cover Database to circa 2011.” Remote Sensing of Environment, 132: 159 – 175.

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USA land cover change

Download at project website

Function

This layer displays change in land cover between 2001 and 2011. Pixels that changed during this period display the land cover value that they changed to. Pixels with no change are transparent.

RESOLUTION / SCALE

30 × 30 meters

Geographic coverage

Contiguous United States (excluding Alaska and Hawaii)

Source data

Landsat

Frecuency of updates

Approximately every 5 years (2001, 2006, and 2011 now available)

Date of content

2001 to 2011

Cautions

NLCD land cover products have been published for 2001, 2006, and 2011, with change products available for 2001 to 2006, 2006 to 2011, and 2001 to 2011. This layer contains less overall change than the sum of 2001/2006 and 2006/2011 land cover change pixels as some transitioned through two classes from 2001 to 2006 to 2011. In this case, the latest change class is given.

An assessment of accuracy for the NLCD land cover product found overall accuracies for the 2001 and 2006 products were 79% and 78%, respectively, with accuracies exceeding 80% for water, high density urban, all upland forest classes, shrubland, and cropland for both dates.

License

U.S. Federal data is offered for free and without restriction. https://project-open-data.cio.gov/policy-memo/

Overview

This layer displays change in US land cover between 2001 and 2011. Pixels that changed during this period display the land cover value that they changed to. Pixels with no change are transparent.

The National Land Cover Database 2011 (NLCD 2011) is the most recent national data product created by the United States Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC is a group of federal agencies who coordinate and generate consistent and relevant land cover information at the national scale for a wide variety of environmental, land management, and modeling applications. NLCD 2011 provides - for the first time - the capability to assess wall-to-wall, spatially explicit, national land cover changes and trends across the United States from 2001 to 2011. As with two previous NLCD land cover products NLCD 2011 keeps the same 16-class land cover classification scheme that has been applied consistently across the United States at a spatial resolution of 30 meters. NLCD 2011 is based primarily on a decision-tree classification of circa 2011 Landsat satellite data.

The 2001/2011 land cover change layer is one of five primary data products produced as part of the NLCD 2011: 1) NLCD 2011 Land Cover 2) NLCD 2006/2011 Land Cover Change Pixels labeled with the 2011 land cover class 3) NLCD 2011 Percent Developed Imperviousness 4) NLCD 2006/2011 Percent Developed Imperviousness Change Pixels 5) NLCD 2011 Tree Canopy Cover.

Land cover class categories include forest, planted/cultivated lands, wetland, grassland, water, developed areas and barren land. Land cover information is critical for local, state, and federal managers and officials to assist them with issues such as assessing ecosystem status and health, modeling nutrient and pesticide runoff, understanding spatial patterns of biodiversity, land use planning, deriving landscape pattern metrics, and developing land management policies

Citation: Jin, S., Yang, L., Danielson, P., Homer, C., Fry, J., and Xian, G. 2013. A comprehensive change detection method for updating the National Land Cover Database to circa 2011. Remote Sensing of Environment, 132: 159 – 175.

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GlobCover – Global landcover (2009)

Function

Maps land cover distribution globally.

RESOLUTION / SCALE

300 × 300 meters

Geographic coverage

Global

Source data

MERIS

Frecuency of updates

None planned

Date of content

2009

Cautions

RData gaps in the MERIS 2009 satellite acquisitions (about 5% of the total data area) were filled using the GlobCover 2005 land cover map.

The lack of a short-wave infrared (SWIR) band in the MERIS sensor may result in underestimation of flooded forests. These classes were therefore imported from the 2005 GlobCover land cover map.

Delineation between land and water is not absolutely correct: it is not exhaustive, especially regarding inland water bodies, and it presents some geo-location inaccuracies.

Overview

GlobCover is a European Space Agency (ESA) initiative which began in 2005 in partnership with the Joint Research Center, European Environmental Agency, UN Food and Agricultural Organization, UN Environment Programme, Global Observation of Forest Cover and Land Cover Dynamics, and International Geosphere-Biosphere Programme. The aim of the project was to develop a service capable of delivering global composites and land cover maps using observations from the 300 meter MERIS sensor on board the ENVISAT satellite mission. ESA makes land cover maps available covering 2 periods: December 2004 - June 2006 and January - December 2009. GlobCover products come with a thematic legend compatible with the UN Land Cover Classification System (LCCS).

Data in this layer was generated using MERIS images which were classified using both a supervised (human-verified) and unsupervised (automated)classification algorithm applied at two different seasonal time steps to create land cover classes based on both spectral and temporal properties of land cover. The labelling procedure is automated and based on the GlobCover 2005 (V2.2) land cover map. Several decision rules have been defined with the help of international land cover experts to create unique labels for each class. For more information, see due.esrin.esa.int/globcover/.

Citation: © ESA 2010 and UCLouvain

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Forest use

Forest use data measure human use of forests, especially the boundaries of areas allocated for a certain land use through concessions, licenses, permits, titles, management units, etc.

Managed forests
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Function

Displays boundaries of forested areas allocated by governments to companies for harvesting timber and other wood products.

RESOLUTION / SCALE

Varies by country

Geographic coverage

Currently available for Cameroon, Canada, Central African Republic, Democratic Republic of the Congo (DRC), Equatorial Guinea, Gabon, Indonesia, Liberia, and Republic of the Congo.

Source data

Generally based on a combination of government documents, satellite imagery, and GPS data. For information on country-specific concessions data please refer to the Data page.

Frequency of updates

Variable, depending on government agencies in each country and other data providers

Date of content

Varies by country

Cautions

This layer is a compilation of concession data from various countries and sources. The quality of these data can vary depending on the source. This layer may not be comprehensive of all existing concessions in a country, and the location of certain concessions can be inaccurate.

Overview

“Managed forests” refers to areas allocated by a government for harvesting timber and other wood products in a public forest. Managed forests are distinct from wood fiber concessions, where tree plantations are established for the exclusive production of pulp and paper products. “Concession” is used as a general term for licenses, permits, or other contracts that confer rights to private companies to manage and extract timber and other wood products from public forests; terminology varies at the national level, however, and includes "forest permits," "tenures," "licenses," and other terms.

This data set displays managed forest concessions as a single layer assembled by aggregating data for multiple countries. The data may come from government agencies, NGOs, or other organizations and varies by date and data sources. For more information on concession data for each country please visit the Open Data Portal.

If you are aware of concession data for additional countries, please email us here.

Suggested citation for data as displayed on GFW: “Managed forests.” World Resources Institute. Accessed through Global Forest Watch on [date]. incendios.fan-bo.org.

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GFW currently includes logging concession data for the following countries:
Select a country
Cameroon forest management units

Canada forest tenures

Central African republic logging permits

Democratic Republic of the Congo forest titles

Equatorial Guinea logging concessions

Gabon forest licenses

Indonesia logging concessions

Liberia logging concessions

Republic of the Congo logging concessions
Download

Logging in Cameroon’s forests is permitted within Forest Management Units (FMUs). This data set displays the FMUs within Cameroon’s permanent forest estate. Selective logging is permitted in Cameroon’s FMUs, which are further divided into logging concessions called annual allowable cuts (AACs). These logging permits require owners and operators to maintain permanent forest cover. This data set was produced in collaboration between the Cameroon Ministry of Forestry and Wildlife and WRI. For more information and data sets, see the Interactive Forest Atlas for Cameroon.

Credit: Cameroon Ministry of Forestry and Wildlife, World Resources Institute.

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This data set provides the boundaries of forest areas licensed to companies for forestry and is a compilation of provincial forest tenure data sets across Canada. Tenures for Nova Scotia are not provided, due to changes underway in forest management in that province, and will be added to this data set when available. Much of Canada’s logging activity occurs on Crown (often referred to as “public”) land and is regulated by various provincial commercial forest tenure systems that allocate cutting rights to and confer obligations on recipients of the tenures. It is these tenure systems on Crown forest land that are the focus of this data product. The information in this data set was gathered in order to continue to develop an understanding of how much of Canada’s forest area is under commercial forest tenures, where these tenures (including the operating areas of major forest companies) are located, and who is most likely to control them. This information and these data sets are important because of the extent of tenures and the resulting logging activity over vast areas of Canada’s Crown forest land.

Credit: Global Forest Watch Canada, 2013.

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This data set provides the permit boundaries for selective logging in the Central African Republic’s production forests. This data set was produced through a collaboration between the CAR Ministry of Water, Forests, Hunting, and Fishing (MEFCP) and WRI. For more information, see the Interactive Forest Atlas for the Central African Republic.

Credit: Central African Republic Ministry of Water and Forests, Hunting, and Fishing; German Technical Cooperation (GIZ); French Development Agency (AFD); Special Allocation Fund for Forest Development (CASDF); World Resources Institute

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Forest concession data for the Democratic Republic of the Congo (DRC) represent geographic areas permitted for exploitation of timber by selective logging. This data set was produced through a collaboration between the DRC Ministry of Environment, Nature Conservation, and Tourism (MECNT) and WRI. For more information, see the Interactive Forest Atlas for the Democratic Republic of the Congo

Credit: Democratic Republic of the Congo Ministry of Environment, Nature Conservation, and Tourism (MECNT); Department for Permanent Service for Forest Inventory and Management (SPIAF); World Resources Institute; Asset Management and Forest Management (DIAF); Forest Management Branch (FMB)

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This data set provides the boundaries for logging concessions for Equatorial Guinea, where commercial forestry is permitted. The Equatorial Guinea Ministry of Agriculture and Forests and the World Resources Institute produced this information in a collaboration for the Interactive Forest Atlas of Equatorial Guinea. Information provided in the data set includes the boundaries of concessions, the operating company, the ownership group, documentation on the permit process, and other information.

Credit: Equatorial Guinea Ministry of Agriculture and Forests and the World Resources Institute, 2013

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This data set provides the boundaries for forest licenses in Gabon. The licenses cover areas permitted for selective logging. This data set was produced in a collaboration between the Gabon Ministry of Forest Economy, Water, Fisheries, and Aquaculture (MEFEPA) and WRI. For more information, see the Interactive Forest Atlas for Gabon.

Credit: Gabon Ministry of Forest Economy, Water, Fisheries, and Aquaculture (MEFEPA); World Resources Institute

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This data set, produced by the Indonesia Ministry of Forestry, provides the boundaries of logging concessions for the selective logging of natural forests in Indonesia. According to this data set, there are 557 active logging concessions in Indonesia.

Credit: Indonesia Ministry of Forestry

Download

The Liberia logging concessions data set combines the boundaries of forest management contracts, timber sale contracts, and private use permits, compiled by Global Witness from available government and contractual maps. Due to a lack of quality data, this data set should be used for demonstration purposes only and not for land use planning purposes. Forests in Liberia are managed by the state under the National Forestry Reform Law, enacted in October 2006. Following the enactment of this law, UN Security Council timber export sanctions against Liberia were lifted, permitting commercial forestry activities to resume. Forest management contracts include concession areas of 50,000 hectares to 400,000 hectares and are open for bids from qualified bidders that demonstrate at least 51% ownership by Liberian citizens; concessions of more than 100,000 hectares are open for bidding from international investors. Timber sale contracts are established through a bidding process for areas up to 5,000 hectares; bidders must demonstrate at least 51% ownership by Liberian citizens. Private Use Permits are licenses issued to private landowners to extract wood and lack sustainability regulations. Global Witness compiled the logging concession data as part of the report Signing Their Lives Away: Liberia’s Private Use Permits and the Destruction of Community Owned Rainforest (Global Witness, 2012).

Credit: Global Witness, 2012

Download

Forest concession data for the Republic of the Congo provide the boundaries of areas permitted for selective logging. These areas, also called Forest Exploitation Units, are managed in accordance with the national Forest Code. This data set was produced through a collaboration between the Republic of the Congo Ministry of Forest Economy and WRI. For more information, see the Interactive Forest Atlas for the Republic of the Congo.

Credit: Republic of the Congo Ministry of Forest Economy (MEF), National Center for Inventory and Planning of Forest and Wildlife Resources (CNIAF), World Resources Institute
Canada forest tenures

Overview

This data set provides the boundaries of forest areas licensed to companies for forestry and is a compilation of provincial forest tenure data sets across Canada.

Tenures for Nova Scotia are not provided, due to changes underway in forest management in that province, and will be added to this data set when available. Much of Canada’s logging activity occurs on Crown (often referred to as “public”) land and is regulated by various provincial commercial forest tenure systems that allocate cutting rights to and confer obligations on recipients of the tenures. It is these tenure systems on Crown forest land that are the focus of this data product. The information in this data set was gathered in order to continue to develop an understanding of how much of Canada’s forest area is under commercial forest tenures, where these tenures (including the operating areas of major forest companies) are located, and who is most likely to control them. This information and these data sets are important because of the extent of tenures and the resulting logging activity over vast areas of Canada’s Crown forest land.

Credit:Global Forest Watch Canada, 2013.

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Cameroon forest management units

Overview

Logging in Cameroon’s forests is permitted within Forest Management Units (FMUs). This data set displays the FMUs within Cameroon’s permanent forest estate. Selective logging is permitted in Cameroon’s FMUs, which are further divided into logging concessions called annual allowable cuts (AACs). These logging permits require owners and operators to maintain permanent forest cover. This data set was produced in collaboration between the Cameroon Ministry of Forestry and Wildlife and WRI. For more information and data sets, see the Interactive Forest Atlas for Cameroon.

Credit:Cameroon Ministry of Forestry and Wildlife, World Resources Institute.

Learn more and download data
Central African Republic logging permits

Overview

This data set provides the permit boundaries for selective logging in the Central African Republic’s production forests. This data set was produced through a collaboration between the CAR Ministry of Water, Forests, Hunting, and Fishing (MEFCP) and WRI. For more information, see the Interactive Forest Atlas for the Central African Republic.

Credit:Central African Republic Ministry of Water and Forests, Hunting, and Fishing; German Technical Cooperation (GIZ); French Development Agency (AFD); Special Allocation Fund for Forest Development (CASDF); World Resources Institute

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Democratic Republic of the Congo forest titles

Overview

Forest concession data for the Democratic Republic of the Congo (DRC) represent geographic areas permitted for exploitation of timber by selective logging. This data set was produced through a collaboration between the DRC Ministry of Environment, Nature Conservation, and Tourism (MECNT) and WRI. For more information, see the Interactive Forest Atlas for the Democratic Republic of the Congo.

Credit:Democratic Republic of the Congo Ministry of Environment, Nature Conservation, and Tourism (MECNT); Department for Permanent Service for Forest Inventory and Management (SPIAF); World Resources Institute; Asset Management and Forest Management (DIAF); Forest Management Branch (FMB)

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Equatorial Guinea logging concessions

Overview

This data set provides the boundaries for logging concessions for Equatorial Guinea, where commercial forestry is permitted. The Equatorial Guinea Ministry of Agriculture and Forests and the World Resources Institute produced this information in a collaboration for the Interactive Forest Atlas of Equatorial Guinea. Information provided in the data set includes the boundaries of concessions, the operating company, the ownership group, documentation on the permit process, and other information.

Credit:Equatorial Guinea Ministry of Agriculture and Forests and the World Resources Institute, 2013

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Gabon forest licenses

Overview

This data set provides the boundaries for forest licenses in Gabon. The licenses cover areas permitted for selective logging. This data set was produced in a collaboration between the Gabon Ministry of Forest Economy, Water, Fisheries, and Aquaculture (MEFEPA) and WRI. For more information, see the Interactive Forest Atlas for Gabon.

Credit:Gabon Ministry of Forest Economy, Water, Fisheries, and Aquaculture (MEFEPA); World Resources Institute

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Indonesia logging concessions

Overview

This data set, produced by the Indonesia Ministry of Forestry, provides the boundaries of logging concessions for the selective logging of natural forests in Indonesia. According to this data set, there are 557 active logging concessions in Indonesia.

Credit:Indonesia Ministry of Forestry

Learn more and download data
Liberia logging concessions

Overview

The Liberia logging concessions data set combines the boundaries of forest management contracts, timber sale contracts, and private use permits, compiled by Global Witness from available government and contractual maps.

Due to a lack of quality data, this data set should be used for demonstration purposes only and not for land use planning purposes. Forests in Liberia are managed by the state under the National Forestry Reform Law, enacted in October 2006. Following the enactment of this law, UN Security Council timber export sanctions against Liberia were lifted, permitting commercial forestry activities to resume. Forest management contracts include concession areas of 50,000 hectares to 400,000 hectares and are open for bids from qualified bidders that demonstrate at least 51% ownership by Liberian citizens; concessions of more than 100,000 hectares are open for bidding from international investors.

Timber sale contracts are established through a bidding process for areas up to 5,000 hectares; bidders must demonstrate at least 51% ownership by Liberian citizens. Private Use Permits are licenses issued to private landowners to extract wood and lack sustainability regulations. Global Witness compiled the logging concession data as part of the report Signing Their Lives Away: Liberia’s Private Use Permits and the Destruction of Community Owned Rainforest (Global Witness, 2012).

Credit:Global Witness, 2012

Learn more and download data
Republic of the Congo logging concessions

Overview

Forest concession data for the Republic of the Congo provide the boundaries of areas permitted for selective logging. These areas, also called Forest Exploitation Units, are managed in accordance with the national Forest Code. This data set was produced through a collaboration between the Republic of the Congo Ministry of Forest Economy and WRI. For more information, see the Interactive Forest Atlas for the Republic of the Congo.

Credit:Republic of the Congo Ministry of Forest Economy (MEF), National Center for Inventory and Planning of Forest and Wildlife Resources (CNIAF), World Resources Institute.

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Mining
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Function

Displays boundaries of areas allocated by governments to companies for extraction of minerals

RESOLUTION / SCALE

Varies by country

Geographic coverage

Currently available for Cameroon, Canada, Colombia, Republic of the Congo, Democratic Republic of the Congo (DRC), and Gabon

Source data

Generally based on a combination of government documents, satellite imagery, and GPS data. For information on country-specific concessions data please refer to the Data page.

Frequency of updates

Variable, depending on government agencies in each country and other data providers

Date of content

Varies by country

Cautions

This layer is a compilation of concession data from various countries and sources. The quality of these data can vary depending on the source. This layer may not include all existing concessions in a country, and the location of certain concessions can be inaccurate.

Overview

“Mining concession” refers to an area allocated by a government or other body for the extraction of minerals. The terminology for these areas varies from country to country. “Concession” is used as a general term for licenses, permits, or other contracts that confer rights to private companies to manage and extract minerals from public lands; terminology varies at the national level, however, and includes mineral or mining "permits," "tenures," "licenses," and other terms.

This data set displays mining concessions as a single layer assembled by aggregating concession data for multiple countries. The data may come from government agencies, NGOs, or other organizations and varies by date and data sources. For more information on concession data for each country please visit the Open Data Portal.

If you are aware of concession data for additional countries, please email us here.

Suggested citation for data as displayed on GFW: “Mining.” World Resources Institute. Accessed through Global Forest Watch on [date]. incendios.fan-bo.org.

Learn more or download data
GFW currently includes mining concession data for the following countries:
Select a country
Cameroon mining permits

Colombia mining titles

Democratic Republic of the Congo mining permits

Gabon mining permits

Republic of the Congo mining permits
Download

This data set provides the boundaries of prospective mining permits for Cameroon, as well as the type of mineral resource. Map data were provided by the Cameroon Ministry of Mines and Technological Development and published in a collaboration with the World Resources Institute. For more information and data sets, see the Interactive Forest Atlas for Cameroon.

Credit: Cameroon Ministry of Mines and Technological Development.

Download

This data set provides the boundaries of mining titles (títulos mineros concedidos) for Colombia. The shapefiles are compiled by Tierra Minada, a Colombian civil society group, utilizing information from the Colombian Mining Registry, which is maintained by the National Mining Agency. For more information about the data sets, visit the Tierra Minada website or Colombia’s Mining Cadaster Portal.

Credit: Tierra Minada; Agencia Nacional de Minería de Colombia.

This data set provides the boundaries for mining permits in the Democratic Republic of the Congo. This data set is available from the Ministry of Mines Mining Registry (CAMI), for purchase and could not be made available for public download. For more information, see the DRC's mining cadaster portal.

Credit: Democratic Republic of the Congo Ministry of Mines Mining Registry (CAMI)

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This data set provides the boundaries for mining permits and prospecting permits for Gabon. The data set was produced by the Gabon Ministry of Mines, Petroleum, and Hydrocarbons and the World Resources Institute for the Interactive Mining, Forest, and Conservation Atlas of Gabon. For more information, see the Interactive Forest Atlas of Gabon.

Credit: Gabon Ministry of Mines, Petroleum, and Hydrocarbons; World Resources Institute.

Download

This data set provides the boundaries of mining permits for the Republic of the Congo. The original map data were produced by the Republic of the Congo Ministry of Mines and Geology with the support of the World Resources Institute. For more information, see the Interactive Forest Atlas for the Republic of the Congo.

Credit: Republic of the Congo Ministry of Mines and Geology, World Resources Institute.
Canada mining permits

Overview

This data set provides the boundaries for the following industrial concessions across Canada: active mineral prospecting permits across the Northwest Territories and Nunavut as of July 2012; Active mineral leases as of February 2013; Active mineral claims as of February 2013.Active coal tenures as of February 2013. Data was obtained from provincial and federal government websites and may be subject to use limitations listed with those sources. This data compilation was completed by Global Forest Watch Canada.

Credit:Global Forest Watch Canada.

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Cameroon mining permits

Overview

This data set provides the boundaries of prospective mining permits for Cameroon, as well as the type of mineral resource. Map data were provided by the Cameroon Ministry of Mines and Technological Development and published in a collaboration with the World Resources Institute. For more information and data sets, see the Interactive Forest Atlas for Cameroon.

Credit:Cameroon Ministry of Mines and Technological Development.

Learn more and download data
Colombia mining titles

Overview

This data set provides the boundaries of mining titles (títulos mineros concedidos) for Colombia. The shapefiles are compiled by Tierra Minada, a Colombian civil society group, utilizing information from the Colombian Mining Registry, which is maintained by the National Mining Agency. For more information about the data sets, visit the Tierra Minada website or Colombia’s Mining Cadaster Portal.

Credit:Tierra Minada; Agencia Nacional de Minería de Colombia.

Learn more and download data
Democratic Republic of the Congo mining permits

Overview

This data set provides the boundaries for mining permits in the Democratic Republic of the Congo. This data set is available from the Ministry of Mines Mining Registry (CAMI), for purchase and could not be made available for public download. For more information, see the DRC's mining cadaster portal.

Credit:Democratic Republic of the Congo Ministry of Mines Mining Registry (CAMI)

This data set is not available for download
Gabon mining permits

Overview

This data set provides the boundaries for mining permits and prospecting permits for Gabon. The data set was produced by the Gabon Ministry of Mines, Petroleum, and Hydrocarbons and the World Resources Institute for the Interactive Mining, Forest, and Conservation Atlas of Gabon. For more information, see the Interactive Forest Atlas of Gabon.

Credit:Democratic Republic of the Congo Ministry of Mines Mining Registry (CAMI)

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Republic of the Congo mining permits

Overview

This data set provides the boundaries of mining permits for the Republic of the Congo. The original map data were produced by the Republic of the Congo Ministry of Mines and Geology with the support of the World Resources Institute. For more information, see the Interactive Forest Atlas for the Republic of the Congo.

Credit:Republic of the Congo Ministry of Mines and Geology, World Resources Institute.

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Cambodia Mining Licenses

Overview

This data set displays the boundaries and locations of mining licenses in Cambodia. Data were compiled from MIME, company websites, and other contract data. This data set is a combination of the primary, secondary and partial data sets provided by Open Development Cambodia. To learn more, please visit OpenDevCam.net.

Credit:Open Development Cambodia, 2014.

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Plantations
Download

Function

Displays boundaries of areas allocated by governments to companies for tree plantations

RESOLUTION / SCALE

Varies by country

Geographic coverage

Currently available for Cameroon, Gabon, Indonesia, Liberia, and Republic of the Congo

Source data

Generally based on a combination of government documents, satellite imagery, and GPS data. For information on country-specific concessions data please refer to the Data page.

Frequency of updates

Variable, depending on government agencies in each country and other data providers

Date of content

Varies by country

Cautions

This layer is a compilation of concession data from various countries and sources. The quality of these data can vary depending on the source. This layer may not include all existing concessions in a country, and the location of certain concessions can be inaccurate.

Overview

“Plantation” refers to an area allocated by a government or other body for the establishment of fast growing tree plantations for the production of oil palm, timber, or other wood products, including pulp and paper.

This data set displays plantation concessions as a single layer assembled by aggregating data for multiple countries. The data may come from government agencies, NGOs, or other organizations and varies by date and data sources. For more information on concession data for each country please visit the Open Data Portal.

If you are aware of plantation concession data for additional countries, please email us here.

Suggested citation for data as displayed on GFW: “Plantations.” World Resources Institute. Accessed through Global Forest Watch on [date]. incendios.fan-bo.org.

Learn more or download data
GFW currently includes oil palm concession data for the following countries:
Select a country
Cameroon agro-industrial zones

Indonesia oil palm concessions

Liberia oil palm concessions

Republic of the Congo oil palm concessions
Download

This data layer shows the boundaries of agro-industrial zones, where oil palm and rubber tree plantations, as well as other crops, may be established. In Cameroon, industrial agriculture falls outside of the National Forest Estate. Agricultural plantations are allocated by the Ministry of Economy and Planning to private entities under long-term, renewable contracts, which are then monitored by the Ministry of Agriculture. The agro-industrial data set was mapped using satellite imagery, with ground-truthing to determine the crop type and operating company. Official documentation was often lacking, so boundaries should be considered approximate and nonexhaustive.

Credit: World Resources Institute.

Download

This data set, produced by the Indonesia Ministry of Forestry, provides the boundaries of current or planned oil palm plantations in Indonesia. This data set is known to be incomplete, but it is currently the best available.

Credit: Indonesia Ministry of Forestry.

Download

This data set provides the boundaries of known oil palm plantations for Liberia and was compiled by Global Witness from available government maps. Information provided with this data set includes company, ownership group, and land area.

Credit: Global Witness, 2013.

Download

This data set provides the boundaries for oil palm plantations according to the Republic of the Congo Ministry of Agriculture.

Credit: World Resources Institute; Republic of the Congo Ministry of Agriculture.
Oil palm
Download

Function

Displays boundaries of areas allocated by governments to companies for oil palm plantations

RESOLUTION / SCALE

Varies by country

Geographic coverage

Currently available for Cameroon, Republic of the Congo, Indonesia, and Liberia

Source data

Generally based on a combination of government documents, satellite imagery, and GPS data. For information on country-specific concessions data please refer to the Data page.

Frequency of updates

Variable, depending on government agencies in each country and other data providers

Date of content

Varies by country

Cautions

This layer is a compilation of concession data from various countries and sources. The quality of these data can vary depending on the source. This layer may not include all existing concessions in a country, and the location of certain concessions can be inaccurate.

Overview

“Oil palm concession” refers to an area allocated by a government or other body for industrial-scale oil palm plantations.

This data set displays oil palm concessions as a single layer assembled by aggregating concession data for multiple countries. The data may come from government agencies, NGOs, or other organizations and varies by date and data sources. For more information on concession data for each country please visit the Open Data Portal.

If you are aware of concession data for additional countries, please email us here.

Suggested citation for data as displayed on GFW: “Oil Palm.” World Resources Institute. Accessed through Global Forest Watch on [date]. incendios.fan-bo.org.

Learn more or download data
GFW currently includes oil palm concession data for the following countries:
Select a country
Cameroon agro-industrial zones

Indonesia oil palm concessions

Liberia oil palm concessions

Republic of the Congo oil palm concessions
Download

This data layer shows the boundaries of agro-industrial zones, where oil palm and rubber tree plantations, as well as other crops, may be established. In Cameroon, industrial agriculture falls outside of the National Forest Estate. Agricultural plantations are allocated by the Ministry of Economy and Planning to private entities under long-term, renewable contracts, which are then monitored by the Ministry of Agriculture. The agro-industrial data set was mapped using satellite imagery, with ground-truthing to determine the crop type and operating company. Official documentation was often lacking, so boundaries should be considered approximate and nonexhaustive.

Credit: World Resources Institute.

Download

This data set, produced by the Indonesia Ministry of Forestry, provides the boundaries of current or planned oil palm plantations in Indonesia. This data set is known to be incomplete, but it is currently the best available.

Credit: Indonesia Ministry of Forestry.

Download

This data set provides the boundaries of known oil palm plantations for Liberia and was compiled by Global Witness from available government maps. Information provided with this data set includes company, ownership group, and land area.

Credit: Global Witness, 2013.

Download

This data set provides the boundaries for oil palm plantations according to the Republic of the Congo Ministry of Agriculture.

Credit: World Resources Institute; Republic of the Congo Ministry of Agriculture.
Republic of the Congo oil palm concessions

Overview

This data set provides the boundaries for oil palm plantations according to the Republic of the Congo Ministry of Agriculture.

Credit:World Resources Institute; Republic of the Congo Ministry of Agriculture.

Learn more and download data
Indonesia oil palm concessions

Overview

This data set, produced by the Indonesia Ministry of Forestry, provides the boundaries of current or planned oil palm plantations in Indonesia. This data set is known to be incomplete, but it is currently the best available.

Credit:Indonesia Ministry of Forestry.

Learn more and download data
Cameroon agro-industrial zones

Overview

This data layer shows the boundaries of agro-industrial zones, where oil palm and rubber tree plantations, as well as other crops, may be established. In Cameroon, industrial agriculture falls outside of the National Forest Estate. Agricultural plantations are allocated by the Ministry of Economy and Planning to private entities under long-term, renewable contracts, which are then monitored by the Ministry of Agriculture. The agro-industrial data set was mapped using satellite imagery, with ground-truthing to determine the crop type and operating company. Official documentation was often lacking, so boundaries should be considered approximate and nonexhaustive.

Credit:World Resources Institute.

Learn more and download data
Liberia oil palm concessions

Overview

This data set provides the boundaries of known oil palm plantations for Liberia and was compiled by Global Witness from available government maps. Information provided with this data set includes company, ownership group, and land area.

Credit:Global Witness, 2013.

Learn more and download data
Wood Fiber Plantations
Download

Function

Displays boundaries of areas allocated by governments to private companies for tree plantations for production of timber and wood pulp for paper and paper products

RESOLUTION / SCALE

Varies by country

Geographic coverage

Currently available for Republic of the Congo, Gabon, and Indonesia

Source data

Generally based on a combination of government documents, satellite imagery, and GPS data. For information on country-specific concessions data please refer to the Data page.

Frequency of updates

Variable, depending on government agencies in each country and other data providers

Date of content

Varies by country

Cautions

This layer is a compilation of concession data from various countries and sources. The quality of these data can vary depending on the source. This layer may not include all existing concessions in a country, and the location of certain concessions can be inaccurate.

Overview

“Wood fiber concession” refers to an area allocated by a government or other body for establishment of fast-growing tree plantations for the production of timber and wood pulp for paper and paper products.

This data set displays wood fiber concessions as a single layer assembled by aggregating concession data for multiple countries. The data may come from government agencies, NGOs, or other organizations and varies by date and data sources. For more information on concession data for each country please visit the Open Data Portal.

If you are aware of concession data for additional countries, please email us here.

Suggested citation for data as displayed on GFW: “Wood Fiber.” World Resources Institute. Accessed through Global Forest Watch on [date]. incendios.fan-bo.org.

Learn more or download data
GFW currently hosts wood fiber concession data for the following countries:
Select a country
Indonesia wood fiber plantations

Republic of the Congo eucalyptus plantations
Download

This data set, produced by the Indonesia Ministry of Forestry, provides the boundaries of current or planned wood fiber plantations in Indonesia. This data set is known to be incomplete, but it is compiled from the best information currently available.

Credit: Indonesia Ministry of Forestry.

Download

This data set provides the boundaries for eucalyptus and other plantations in the Republic of the Congo. The World Resources Institute compiled information from the Republic of the Congo Ministry of Agriculture to produce this data layer.

Credit: World Resources Institute; Republic of the Congo Ministry of Agriculture.
Gabon wood fiber plantations

Learn more and download data
Republic of the Congo eucalyptus plantations

Overview

This data set provides the boundaries for eucalyptus and other plantations in the Republic of the Congo. The World Resources Institute compiled information from the Republic of the Congo Ministry of Agriculture to produce this data layer.

Credit:World Resources Institute; Republic of the Congo Ministry of Agriculture.

Learn more and download data
Indonesia wood fiber plantations

Overview

This data set, produced by the Indonesia Ministry of Forestry, provides the boundaries of current or planned wood fiber plantations in Indonesia. This data set is known to be incomplete, but it is compiled from the best information currently available.

Credit:Indonesia Ministry of Forestry.

Learn more and download data
Indonesia Leuser Ecosystem

Function

Displays the boundary of the Leuser Ecosystem, a National Strategic Area for its Environmental Protection Function.

RESOLUTION / SCALE

N/A

Geographic coverage

Leuser Ecosystem.

Source data

Digitization of JPEG of Ratification of Leuser Ecosystem boundary map, Ministry of Forestry decree 190/Kpts-II/2001 and 10193/Kpts-II/2002 (SK Menteri Kehutanan).

Frequency of updates

N/A

Date of content

November 19, 2013

Cautions

This data is not official data from the Indonesian Ministry of Environmental and Forestry. As a result, this data may differ from official data and there may be inaccuracies.

Overview

The Leuser Ecosystem spans the provinces of Aceh and North Sumatra on the island of Sumatra in Indonesia. Over 35 times the size of Singapore, this majestic and ancient ecosystem covers more than 2.6 million hectares of lowland rainforests, peat swamps, montane and coastal forests and alpine meadows. Globally recognized as one of the richest expanses of tropical rainforest found anywhere in Southeast Asia, the Leuser Ecosystem is also one of Asia’s largest carbon sinks. The Leuser Ecosystem is the last place on earth where orangutans, rhinos, elephants, and tigers co-exist in the wild. All four of these species are now classified by the International Union for Conservation of Nature (IUCN) as Critically Endangered. The Leuser Ecosystem is the only remaining habitat left in Sumatra large enough to sustain viable populations of these species. A publication in leading international journal Science listed the Leuser Ecosystem as “one of the world’s foremost irreplaceable areas.”

The Leuser Ecosystem is an essential asset for the economic development of Aceh, providing a total economic value of at least 350 million US dollars per year. The Leuser Ecosystem acts as a life-support system for approximately four million people in Aceh. The primary ecosystem services are fresh water provision and disaster mitigation. The forests of the Leuser Ecosystem act as a sponge, soaking up the downpours of the rainy season and spreading out the release of water downstream more evenly across the months. Deforestation of this environmentally sensitive area is having a dramatic impact by increasing the damage caused by flooding and landslides, and causing economic damage to communities and downstream industry. Locally and globally, the Leuser Ecosystem also has immense environmental value due to its role in climate regulation and carbon storage. Efforts to conserve the Leuser Ecosystem date as far back as the early 19th century, when the traditional leaders of Aceh lobbied the colonial government to protect their natural heritage, ranging from the mountains all the way down to the coast. More recent laws have served to strengthen the protection of the Leuser Ecosystem and placed the responsibility for managing its protection and restoration with the Aceh Provincial Government (Article 150 of National Law on Governing Aceh No. 11/2006). Furthermore, the Leuser Ecosystem in Aceh has special legal status as a National Strategic Area for its Environmental Protection Function (26 of 2007 juncto 26/2008), prohibiting any activities that reduce that function, including cultivation and infrastructure development.

Citation: Hutan Alam dan Lingkungan Aceh (HAkA). 2013.

Learn more and download data
Peru forest concessions/Concesiones forestales del Perú
Function
UTILIDAD

Displays boundaries of areas allocated by the forest authority and supervised by the Supervisory Body for Forest and Wildlife Resources (OSINFOR) for timber, non-timber products, conservation, ecotourism, wildlife, afforestation, and reforestation.
Muestra las concesiones forestales otorgadas por la autoridad forestal y supervisadas por el Organismo de Supervisión de los Recursos Forestales y de Fauna Silvestre (OSINFOR) para productos maderables, productos forestales no maderables, conservación, ecoturismo, fauna silvestre, forestación, y reforestación.

RESOLUTION / SCALE
RESOLUCIÓN / ESCALA

N/A

Geographic coverage
COBERTURA GEOGRÁFICA

Peru
Péru

Source data
FUENTE DE LA INFORMACIÓN

Compilation of field (GPS) and desktop data from Forest Management Plans and/or operational plans undertaken by the Supervisory Body for Forest and Wildlife Resources (OSINFOR)
Recopilación en campo (SPG) y de gabinete a partir de Planes de Manejo Forestal y/o planes operativos por parte del Organismo de Supervisión de los Recursos Forestales y de Fauna Silvestre (OSINFOR)

Frequency of updates
FRECUENCIA DE ACTUALIZACIÓN

Monthly
Mensual

Date of content
FECHA DE LOS CONTENIDOS

Varies by concession
Varía por concesión

Cautions
ADVERTENCIAS

Coverage includes information on the concessions granted by the forest authority and may be updated by transfer, resizing, and compensation of areas, among others
La cobertura contiene información de las concesiones otorgadas por la autoridad forestal y puede ser actualizada por transferencia, redimensionamiento, y compensación de áreas, entre otros.
Overview

Displays boundaries of areas allocated by the forest authority and supervised by the Supervisory Body for Forest and Wildlife Resources (OSINFOR) for timber, non-timber products, conservation, ecotourism, wildlife, afforestation, and reforestation. The concession grants the licensee the exclusive right to the sustainable use of natural resources granted under the conditions and limitations established by the respective title. The concession grants the holder the right to use and enjoy the natural resource granted and, consequently, ownership of the fruits and products extracted.

Types of concessions are indicated in the attribute data of each boundary, and include:
- Timber Concessions - Areas granted for timber operations in production forests permanently established in primary or secondary forests. Granted in two categories: between 5,000-10,000 hectares or areas greater than 10,000 hectares, both renewable for up to forty years.
- Non-Timber Forest Products - Areas granted for harvesting of non-timber products, such as fruits, buds, latex, resins, gums, flowers, fibers, whose extraction does not lead to the removal of forest cover. Maximum area of 10,000 hectares, renewable up to forty years.
- Conservation Concessions - Concessions aimed at directly contributing to conservation of plant and wildlife through protection and compatible uses such as research, education, and ecological restoration. Logging for timber is not allowed.
- Ecotourism Concessions - Concession for the development of activities related to recreation and ecotourism, contributing to the conservation of nature, animals and cultural values of this site, and allowing for beneficial social and economic participation of the local communities. Commercial logging is not permitted. Areas valid for forty years for a maximum area of 10,000 hectares.
- Wildlife Concessions - Public lands granted for wildlife management and aimed at sustainable enjoyment of authorized species. Renewable for up to twenty-five years.
- Reforestation/Afforestation areas - Areas designated for reforestation and afforestation activities.
Supervision status is also indicated in the attribute data of each boundary, and includes:
- Supervised - Forest concessions where OSINFOR, through field and desktop research, has verified the fulfillment of conditions and obligations in concession contracts and/or operational plans.
- Unsupervised - Forest concessions that are pending supervision.
For more information on each of the concession types, please visit the OSINFOR website

Citation: Supervisory Body for Forest and Wildlife Resources (OSINFOR). Peru forest concessions. 2015.

Suggested citation for data as displayed on GFW: “Peru Forest Concessions.” Supervisory Body for Forest and Wildlife Resources (OSINFOR). Accessed through Global Forest Watch on [date]. incendios.fan-bo.org.

Learn more at www.osinfor.gob.pe or visualize the original data at sisfor.osinfor.gob.pe
RESUMEN

Muestra las concesiones forestales otorgadas por la autoridad forestal y supervisadas por el Organismo de Supervisión de los Recursos Forestales y de Fauna Silvestre (OSINFOR) para productos maderables, productos forestales no maderables, conservación, ecoturismo, fauna silvestre, forestación, y reforestación. La concesión otorga al concesionario el derecho exclusivo de aprovechamiento sostenible del recurso natural concedido, de acuerdo con las condiciones y limitaciones establecidas en el título de concesión. La concesión otorga a su titular el derecho de uso y explotación del recurso natural concedido y, en consecuencia, la propiedad de los frutos y productos a extraerse.

El tipo de concesión se indica en los datos de atributos de cada polígono, e incluye:
- Concesiones Forestales con fines Maderables - Áreas otorgadas para la extracción maderera en bosques de producción permanente establecidos en bosques primarios o secundarios. Los títulos otorgados en dos categorías van de 5,000 hasta 10,000 hectáreas, o áreas de más de 10,000 hectáreas hasta 40,000 hectáreas; para ambas categorías el plazo es de hasta cuarenta años y puede renovarse.
- Concesiones para Productos Forestales no Maderables - ASon concesiones cuyo objetivo es contribuir de manera directa a la conservación de especies de flora y fauna silvestre a través de la protección efectiva y usos compatibles como la investigación, educación, y la restauración ecológica. No se permite el aprovechamiento forestal maderable.
- Concesiones de Conservación - Son concesiones para el desarrollo de actividades vinculadas a la recreación y el turismo de naturaleza ecológicamente responsables, contribuyendo de este modo a la conservación de la naturaleza, la fauna silvestre, y los valores culturales del sitio, y dando cabida a una participación socioeconómica activa y beneficiosa para las poblaciones locales. No se permite el aprovechamiento forestal maderable con fines comerciales. Estas concesiones tienen vigencia hasta de cuarenta años y pueden ser renovadas, y pueden abarcar una superficie máxima de diez mil hectáreas.
- Concesiones para Ecoturismo - Tierras de dominio público otorgadas al manejo de fauna silvestre y destinadas al aprovechamiento sostenible de poblaciones de especies autorizadas. Estas concesiones pueden ser por periodos de hasta veinticinco años y pueden ser renovadas.
- Concesiones de Fauna Silvestre - Public lands granted for wildlife management and aimed at sustainable enjoyment of authorized species. Renewable for up to twenty-five years.
- Concesiones con Fines de Forestación y/o Reforestación - Áreas destinadas a actividades de forestación y reforestación.
El estado de supervisión también se indica en los datos de atributos de cada polígono, e incluye:
- Supervised - Concesiones forestales donde el OSINFOR, a través de trabajo de campo y gabinete, se ha verificado el cumplimiento de las condiciones y obligaciones en los contratos de concesión y/o planes operativos.
- Unsupervised - Concesiones forestales que están pendientes de supervisión.
Para más información sobre cada tipo de concesión, por favor visite el sitio de OSINFOR.

Citation: Organismo de Supervisión de los Recursos Forestales y de Fauna Silvestre (OSINFOR). Concesiones forestales del Perú. 2015.

Cita sugerida para los datos desplegados en GFW:“Concesiones forestales del Perú.” Organismo de Supervisión de los Recursos Forestales y de Fauna Silvestre (OSINFOR). Accedido a través de Global Forest Watch el [fecha]. incendios.fan-bo.org.

Aprenda más en www.osinfor.gob.pe o visualice los datos originales en sisfor.osinfor.gob.pe
Peru forest concessions
Function
UTILIDAD

Displays boundaries of areas allocated by the forest authority and supervised by the Supervisory Body for Forest and Wildlife Resources (OSINFOR) for timber, non-timber products, conservation, ecotourism, wildlife, afforestation, and reforestation.
Muestra las concesiones forestales otorgadas por la autoridad forestal y supervisadas por el Organismo de Supervisión de los Recursos Forestales y de Fauna Silvestre (OSINFOR) para productos maderables, productos forestales no maderables, conservación, ecoturismo, fauna silvestre, forestación, y reforestación.

RESOLUTION / SCALE
RESOLUCIÓN / ESCALA

N/A

Geographic coverage
COBERTURA GEOGRÁFICA

Peru
Péru

Source data
FUENTE DE LA INFORMACIÓN

Compilation of field (GPS) and desktop data from Forest Management Plans and/or operational plans undertaken by the Supervisory Body for Forest and Wildlife Resources (OSINFOR)
Recopilación en campo (SPG) y de gabinete a partir de Planes de Manejo Forestal y/o planes operativos por parte del Organismo de Supervisión de los Recursos Forestales y de Fauna Silvestre (OSINFOR)

Frequency of updates
FRECUENCIA DE ACTUALIZACIÓN

Monthly
Mensual

Date of content
FECHA DE LOS CONTENIDOS

Varies by concession
Varía por concesión

Cautions
ADVERTENCIAS

Coverage includes information on the concessions granted by the forest authority and may be updated by transfer, resizing, and compensation of areas, among others
La cobertura contiene información de las concesiones otorgadas por la autoridad forestal y puede ser actualizada por transferencia, redimensionamiento, y compensación de áreas, entre otros.
Overview

Displays boundaries of areas allocated by the forest authority and supervised by the Supervisory Body for Forest and Wildlife Resources (OSINFOR) for timber, non-timber products, conservation, ecotourism, wildlife, afforestation, and reforestation. The concession grants the licensee the exclusive right to the sustainable use of natural resources granted under the conditions and limitations established by the respective title. The concession grants the holder the right to use and enjoy the natural resource granted and, consequently, ownership of the fruits and products extracted.

Types of concessions are indicated in the attribute data of each boundary, and include:
- Timber Concessions - Areas granted for timber operations in production forests permanently established in primary or secondary forests. Granted in two categories: between 5,000-10,000 hectares or areas greater than 10,000 hectares, both renewable for up to forty years.
- Non-Timber Forest Products - Areas granted for harvesting of non-timber products, such as fruits, buds, latex, resins, gums, flowers, fibers, whose extraction does not lead to the removal of forest cover. Maximum area of 10,000 hectares, renewable up to forty years.
- Conservation Concessions - Concessions aimed at directly contributing to conservation of plant and wildlife through protection and compatible uses such as research, education, and ecological restoration. Logging for timber is not allowed.
- Ecotourism Concessions - Concession for the development of activities related to recreation and ecotourism, contributing to the conservation of nature, animals and cultural values of this site, and allowing for beneficial social and economic participation of the local communities. Commercial logging is not permitted. Areas valid for forty years for a maximum area of 10,000 hectares.
- Wildlife Concessions - Public lands granted for wildlife management and aimed at sustainable enjoyment of authorized species. Renewable for up to twenty-five years.
- Reforestation/Afforestation areas - Areas designated for reforestation and afforestation activities.
Supervision status is also indicated in the attribute data of each boundary, and includes:
- Supervised - Forest concessions where OSINFOR, through field and desktop research, has verified the fulfillment of conditions and obligations in concession contracts and/or operational plans.
- Unsupervised - Forest concessions that are pending supervision.
Citation: For more information on each of the concession types, please visit the OSINFOR website.

Suggested citation for data as displayed on GFW: “Peru Forest Concessions.” Supervisory Body for Forest and Wildlife Resources (OSINFOR). Accessed through Global Forest Watch on [date]. incendios.fan-bo.org.

Learn more at www.osinfor.gob.pe or visualize the original data at sisfor.osinfor.gob.pe
RESUMEN

Muestra las concesiones forestales otorgadas por la autoridad forestal y supervisadas por el Organismo de Supervisión de los Recursos Forestales y de Fauna Silvestre (OSINFOR) para productos maderables, productos forestales no maderables, conservación, ecoturismo, fauna silvestre, forestación, y reforestación. La concesión otorga al concesionario el derecho exclusivo de aprovechamiento sostenible del recurso natural concedido, de acuerdo con las condiciones y limitaciones establecidas en el título de concesión. La concesión otorga a su titular el derecho de uso y explotación del recurso natural concedido y, en consecuencia, la propiedad de los frutos y productos a extraerse.

El tipo de concesión se indica en los datos de atributos de cada polígono, e incluye:
- Concesiones Forestales con fines Maderables - Áreas otorgadas para la extracción maderera en bosques de producción permanente establecidos en bosques primarios o secundarios. Los títulos otorgados en dos categorías van de 5,000 hasta 10,000 hectáreas, o áreas de más de 10,000 hectáreas hasta 40,000 hectáreas; para ambas categorías el plazo es de hasta cuarenta años y puede renovarse.
- Concesiones para Productos Forestales no Maderables - ASon concesiones cuyo objetivo es contribuir de manera directa a la conservación de especies de flora y fauna silvestre a través de la protección efectiva y usos compatibles como la investigación, educación, y la restauración ecológica. No se permite el aprovechamiento forestal maderable.
- Concesiones de Conservación - Son concesiones para el desarrollo de actividades vinculadas a la recreación y el turismo de naturaleza ecológicamente responsables, contribuyendo de este modo a la conservación de la naturaleza, la fauna silvestre, y los valores culturales del sitio, y dando cabida a una participación socioeconómica activa y beneficiosa para las poblaciones locales. No se permite el aprovechamiento forestal maderable con fines comerciales. Estas concesiones tienen vigencia hasta de cuarenta años y pueden ser renovadas, y pueden abarcar una superficie máxima de diez mil hectáreas.
- Concesiones para Ecoturismo - Tierras de dominio público otorgadas al manejo de fauna silvestre y destinadas al aprovechamiento sostenible de poblaciones de especies autorizadas. Estas concesiones pueden ser por periodos de hasta veinticinco años y pueden ser renovadas.
- Concesiones de Fauna Silvestre - Public lands granted for wildlife management and aimed at sustainable enjoyment of authorized species. Renewable for up to twenty-five years.
- Concesiones con Fines de Forestación y/o Reforestación - Áreas destinadas a actividades de forestación y reforestación.
El estado de supervisión también se indica en los datos de atributos de cada polígono, e incluye:
- Supervised - Concesiones forestales donde el OSINFOR, a través de trabajo de campo y gabinete, se ha verificado el cumplimiento de las condiciones y obligaciones en los contratos de concesión y/o planes operativos.
- Unsupervised - Concesiones forestales que están pendientes de supervisión.
Citation: Para más información sobre cada tipo de concesión, por favor visite el sitio de OSINFOR.

Cita sugerida para los datos desplegados en GFW:“Concesiones forestales del Perú.” Organismo de Supervisión de los Recursos Forestales y de Fauna Silvestre (OSINFOR). Accedido a través de Global Forest Watch el [fecha]. incendios.fan-bo.org.

Aprenda más en www.osinfor.gob.pe o visualice los datos originales en sisfor.osinfor.gob.pe
Peru forest concessions
Function
UTILIDAD

Displays boundaries of areas allocated by the forest authority and supervised by the Supervisory Body for Forest and Wildlife Resources (OSINFOR) for timber, non-timber products, conservation, ecotourism, wildlife, afforestation, and reforestation.
Muestra las concesiones forestales otorgadas por la autoridad forestal y supervisadas por el Organismo de Supervisión de los Recursos Forestales y de Fauna Silvestre (OSINFOR) para productos maderables, productos forestales no maderables, conservación, ecoturismo, fauna silvestre, forestación, y reforestación.

RESOLUTION / SCALE
RESOLUCIÓN / ESCALA

N/A

Geographic coverage
COBERTURA GEOGRÁFICA

Peru
Péru

Source data
FUENTE DE LA INFORMACIÓN

Compilation of field (GPS) and desktop data from Forest Management Plans and/or operational plans undertaken by the Supervisory Body for Forest and Wildlife Resources (OSINFOR)
Recopilación en campo (SPG) y de gabinete a partir de Planes de Manejo Forestal y/o planes operativos por parte del Organismo de Supervisión de los Recursos Forestales y de Fauna Silvestre (OSINFOR)

Frequency of updates
FRECUENCIA DE ACTUALIZACIÓN

Monthly
Mensual

Date of content
FECHA DE LOS CONTENIDOS

Varies by concession
Varía por concesión

Cautions
ADVERTENCIAS

Coverage includes information on the concessions granted by the forest authority and may be updated by transfer, resizing, and compensation of areas, among others
La cobertura contiene información de las concesiones otorgadas por la autoridad forestal y puede ser actualizada por transferencia, redimensionamiento, y compensación de áreas, entre otros.
Overview

Displays boundaries of areas allocated by the forest authority and supervised by the Supervisory Body for Forest and Wildlife Resources (OSINFOR) for timber, non-timber products, conservation, ecotourism, wildlife, afforestation, and reforestation. The concession grants the licensee the exclusive right to the sustainable use of natural resources granted under the conditions and limitations established by the respective title. The concession grants the holder the right to use and enjoy the natural resource granted and, consequently, ownership of the fruits and products extracted.

Types of concessions are indicated in the attribute data of each boundary, and include:
- Timber Concessions - Areas granted for timber operations in production forests permanently established in primary or secondary forests. Granted in two categories: between 5,000-10,000 hectares or areas greater than 10,000 hectares, both renewable for up to forty years.
- Non-Timber Forest Products - Areas granted for harvesting of non-timber products, such as fruits, buds, latex, resins, gums, flowers, fibers, whose extraction does not lead to the removal of forest cover. Maximum area of 10,000 hectares, renewable up to forty years.
- Conservation Concessions - Concessions aimed at directly contributing to conservation of plant and wildlife through protection and compatible uses such as research, education, and ecological restoration. Logging for timber is not allowed.
- Ecotourism Concessions - Concession for the development of activities related to recreation and ecotourism, contributing to the conservation of nature, animals and cultural values of this site, and allowing for beneficial social and economic participation of the local communities. Commercial logging is not permitted. Areas valid for forty years for a maximum area of 10,000 hectares.
- Wildlife Concessions - Public lands granted for wildlife management and aimed at sustainable enjoyment of authorized species. Renewable for up to twenty-five years.
- Reforestation/Afforestation areas - Areas designated for reforestation and afforestation activities.
Supervision status is also indicated in the attribute data of each boundary, and includes:
- Supervised - Forest concessions where OSINFOR, through field and desktop research, has verified the fulfillment of conditions and obligations in concession contracts and/or operational plans.
- Unsupervised - Forest concessions that are pending supervision.
Citation: For more information on each of the concession types, please visit the OSINFOR website.

Suggested citation for data as displayed on GFW: “Peru Forest Concessions.” Supervisory Body for Forest and Wildlife Resources (OSINFOR). Accessed through Global Forest Watch on [date]. incendios.fan-bo.org.

Learn more at www.osinfor.gob.pe or visualize the original data at sisfor.osinfor.gob.pe
RESUMEN

Muestra las concesiones forestales otorgadas por la autoridad forestal y supervisadas por el Organismo de Supervisión de los Recursos Forestales y de Fauna Silvestre (OSINFOR) para productos maderables, productos forestales no maderables, conservación, ecoturismo, fauna silvestre, forestación, y reforestación. La concesión otorga al concesionario el derecho exclusivo de aprovechamiento sostenible del recurso natural concedido, de acuerdo con las condiciones y limitaciones establecidas en el título de concesión. La concesión otorga a su titular el derecho de uso y explotación del recurso natural concedido y, en consecuencia, la propiedad de los frutos y productos a extraerse.

El tipo de concesión se indica en los datos de atributos de cada polígono, e incluye:
- Concesiones Forestales con fines Maderables - Áreas otorgadas para la extracción maderera en bosques de producción permanente establecidos en bosques primarios o secundarios. Los títulos otorgados en dos categorías van de 5,000 hasta 10,000 hectáreas, o áreas de más de 10,000 hectáreas hasta 40,000 hectáreas; para ambas categorías el plazo es de hasta cuarenta años y puede renovarse.
- Concesiones para Productos Forestales no Maderables - ASon concesiones cuyo objetivo es contribuir de manera directa a la conservación de especies de flora y fauna silvestre a través de la protección efectiva y usos compatibles como la investigación, educación, y la restauración ecológica. No se permite el aprovechamiento forestal maderable.
- Concesiones de Conservación - Son concesiones para el desarrollo de actividades vinculadas a la recreación y el turismo de naturaleza ecológicamente responsables, contribuyendo de este modo a la conservación de la naturaleza, la fauna silvestre, y los valores culturales del sitio, y dando cabida a una participación socioeconómica activa y beneficiosa para las poblaciones locales. No se permite el aprovechamiento forestal maderable con fines comerciales. Estas concesiones tienen vigencia hasta de cuarenta años y pueden ser renovadas, y pueden abarcar una superficie máxima de diez mil hectáreas.
- Concesiones para Ecoturismo - Tierras de dominio público otorgadas al manejo de fauna silvestre y destinadas al aprovechamiento sostenible de poblaciones de especies autorizadas. Estas concesiones pueden ser por periodos de hasta veinticinco años y pueden ser renovadas.
- Concesiones de Fauna Silvestre - Public lands granted for wildlife management and aimed at sustainable enjoyment of authorized species. Renewable for up to twenty-five years.
- Concesiones con Fines de Forestación y/o Reforestación - Áreas destinadas a actividades de forestación y reforestación.
El estado de supervisión también se indica en los datos de atributos de cada polígono, e incluye:
- Supervised - Concesiones forestales donde el OSINFOR, a través de trabajo de campo y gabinete, se ha verificado el cumplimiento de las condiciones y obligaciones en los contratos de concesión y/o planes operativos.
- Unsupervised - Concesiones forestales que están pendientes de supervisión.
Citation: Para más información sobre cada tipo de concesión, por favor visite el sitio de OSINFOR.

Cita sugerida para los datos desplegados en GFW:“Concesiones forestales del Perú.” Organismo de Supervisión de los Recursos Forestales y de Fauna Silvestre (OSINFOR). Accedido a través de Global Forest Watch el [fecha]. incendios.fan-bo.org.

Aprenda más en www.osinfor.gob.pe o visualice los datos originales en sisfor.osinfor.gob.pe
Major dams
Function

Identifies dam locations for the world’s 50 major river basins.

RESOLUTION / SCALE

Varies by country

Geographic coverage

This data set is not global. The data is confined to the world’s 50 major river basins.

Source data

Dams data are compiled from various sources, including: the Global Reservoir and Dam (GRanD) Database, the Consultative Group on International Agricultural Research (CGIAR) Challenge Program on Water and Food - Mekong (for Mekong basin dams only), the United States National Inventory of Dams (NID), other government dam inventories, and original data collection by International Rivers.

Frequency of updates

As new data becomes available

Date of content

2014

Cautions

Data results are biased towards public available data, so gaps may exist.
Overview

The State of the World's Rivers is an interactive web database that illustrates data on ecological health in the world’s 50 major river basins. Indicators of ecosystem health are grouped into the categories of river fragmentation, biodiversity, and water quality. The database was created and published by International Rivers in 2014.

The Dam Hotspots data contains over 5,000 dam locations determined by latitude and longitude coordinates. These locations were confined to the world’s 50 major river basins. The data set comes from multiple sources, and was corrected for location errors by International Rivers. The “project status”—a moving target—was determined by acquiring official government data, as well as through primary research from Berkeley and five International Rivers’ regional offices.
- Operational: Already existing dams.
- Under construction: Dams which are currently being constructed.
- Planned: Dams whose studies or licensing have been completed, but construction has yet to begin.
- Inventoried: Dams whose potential site has been selected, but neither studies nor licensing have occurred.
- Suspended: Dams which have been temporarily or permanently suspended, deactivated, cancelled, or revoked.
- Unknown: No data are currently available.
Citation:International Rivers, The State of the World’s Rivers, August 2014 available at http://tryse.net/googleearth/irivers-dev3/.

Learn more or download data.

Conservation

Conservation data measure information that is important for preservation and enhancement of protected areas and natural resources such as biodiversity.

Protected Areas
Download and project website

Function

Displays areas that are legally protected according to various designations (e.g., national parks, state reserves, and wildlife reserves) and managed to achieve conservation objectives

Geographic coverage

Global

Source data

The World Database on Protected Areas, which compiles protected area data from governments, NGOs, and international secretariats

Frequency of updates

Monthly

Date of content

Varies by protected area

Cautions

Protected area designations, such as “National Park,” can be applied differently in different countries. Therefore, the associated IUCN category and its description of protection may also vary by country.

Protected areas with no boundary data are displayed as brown dotted boxes, which represent the reported protected area size. The box is centered around a single point location and the borders do not indicate the real boundary of the protected area.
Overview

The World Database on Protected Areas (WDPA) is the most comprehensive global spatial data set on marine and terrestrial protected areas available. Protected area data are provided via protectedplanet.net, the online interface for the World Database on Protected Areas (WDPA). The WDPA is a joint initiative of the IUCN and UNEP-WCMC to compile spatially referenced information about protected areas.

IUCN Management Categories

Not all protected areas receive the same degree of protection. While some have strict guidelines designed to preserve intact ecosystems, others allow for sustainable land use, often including limited resource extraction. In addition, not all countries use the same terminology when designating a protected area. Accordingly, the International Union for Conservation of Nature defined universal management categories that stipulate the level of protection for most protected areas.

As you click through protected areas in this layer, note the “legal designation” and the explanations below to better understand the degree to which an area is protected.
- Ia. Strict Nature Reserves. Protected areas designed to preserve biodiversity and all geological features. Limited human use (e.g., scientific study, education) is allowed and carefully monitored. Strict Nature Reserves are often used to understand the impact of indirect human disturbance (e.g., burning fossil fuels) because of the area’s high level of preservation. Other common designations: Biological Reserve, Botanical Reserve
- Ib. Wilderness Areas. Protected areas managed to preserve ecosystem processes with limited human use. Wilderness Areas cannot contain modern infrastructure (e.g., a visitor’s center), but they allow for local indigenous groups to maintain subsistence lifestyles. These areas are often established to restore disturbed environments. Other common designations: Wilderness Reserve, Wildlife Area
- II. National Parks. Protected areas designed to preserve large-scale ecosystems and support human visitation. With conservation as a priority, these areas allow infrastructure and contribute to the local economy by providing opportunities for environmental educational and recreation. Other common designations: State Park, Class A Park, Park Reserve, Provincial Park
- III. National Monuments or Features. Areas established to protect a specific natural feature (e.g., cave, grove) or human-made monument with significant historical, spiritual, or environmental importance and the immediate surroundings. Accordingly, Natural Monuments or Features are typically smaller in area and have high human impact resulting from visitor traffic. Other common designations: Natural Features Reserve, Nature Monument, Botanical Garden
- IV. Habitat and Species Management Areas. Areas designed to conserve specific wildlife populations and/or habitats. Habitat and Species Management Areas often exist within a larger ecosystem or protected area and are carefully managed (e.g., through hunting abatement or habitat restoration) to conserve a target species or habitat. Other common designations: National Wildlife Refuge, State Wildlife Management Area, Faunal Reserve, Zakaznik (Russia), Provincial Reserve, Wildlife Sanctuary
- V. Protected Landscapes and Seascapes. Protected areas with ecological, biological, or cultural importance that have been shaped by human use of the landscape. Protected landscapes and seascapes typically cover entire bodies of land or ocean and allow for a number of for-profit activities (e.g., ecotourism) in accordance with the region’s management plan. Other common designations: National Forest, State Natural Area, Environmental Protection Area, Protected Area, Quasi National Park (Japan), Nature Reserve, State Natural Area
- VI. Protected Areas with Sustainable Use of Natural Resources. Areas designed to manage natural resources and uphold the livelihoods of surrounding communities. These regions have a low level of human occupation, small-scale developments (i.e., not industrial), and part of the landscape in its natural condition. Other common designations: Wildlife Reserve, Biosphere Reserve, Forest Reserve, Protective Zone, National Forest, Natural and National Reserves, Reserve, Multiple Use Reserve, Municipal Reserve
Other Important Designations
- UNESCO-MAP Biosphere Reserves: areas under UNESCO’s Man and the Biosphere Programme designated to “promote sustainable development based on local community efforts and sound science.”
- World Heritage Sites: areas considered to have “outstanding universal value” and meet at least one of ten criteria, as described here.
- Ramsar Sites—Wetlands of International Importance: wetlands that hold significant value designated under the Ramsar Convention on Wetlands.
Citation: IUCN and UNEP-WCMC, The World Database on Protected Areas (WDPA) [On-line], accessed on [insert month/year], Cambridge, UK: UNEP-WCMC. Available at: www.protectedplanet.net.

Learn more or download data at www.protectedplanet.net
Protected Areas
Download and project website

Function

Displays areas that are legally protected according to various designations (e.g., national parks, state reserves, and wildlife reserves) and managed to achieve conservation objectives

Geographic coverage

Global

Source data

The World Database on Protected Areas, which compiles protected area data from governments, NGOs, and international secretariats

Frequency of updates

Monthly

Date of content

Varies by protected area

Cautions

Protected area designations, such as “National Park,” can be applied differently in different countries. Therefore, the associated IUCN category and its description of protection may also vary by country.

Protected areas with no boundary data are displayed as brown dotted boxes, which represent the reported protected area size. The box is centered around a single point location and the borders do not indicate the real boundary of the protected area.
Overview

The World Database on Protected Areas (WDPA) is the most comprehensive global spatial data set on marine and terrestrial protected areas available. Protected area data are provided via protectedplanet.net, the online interface for the World Database on Protected Areas (WDPA). The WDPA is a joint initiative of the IUCN and UNEP-WCMC to compile spatially referenced information about protected areas.

IUCN Management Categories

Not all protected areas receive the same degree of protection. While some have strict guidelines designed to preserve intact ecosystems, others allow for sustainable land use, often including limited resource extraction. In addition, not all countries use the same terminology when designating a protected area. Accordingly, the International Union for Conservation of Nature defined universal management categories that stipulate the level of protection for most protected areas.

As you click through protected areas in this layer, note the “legal designation” and the explanations below to better understand the degree to which an area is protected.
- Ia. Strict Nature Reserves. Protected areas designed to preserve biodiversity and all geological features. Limited human use (e.g., scientific study, education) is allowed and carefully monitored. Strict Nature Reserves are often used to understand the impact of indirect human disturbance (e.g., burning fossil fuels) because of the area’s high level of preservation. Other common designations: Biological Reserve, Botanical Reserve
- Ib. Wilderness Areas. Protected areas managed to preserve ecosystem processes with limited human use. Wilderness Areas cannot contain modern infrastructure (e.g., a visitor’s center), but they allow for local indigenous groups to maintain subsistence lifestyles. These areas are often established to restore disturbed environments. Other common designations: Wilderness Reserve, Wildlife Area
- II. National Parks. Protected areas designed to preserve large-scale ecosystems and support human visitation. With conservation as a priority, these areas allow infrastructure and contribute to the local economy by providing opportunities for environmental educational and recreation. Other common designations: State Park, Class A Park, Park Reserve, Provincial Park
- III. National Monuments or Features. Areas established to protect a specific natural feature (e.g., cave, grove) or human-made monument with significant historical, spiritual, or environmental importance and the immediate surroundings. Accordingly, Natural Monuments or Features are typically smaller in area and have high human impact resulting from visitor traffic. Other common designations: Natural Features Reserve, Nature Monument, Botanical Garden
- IV. Habitat and Species Management Areas. Areas designed to conserve specific wildlife populations and/or habitats. Habitat and Species Management Areas often exist within a larger ecosystem or protected area and are carefully managed (e.g., through hunting abatement or habitat restoration) to conserve a target species or habitat. Other common designations: National Wildlife Refuge, State Wildlife Management Area, Faunal Reserve, Zakaznik (Russia), Provincial Reserve, Wildlife Sanctuary
- V. Protected Landscapes and Seascapes. Protected areas with ecological, biological, or cultural importance that have been shaped by human use of the landscape. Protected landscapes and seascapes typically cover entire bodies of land or ocean and allow for a number of for-profit activities (e.g., ecotourism) in accordance with the region’s management plan. Other common designations: National Forest, State Natural Area, Environmental Protection Area, Protected Area, Quasi National Park (Japan), Nature Reserve, State Natural Area
- VI. Protected Areas with Sustainable Use of Natural Resources. Areas designed to manage natural resources and uphold the livelihoods of surrounding communities. These regions have a low level of human occupation, small-scale developments (i.e., not industrial), and part of the landscape in its natural condition. Other common designations: Wildlife Reserve, Biosphere Reserve, Forest Reserve, Protective Zone, National Forest, Natural and National Reserves, Reserve, Multiple Use Reserve, Municipal Reserve
Other Important Designations
- UNESCO-MAP Biosphere Reserves: areas under UNESCO’s Man and the Biosphere Programme designated to “promote sustainable development based on local community efforts and sound science.”
- World Heritage Sites: areas considered to have “outstanding universal value” and meet at least one of ten criteria, as described here.
- Ramsar Sites—Wetlands of International Importance: wetlands that hold significant value designated under the Ramsar Convention on Wetlands.
Citation: UNEP-WCMC, UNEP, and IUCN. “World Database on Protected Areas.” Accessed on [date]. www.protectedplanet.net.

Learn more or download data at www.protectedplanet.net
Biodiversity hotspots
Download at project website

Function

Displays Conservation International’s biodiversity hotspots—defined regions around the world where biodiversity conservation is most urgent because of high levels of endemism and human threat

Geographic coverage

Global (land only)

Frequency of updates

Updated as new data becomes available through Conservation International

Date of content

2011

Cautions

This layer only displays the land-based portion of biodiversity hotspots, although some hotspots extend offshore
Overview

First defined in 1988 by scientist Norman Myers, biodiversity hotspots are areas characterized by high levels of endemic plants coupled with significant habitat loss. Specifically, a region must meet the following criteria to achieve Conservation International’s hotspot classification:
- At least 1,500 species of vascular plants (>0.5% of the world’s total) are endemic
- At least 70% of the original natural vegetation has been lost
When Myers first defined the term, he identified 10 tropical forest hotspots. The need to pinpoint priority conservation regions led Conservation International (CI) to adopt the term and reassess the hotspot concept. In this process, CI introduced quantitative thresholds (see above) and added additional regions. At that time, there were 25 hotspots. Because of the constant change in environmental threats and the improved understanding of biodiversity, CI has since revisited the hotspots to refine boundaries, update information, and add new regions. This process produced an additional 10 hotspots, bringing the total to 35.

Citation: Conservation International. “Biodiversity Hotspots.” Accessed on [date]. www.conservation.org/where/priority_areas/hotspots/Pages/hotspots_main.aspx.

Learn more or download data at Conservation International
WWF Terrestrial Ecoregions of the World
Download at project website

Function

Displays large-scale areas containing a distinct assemblage of biological communities shaped by similar species, dynamics and environmental conditions

Geographic coverage

Global

Frequency of updates

-

Date of content

2004

Cautions

No single biogeographic framework is optimal for all taxa. Ecoregions reflect the best compromise for as many taxa as possible.
Ecoregion boundaries rarely form abrupt edges; rather, ecotones and mosaic habitats bound them.
Most ecoregions contain habitats that differ from their assigned biome (e.g., for example, rainforest ecoregions in Amazonia often contain small edaphic savannas).
Overview

Terrestrial Ecoregions of the World (TEOW) is a data set of the geographic distribution Earth's terrestrial biodiversity. Ecoregions are defined as relatively large units of land or water containing a distinct assemblage of natural communities sharing a large majority of species, environmental conditions, and processes, such as migrations or fire disturbance regimes. The 867 terrestrial ecoregions are classified into 14 different biomes, such as forests, grasslands, or deserts. Ecoregions represent the original distribution of distinct assemblages of species and communities.

The TEOW data set provides:
- A map of terrestrial biodiversity that gives enough detail to be useful in global and regional conservation priority-setting and planning efforts
- A logical biogeographic framework for developing large-scale conservation strategies
- A framework for a global species database useful in priority setting and ecological analyses
- A foundation for the Global 200, a representative prioritization of the world’s most distinctive biodiversity regions
The TEOW data set was developed by WWF through primary analysis, secondary research, and consultation of existing biogeographic maps and regional experts.

Citation: Olson, D. M., Dinerstein, E., Wikramanayake, E. D., Burgess, N. D., Powell, G. V. N., Underwood, E. C., D'Amico, J. A., Itoua, I., Strand, H. E., Morrison, J. C., Loucks, C. J., Allnutt, T. F., Ricketts, T. H., Kura, Y., Lamoreux, J. F., Wettengel, W. W., Hedao, P., Kassem, K. R. 2001. Terrestrial ecoregions of the world: a new map of life on Earth. Bioscience 51(11):933-938.
Brazil biomes

Function

Shows the boundaries of the six Brazilian continental biomes – Amazônia, Cerrado, Caatinga, Mata Atlântica, Pantanal, and Pampa

Resolution/Scale

1: 5,000,000

Geographic coverage

Continental Brazil

Source data

Ministerio do Meio Ambiente / IGBE

frequency of updates

Variable

Date of content

2004

Overview

This data set displays the boundaries of six Brazilian continental biomes: the Amazônia, Cerrado, Caatinga, Mata Atlântica, Pantanal and Pampa. “Biome” is defined as a collection of life (plant and animal) constituted by the grouping of contiguous vegetation types identifiable on a regional scale with similar geoclimatic conditions and shared history, which results in a unique biological diversity. The names used were the most common and popular in general associated with the predominant type of vegetation or relief, as in the case of Pantanal biome, which is the highest provincial flooded surface of the world.

The Amazon Biome is defined by the climatic region, forest physiognomy and geographic location. The Atlantic Forest biome, which occupies the entire Brazilian continental east Atlantic coast and stretches inland in the Southeast and South, is defined by the predominant forest vegetation and diverse relief. The Pampa, restricted to Rio Grande do Sul, is defined by a set of field vegetation in plain relief. The predominant vegetation in the Cerrado biome in Brazil, second in size, extends from the Maranhão coast to the Midwest and the Caatinga Biome, typical of semi-arid climate of the northeastern backlands. The map is a result of a partnership between the Brazilian Ministry of Environemnt (MMA) and the Brazilian Institute of Geography and Statistics (IBGE). To read more about the data set, please visit: http://www.ibge.gov.br/home/presidencia/noticias/21052004biomashtml.shtm.

Citation: MMA/IGBE

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Endemic Bird Areas

Download at project website

Function

Displays areas where the geographic range of two or more endemic bird species overlaps

Geographic coverage

Global

Source data

BirdLife International

Frequency of updates

Updated Annually

Date of content

2014

Overview

While many bird species are widespread, over 2,500 are endemic and restricted to an area smaller than 5 million hectares (restricted-range species). BirdLife International has mapped every restricted-range species using geo-referenced locality records. Through this process, they identified regions of the world—known as “Endemic Bird Areas” (EBAs)—where the distributions of two or more of these species overlap.

Half of all restricted-range species are globally threatened or near-threatened, and the other half remain vulnerable to loss or degradation of habitat. The majority of EBAs are also important for the conservation of restricted-range species from other animal and plant groups. The unique landscapes where these bird species occur, amounting to just 4.5% of the earth's land surface, are high priorities for broad-scale ecosystem conservation.

Geographically, EBAs are often islands or mountain ranges, and vary considerably in size, from a few hundred hectares to more than 10,000,000 hectares. EBAs also vary in the number of restricted-range species that they support (from two to 80). EBAs are found around the world, but most (77%) of them are located in the tropics and subtropics.

Citation:Stattersfield, A.J., Crosby, M.J., Long, A.J. and Wege, D.C. (1998) Endemic Bird Areas of the World. Priorities for biodiversity conservation. BirdLife Conservation Series 7. Cambridge: BirdLife International.

Learn more or request data at BirdLife International
Alliance for Zero Extinction sites
Learn more or request data at Alliance for Zero Extinction

Function

Displays critical sites for conservation that contain endangered species with limited ranges and populations found nowhere else on the planet

Geographic coverage

Global

Source data

The Alliance for Zero Extinction

Frequency of updates

Every 5 years

Date of content

2010; Updated March 16, 2012
Overview

Created by the Alliance for Zero Extinction (AZE), this data set shows 587 sites for 920 species of mammals, birds, amphibians, reptiles, conifers, and reef-building corals. The species found within these sites have extremely small global ranges and populations; any change to habitat within a site may lead to the extinction of a species in the wild. To meet AZE Extinction Site status, a site must:
- Contain at least one Endangered or Critically Endangered species
- Be the sole area where an Endangered or Critically Endangered species occurs
- Contain greater than 95% of either the known resident population of the species or 95% of the known population of one life history segment (e.g. breeding or wintering) of the species
- Have a definable boundary (e.g., species range, extent of contiguous habitat, etc.)
Launched in 2005, the Alliance for Zero Extinction (AZE) engages 83 non-governmental biodiversity conservation organizations working to prevent species extinctions. The AZE identifies and safeguards places where species evaluated to be Endangered or Critically Endangered by the International Union for Conservation of Nature are restricted to single remaining sites.

Citation:Alliance for Zero Extinction (2010). 2010 AZE Update. www.zeroextinction.org.

Learn more or request data at Alliance for Zero Extinction
Tiger Conservation Landscapes

Download at project website

Function

Displays contiguous areas of suitable tiger habitat that have shown consistent and confirmed evidence of tigers

Geographic coverage

Bangladesh, Bhutan, Cambodia, China, India, Indonesia, Lao PDR, Malaysia, Myanmar, Nepal, Russia, Thailand and Vietnam.

Source data

Dinerstein et al. 2007

Frequency of updates

Updated as new data becomes available through Biodiversity & Wildlife Solutions, RESOLVE

Date of content

2007

Cautions

Tiger Conservation Landscapes were created under the assumption that suitable habitat depends on quality and size of land cover and prey base.

Land cover data was problematic in certain geographies due to the presence of tree plantations. In some cases, forest cover was overestimated or underestimated.

The tiger location database, on which this data set was built, is incomplete for some regions, and the data comes from a variety of sources and research methods.

Overview

Tiger Conservation Landscapes (TCLs) are large blocks of contiguous or connected area of suitable tiger habitat that that can support at least five adult tigers and where tiger presence has been confirmed in the past 10 years. The data set was created by mapping tiger distribution, determined by land cover type, forest extent, and prey base, against a human influence index. Areas of high human influence that overlapped with suitable habitat were not considered tiger habitat.
Tigers require a large area to survive. Accordingly, habitat loss is a major cause of the species’ rapid decline. Before this data set, many countries containing tigers did not have spatially explicit tiger habitat maps necessary to develop habitat conservation and management plans. Among others, this information gap was an impetus to developing the TCL data set.

Credits: Dinerstein, E., Loucks, C.J., Wikramanayake, E., Ginsberg, J., Sanderson, E., Seidensticker, J., Forrest, J.L., Bryja, G., Heydlauff, A., Klenzendorf, S., Mills, J, O'Brien, T., Shrestha, M, Simons, R., Songer, M. 2007. “The fate of wild tigers.” BioScience 57 (June 2007): 508-14.

Tx2 Tiger Conservation Landscapes

Download at project website

Function

Displays areas that could double the wild tiger population through proper conservation and management by 2020

Geographic coverage

Bangladesh, Bhutan, Cambodia, China, India, Indonesia, Lao PDR, Malaysia, Myanmar, Nepal, Russia, Thailand and Vietnam.

Source data

Wikramanayake et al. 2011

Frequency of updates

Updated annually through Biodiversity & Wildlife Solutions, RESOLVE

Date of content

2011

Overview

This data set displays 29 Tx2 Tiger Conservation Landscapes (Tx2 TCLs), defined areas that could double the wild tiger population through proper conservation and management by 2020.

The number of wild tigers has declined from an estimated 100,000 in the early 1900s to a current estimate of around 3,500 adult animals. In response to this rapid decline, government officials convened in November 2010 to endorse the St. Petersburg Declaration, pledging to double the wild tiger population by 2020. To aid in this effort, Wikramanayake and his team conducted a landscape analysis of tiger habitat to determine if a recovery of such magnitude is possible. They identified 29 Tiger Conservation Landscapes with potential for doubling wild tiger population with proper conservation and management.

Credits: Wikramanayake, E., Dinerstein, E., Seidensticker, J., Lumpkin, S., Pandav, B., Shrestha, M., Mishra, H., Ballou, J., Johnsingh, A.J.T., Chestin, I., Sunarto, S., Thinley, P., Thapa, K., Jiang, G., Elagupillay, S., Kafley, H., Pradhan, N.M.B., Jigme, K., Teak, S., Cutter, P., Aziz, Md. A., Than, U. 2011. A landscape-based conservation strategy to double the wild tiger population. Conservation Letters, 4 (3):219-227.

Terai Arc Landscape Corridors

Function

Displays critical forest corridors connecting existing tiger populations in Nepal and India.

Geographic coverage

Nepal and India.

Source data

Terai Arc Landscape project

Frequency of updates

Updated annually through Biodiversity & Wildlife Solutions, RESOLVE

Date of content

2014

Cautions

The corridors are existing forests or grasslands which might also include human settlements.

Overview

This data set displays 9 forest corridors on the Nepalese side of the Terai Arc Landscape (TAL). Corridors are defined as existing forests connecting current Royal Bengal tiger meta-populations in Nepal and India.

The TAL is spread over 4.95 million hectares, linking 14 transboundary protected areas across Nepal and India. This landscape has the second largest population of rhinos, one of the highest densities of tiger populations, and is home to the Asiatic elephant. In Nepal, TAL encompasses 2.31 million hectares extending over 14 districts and includes 75 percent of the remaining forests of lowland Nepal. In addition, TAL was recognized as a WWF Global 200 ecoregion and spans three Ramsar sites and two World Heritage Sites.

Credits: Wikramanayake, E., M. McNight, E. Dinerstein, A. Joshi, B. Gurung, D. Smith. 2004. Designing a Conservation Landscape for Tigers in Human-Dominated Environments. Conservation Biology (18):839-844.

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Verified Carbon Standard project boundaries

Function

Displays the location of VCS projects categorized as Reduced Emissions from Deforestation and Forest Degradation (REDD), Improved Forest Management (IFM) and Afforestation, Reforestation and Revegetation (ARR), which are managed to protect or increase forest carbon stocks

Resoution/Scale

N/A

Geographic coverage

Global

Source data

The VCS Project Database at http://www.vcsprojectdatabase.org/

Frequency of updates

New VCS projects will be added as they become registered under the VCS

Date of content

Varies by project area and is specified in the records of each individual VCS project

Cautions

Some boundaries may be for the project group rather than for the individual project.

Overview

The Verified Carbon Standard (VCS) is the world’s widely used voluntary greenhouse gas (GHG) emission reduction program. VCS projects are developed across a wide range of sectoral scopes, including those classified within the Agriculture, Forestry and Other Land Use (AFOLU) sector. These projects reduce emissions from forest-related activities around the world and apply innovative GHG accounting methodologies to quantify such emission reductions, which are independently verified and transparently registered.

This layer shows VCS projects categorized as REDD (Reduced Emissions from Deforestation and Forest Degradation), IFM (Improved Forest Management) and ARR (Afforestation, Reforestation and Revegetation). More detail on the VCS program and these project categories can be found in the VCS Standard and VCS AFOLU Requirements documents.

In addition to these project activities, more than a dozen national and subnational jurisdictions around the world are applying the VCS Jurisdictional and Nested REDD+ framework to account for the emission reductions generated by their REDD+ policies and measures. This information will be added in the future as these programs register under the VCS.

Citation:The VCS Project Database. 2015. www.vcsprojectdatabase.org.

Learn more or request data at VCS Project Database
USA Conservation Easements

Function

Maps the boundaries of conservation easements on private lands and provides information on their status and management

RESOLUTION / SCALE

Variable

Geographic coverage

United States

Source data

Various – Government, Land Trusts, NGOs, other

Frequency of updates

As needed

Date of content

2014

Cautions

The NCED completeness maps measure the number of easements that are in the NCED database compared to the estimated total number of easements the NCED team is aware of from the Land Trust Alliance Census data and the NCED data collection efforts. Easements are known yet not in NCED because, 1) they have not been digitized, 2) they were withheld from NCED, or 3) the NCED team is still working with the easement holders to collect the information.

Approximately 70% of known land trusts are included in the Census; however, the Census gives us a good base number for comparison with NCED. There is no census for publicly-held easements so the total number of publicly-held easements is based on the data collection efforts of NCED.

Overview

A conservation easement, according to the Land Trust Alliance, is “a legal agreement between a landowner and a land trust or government agency that permanently limits uses of the land in order to protect its conservation values.” The National Conservation Easement Database (NCED) is the first national database of conservation easements in the United States. Voluntary and secure, the NCED respects landowner privacy and will not collect landowner names or sensitive information. This public-private partnership brings together national conservation groups, local and regional land trusts, and state and federal agencies around a common objective. The NCED provides a comprehensive picture of the estimated 40 million acres of privately owned conservation easement lands, recognizing their contribution to America’s natural heritage, a vibrant economy, and healthy communities.

Before the NCED was created no single, nationwide system existed for sharing and managing information about conservation easements. By building the first national database and web site to access this information, the NCED helps agencies, land trusts, and other organizations plan more strategically, identify opportunities for collaboration, advance public accountability, and raise the profile of what's happening on-the-ground in the name of conservation.

With the initial support of the U.S. Endowment for Forestry and Communities, NCED is the result of a collaboration between five environmental non-profits: The Trust for Public Land, Ducks Unlimited, Defenders of Wildlife, Conservation Biology Institute, and NatureServe.

Citation:National Conservation Easement Database, July 2012.

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Peru permanent production forests

Function
UTILIDAD

Displays official forest zoning in Peru.
Muestra la principal zonificación forestal del Perú

RESOLUTION / SCALE
Resolución / Escala

N/A

Geographic coverage
COBERTURA GEOGRÁFICA

Peru

Source data
FUENTE DE LA INFORMACIÓN

Supervisory Body for Forest and Wildlife Resources (OSINFOR).
Organismo de Supervisión de los Recursos Forestales y de Fauna Silvestre – OSINFOR.

Frequency of updates
FRECUENCIA DE ACTUALIZACIÓN

Biannual
Semestral

Date of content
FECHA DE LOS CONTENIDOS

May 2015
Mayo 2015

CAUTIONS
ADVERTENCIAS

Boundaries are subject to change from rezoning
La cobertura es susceptible a modificaciones en sus límites a partir de redimensionamientos

Overview

Permanent production forests are areas of natural primary forest that, under a ministerial resolution of the Ministry of Agriculture, are available to private interests for the preferential use of wood and other forest resources as well as wildlife as proposed by the forest and wildlife authority.

In these areas, use rights for different products of wood and wildlife may be granted, as long as they don’t affect the long-term potential of said resources.

Citation:Supervisory Body for Forest and Wildlife Resources (OSINFOR). Peru permanent production forests. 2015.

“Peru permanent production forests.” Supervisory Body for Forest and Wildlife Resources (OSINFOR). Accessed through Global Forest Watch on [date].incendios.fan-bo.org.

Learn more at www.osinfor.gob.pe or visualize the original data at sisfor.osinfor.gob.pe

Resumen

Los Bosques de Producción Permanente son áreas con bosques naturales primarios que mediante resolución ministerial del Ministerio de Agricultura se ponen a disposición de los particulares para el aprovechamiento preferentemente de la madera y de otros recursos forestales y de fauna silvestre a propuesta de la autoridad forestal y de fauna silvestre.

En estas áreas pueden otorgarse derechos para el aprovechamiento de productos diferentes de la madera y fauna silvestre, en tanto no afecten el potencial aprovechable de dichos recursos.

Cita:Organismo de Supervisión de los Recursos Forestales y de Fauna Silvestre (OSINFOR). Bosques de producción permanente del Perú. 2015

“Bosques de produccion permanente del Perú.” Organismo de Supervisión de los Recursos Forestales y de Fauna Silvestre (OSINFOR). Accedido a través de Global Forest Watch el [fecha]. incendios.fan-bo.org.

Aprenda más en www.osinfor.gob.pe o visualice los datos originales sisfor.osinfor.gob.pe

People

Data compiled under “People” indicate areas over which indigenous peoples or local communities have rights over land and/or certain resources.

The laws of many countries separate land rights from resource rights. Legally recognized land rights extend to the land and certain resources associated with the land, depending on the nature of the right. The right to the land and certain resources include some combination of rights of access, use, management, exclusion, and alienation. Similarly, legally recognized resource rights can cover some combination of the right to access, use, manage, exclude, or alienate forests, wildlife, or other resources. Whether rights to the land or resources, the law may recognize their rights in perpetuity or for a limited period of time.

Some data sets displayed on Global Forest Watch include land and resource rights governed by customary tenure systems but that are not recognized by national laws.

Land Rights

Function

Displays boundaries of areas over which indigenous peoples or local communities enjoy rights to the land and certain resources

RESOLUTION / SCALE

Varies by country

Geographic coverage

Currently available for Australia, Brazil, Canada, Costa Rica, New Zealand, and Panama

Source data

Generally based on a combination of sources, including government agencies, NGOs and other organizations. For information on country-specific concessions data please refer to the Data page.

Frequency of updates

Variable, depending on government agencies in each country and other data providers

Date of content

Varies by country

Cautions

Some data sets displayed on Global Forest Watch include land and resource rights governed by customary tenure systems but that are not recognized by national laws.
Overview

“Land Rights” refers to areas over which indigenous peoples or local communities enjoy rights to the land and certain resources, whether legally recognized or not. The exact nature of these land rights varies among tenure type and country.

The land rights data on GFW, while displayed as a single layer, is assembled on a country-by-country basis from multiple sources.

Land rights data displayed on the GFW website vary from country to country by date and data sources. Data may come from government agencies, NGOs, or other organizations.

See the Open Data Portal for details on specific data sets.

If you are aware of land rights data for additional countries, please email us here.

Suggested citation for data as displayed on GFW: “Land Rights.” World Resources Institute. Accessed through Global Forest Watch on [date]. incendios.fan-bo.org.
GFW currently includes land rights data for the following countries:
Select a country
Brazil indigenous lands

Canada aboriginal lands

Panama comarcas
Download

This data set displays the boundaries of areas designated as Indigenous Lands in Brazil. Indigenous Lands legally recognize indigenous peoples’ perpetual rights of access, use, withdrawal, management, and exclusion over the land and associated resources. Alienation of the land is prohibited. However, commercial use of forest resources is permitted, but cutting trees for sale requires approval by the National Legislature. Rights to subsoil resources may be obtained only with the approval of the National Legislature and after consultation with the affected indigenous peoples. This data set includes Indigenous Lands that are officially registered and those at various stages of the registration process.

Credit:Fundação Nacional do Índio (FUNAI)

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The Aboriginal Lands data set depicts the administrative boundaries (exterior limits) of lands where the title has been vested in specific Aboriginal Groups of Canada or lands which were set aside for their exclusive benefit. The Aboriginal Lands data set includes, but is not limited to, Indian Reserves,Cree-Naskapi Category 1A and 1A-N Lands, Yukon First Nation Settlement Lands, Kanesatake Mohawk Interim Land Base, the Inuit Owned Lands, Tlicho Lands, Inuvialuit Lands, Gwich’in Lands and Sahtu Lands.

Credit:Government of Canada, Natural Resources Canada, Earth Sciences Sector, Geomatics Canada, Surveyor General Branch. Available through the Open Government License - Canada

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This data set displays the boundaries of areas designated as comarcas in Panama. Comarcas are legally recognized semi-autonomous areas where indigenous peoples own the land and resources with rights of access, use, withdrawal, management, and exclusion. Although the Government retains ownership of subsoil resources, the indigenous community must be consulted by government and private organizations for proposed developments on their lands. The government and mining concessionaire are required to guarantee benefits to the community and compliance with sustainable development practices.

Credit:National Coordinating Body of Indigenous Peoples in Panama (COONAPIP)
Australia Aboriginal freehold lands

Overview

The inalienable Aboriginal freehold lands data set represents boundary and attribute information for land parcels, granted to incorporated Aboriginal groups through the Aboriginal Land Rights (Northern Territory) Act of 1976, which are greater than 40 hectares. Aboriginal land is private property owned under special freehold title. It is inalienable, meaning it cannot be bought, acquired, or forfeited. The inalienable Aboriginal freehold is granted as a communal title (where land is held collectively by a group, rather than by individuals), and is the strongest form of title in Australia. This title gives Aboriginal groups the power to control the direction and pace of development on their land. The data set only includes Aboriginal lands that are officially registered. More information is available at: http://www.ga.gov.au/metadata-gateway/metadata/record/42339/.

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Panama comarcas

Overview

This data set displays the boundaries of areas designated as comarcas in Panama. Comarcas are legally recognized semi-autonomous areas where indigenous peoples own the land and resources with rights of access, use, withdrawal, management, and exclusion. Although the Government retains ownership of subsoil resources, the indigenous community must be consulted by government and private organizations for proposed developments on their lands. The government and mining concessionaire are required to guarantee benefits to the community and compliance with sustainable development practices.

Credit:National Coordinating Body of Indigenous Peoples in Panama (COONAPIP)

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Brazil indigenous lands

Overview

This data set displays the boundaries of areas designated as indigenous lands in Brazil. Indigenous lands legally recognize indigenous peoples’ perpetual rights of access, use, withdrawal, management, and exclusion over the land and associated resources. Alienation of the land is prohibited. However, commercial use of forest resources is permitted, but cutting trees for sale requires approval by the National Legislature. Rights to subsoil resources may be obtained only with the approval of the National Legislature and after consultation with the affected indigenous peoples. This data set includes indigenous lands that are officially registered and those at various stages of the registration process.

Credit:Fundação Nacional do Índio (FUNAI)

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Canada aboriginal lands

Overview

The aboriginal lands data set depicts the administrative boundaries (exterior limits) of lands where the title has been vested in specific aboriginal groups of Canada or lands which were set aside for their exclusive benefit. The aboriginal lands data set includes, but is not limited to, Indian Reserves, Cree-Naskapi Category 1A and 1A-N Lands, Yukon First Nation Settlement Lands, Kanesatake Mohawk Interim Land Base, the Inuit Owned Lands, Tlicho Lands, Inuvialuit Lands, Gwich’in Lands, and Sahtu Lands.

Credit:Government of Canada, Natural Resources Canada, Earth Sciences Sector, Geomatics Canada, Surveyor General Branch. Available through the Open Government License - Canada

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Costa Rica indigenous territories

Overview

This data set displays the boundaries of the 24 legally-recognized and titled indigenous territories in Costa Rica as of 2008. It was created by the Observatorio del Desarrollo within the Universidad de Costa Rica, and is made available through the online Digital Atlas of Indigenous Peoples. Data sources include the Universidad de Costa Rica, la Universidad Nacional, and el Instituto Tecnológico. To view the interactive Atlas, please visit pueblosindigenas.odd.ucr.ac.cr/

Credit:El Observatorio del Desarrollo, Universidad de Costa Rica

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Resource Rights

Function

Displays boundaries of areas over which indigenous peoples or local communities enjoy rights to certain resources and a limited right to access the land

RESOLUTION / SCALE

Varies by country

Geographic coverage

Currently available for Cameroon, Equatorial Guinea, Liberia and Namibia

Source data

Generally based on a combination of sources, including government agencies, NGOs and other organizations. For information on country-specific concessions data please refer to the Data page.

Frequency of updates

Variable, depending on government agencies in each country and other data providers

Date of content

Varies by country

Cautions

Some data sets displayed on Global Forest Watch include land and resource rights governed by customary tenure systems but that are not recognized by national laws.
Overview

“Resource Rights” refers to areas over which indigenous peoples or local communities enjoy rights to certain resources and a limited right to access the land, whether legally recognized or not, in order to exercise their resource rights. The exact nature of these resource rights varies among tenure type and country.

The resource rights data on GFW, while displayed as a single layer, is assembled on a country-by-country basis from multiple sources.

Resource rights data displayed on the GFW website vary from country to country by date and data sources. Data may come from government agencies, NGOs, or other organizations. See the Open Data Portal for details on specific data sets.

If you are aware of resource rights data for additional countries, please email us here.

Suggested citation for data as displayed on GFW: “Resource Rights.” World Resources Institute. Accessed through Global Forest Watch on [date]. incendios.fan-bo.org.

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GFW currently includes resource rights data for the following countries:
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Cameroon Community Forests

Equatorial Guinea community forests

Liberia community forests

Namibia community forests
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This data set displays the boundaries of areas designated as Community forests in Cameroon. Community forests legally recognize a community’s ownership rights to forest resources, both timber and non-timber. It includes the right to access, use, withdraw for commercial purposes or subsistence, and exclude others from the forest. The land remains owned by the Cameroonian Government. The community’s rights to forest resources are renewed every five years as long as the community complies with the Community Forest Management Agreement. A community may also contract with a third party to commercially harvest timber.

Credit: WRI Congo Basin Forest Atlas

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This data set displays the boundaries of areas designated as Community forests in Equatorial Guinea. Community forests legally recognize a community’s right to access government owned land in order to use the forest for subsistence. The forest remains owned by the government, and must be adjacent to the community. Community forests are of perpetual duration.

Credit: WRI Congo Basin Forest Atlas

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Communal Forests are areas set aside by statute or regulation for the sustainable use of forest products by local communities or tribes on a non-commercial basis. According to the National Forestry Reform Law of 2006, no prospecting, mining, settlement, farming or commercial timber extraction is permitted on community forests.

Credit: USAID-Liberia PROSPER-

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This data set displays the boundaries of areas registered as Community forests in Namibia. Community forests are recognized by the Minister of Environment and Tourism as communal lands subject to a management plan agreed upon by the Minister and a representative body of communal land members. In accordance with the agreement, the management plan grants communal land members the rights to manage and use natural resources, including the removal of forest produce for fuel, personal shelter, or livestock shelter; allows for agricultural activity; allows communal land members to authorize others to use the community forest’s natural resources; and allows communal land members to collect a fee and set conditions for the use of natural resources.

Credit:Namibian Association of Community Based Natural Resource Management (CBNRM) Support Organisations (NACSO)
Cameroon community forest

Overview

This data set displays the boundaries of areas designated as Community forests in Cameroon. Community forests legally recognize a community’s ownership rights to forest resources, both timber and non-timber. It includes the right to access, use, withdraw for commercial purposes or subsistence, and exclude others from the forest. The land remains owned by the Cameroonian Government. The community’s rights to forest resources are renewed every five years as long as the community complies with the community forest management agreement. A community may also contract with a third party to commercially harvest timber.

Credit:WRI Congo Basin Forest Atlas

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Liberia community forests

Overview

Communal forests are areas set aside by statute or regulation for the sustainable use of forest products by local communities or tribes on a non-commercial basis. According to the National Forestry Reform Law of 2006, no prospecting, mining, settlement, farming or commercial timber extraction is permitted on community forests.

Credit:USAID-Liberia PROSPER

This data set is not available for download
Equatorial Guinea community forests

Overview

This data set displays the boundaries of areas designated as community forests in Equatorial Guinea. Community forests legally recognize a community’s right to access government owned land in order to use the forest for subsistence. The forest remains owned by the government, and must be adjacent to the community. Community forests are of perpetual duration.

Credit:WRI Congo Basin Forest Atlas

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Namibia community forests

Overview

This data set displays the boundaries of areas registered as community forests in Namibia. Community forests are recognized by the Minister of Environment and Tourism as communal lands subject to a management plan agreed upon by the Minister and a representative body of communal land members. In accordance with the agreement, the management plan grants communal land members the rights to manage and use natural resources, including the removal of forest produce for fuel, personal shelter, or livestock shelter; allows for agricultural activity; allows communal land members to authorize others to use the community forest’s natural resources; and allows communal land members to collect a fee and set conditions for the use of natural resources.

Credit:Namibian Association of Community Based Natural Resource Management (CBNRM) Support Organisations (NACSO)

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Population Density

Function

The Population Density layer measures human population per square km.

RESOLUTION / SCALE

Square Km Grid (30 Arc Seconds)

Geographic coverage

Global

Source data

Columbia University Center for International Earth Science Information Network (CIESIN)

Date of content

2000

Overview

“The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) consists of estimates of human population for the years 1990, 1995, and 2000 in a 1km global grid. The population density grids measure population per square km.

A proportional allocation gridding algorithm, utilizing more than 1,000,000 national and sub-national geographic units, is used to assign population values to grid cells. The population count grids are divided by the land area grid to produce population densities. This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT).

Citation: Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) D.L. Balk, U. Deichmann, G. Yetman, F. Pozzi, S.I. Hay and A. Nelson. Determining Global Population Distribution: Methods, Applications and Data., Advances in Parasitology 62: 119-156, 2006. incendios.fan-bo.org.

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Geographic coverage of Imazon SAD alerts

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Forest use

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Conservation

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