Canada

Conventions change

Convention on Biological Diversity (CBD)

The Convention on Biological Diversity was launched on 29 December 1993. Its three main objectives are to conserve biological diversity, sustainably use the components of biological diversity, and fairly and equitably share the benefits resulting from the use of genetic resources.

Terms
All terms—“ratification,” “accession,” “approval,” and “acceptance”—signify a state’s consent to be bound by a treaty. The legal incidents and implications of ratification, accession, approval, and acceptance are the same. The treaty becomes legally binding on the state or the regional economic integration organization. Countries that have not ratified the treaty are identified as “Non Parties.”

Ratification and Accession
Ratification and accession have the same legal effect. The main distinction concerns when a state accepts the offer or the opportunity to become a party to a treaty. Only states that have signed a treaty, while it was open for signature, can proceed to ratify it. The signature does not establish consent to be bound, hence the need for ratification. Accession is the act whereby a state becomes a party to a treaty that has already been negotiated and signed by other states.

Acceptance and Approval
The terms “acceptance” and “approval” originated more recently and apply under the same conditions as those for ratification. The legal effect is the same as ratification. The use of one term or the other results from differences in legal systems. Certain countries, especially some East European states, use the terms “acceptance” or “approval” for participation in treaties. The terms are also used when organizations (e.g., the EU) rather than states become parties to an international treaty.

Succession
Succession occurs when one state replaces another in the responsibility for the international relations of a territory. Generally, a newly independent state that issues a notification of succession is considered a party to a treaty from the date of the succession of states or from the date of entry into force of the treaty, whichever is later.

Citation: CBD, 2013

United Nations Framework Convention on Climate Change (UNFCCC)

The United Nations Framework Convention on Climate Change was negotiated at the Earth Summit in Rio de Janeiro from 3 to 14 June 1992 and entered into force on 21 March 1993. The treaty’s main goal is the “stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference with the climate system.”

Terms
The convention divides countries into three main groups based on their commitments.

Annex 1 Parties
Industrialized countries that were members of the Organisation for Economic Co-operation and Development (OECD) in 1992 and countries with economies in transition (EIT Parties), such as the Russian Federation, the Baltic states, and several Central and Eastern European states.

Annex II Parties
OECD members of Annex I but not the EIT Parties. Annex II Parties are required to provide financial resources to enable developing countries to undertake emissions reduction activities under the convention and to help them adapt to effects of climate change.

Non–Annex I Parties
Mostly developing countries that are recognized by the convention as being particularly vulnerable to the adverse impacts of climate change and/or the potential economic impacts of climate change response measures.

Citation: UNFCCC, 2013

Kyoto Protocol

The Kyoto Protocol was adopted on 11 December 1997 and entered into force on 16 February 2005. It is an international agreement linked to the United Nations Framework Convention on Climate Change that sets internationally binding emission reduction targets for its parties.

Terms

Ratification and Accession
Ratification and accession have the same legal effect. The main distinction concerns when a state accepts the offer or the opportunity to become a party to a treaty. Only states that have signed a treaty, while it was open for signature, can proceed to ratify it. The signature does not establish consent to be bound, hence the need for ratification. Accession is the act whereby a state becomes a party to a treaty that has already been negotiated and signed by other states.

Citation: UNFCCC, 2013

United Nations Convention to Combat Desertification (UNCCD)

The United Nations Convention to Combat Desertification was adopted on 17 June 1994 and entered into force in December 1996. The Convention aims to combat desertification and to mitigate the effects of drought.

Terms

Ratification and Accession
Ratification and accession have the same legal effect. The main distinction concerns when a state accepts the offer or the opportunity to become a party to a treaty. Only states that have signed a treaty, while it was open for signature, can proceed to ratify it. The signature does not establish consent to be bound, hence the need for ratification. Accession is the act whereby a state becomes a party to a treaty that has already been negotiated and signed by other states.

Citation: UNCCD, 2012

International Tropical Timber Agreement (ITTA)

The International Tropical Timber Agreement entered into force on 7 December 2011. The agreement aims “to promote the expansion and diversification of international trade in tropical timber from sustainably managed and legally harvested forests and to promote the sustainable management of tropical timber producing forests.”

Terms
Members of the ITTA have consented to be bound by this agreement. Producer members are those situated between the Tropic of Cancer and the Tropic of Capricorn with tropical forest resources and/or a net export of tropical timber. Consumer members are those that import tropical timber.

Citation: ITTO, 2011

Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES)

The Convention on International Trade in Endangered Species of Wild Fauna and Flora is an international agreement that aims to ensure that international trade of wild plants and animals does not threaten their survival.

Terms
All terms—“ratification,” “accession,” “approval,” and “acceptance”—signify a state’s consent to be bound by a treaty. The legal incidents and implications of ratification, accession, approval, and acceptance are the same. The treaty becomes legally binding on the state or the regional economic integration organization. Countries that have not ratified the treaty are identified as “Non Parties.”

Ratification and Accession
Ratification and accession have the same legal effect. The main distinction concerns when a state accepts the offer or the opportunity to become a party to a treaty. Only states that have signed a treaty, while it was open for signature, can proceed to ratify it. The signature does not establish consent to be bound, hence the need for ratification. Accession is the act whereby a state becomes a party to a treaty that has already been negotiated and signed by other states.

Acceptance and Approval
The terms “acceptance” and “approval” originated more recently and apply under the same conditions as those for ratification. The legal effect is the same as ratification. The use of one term or the other results from differences in legal systems.

Certain countries, especially some East European states, use the terms “acceptance” or “approval” for participation in treaties. The terms are also used when organizations rather than states become parties to an international treaty (for example, the EU).

Succession
Succession occurs when one state replaces another in the responsibility for the international relations of a territory. Generally, a newly independent state which makes a notification of succession is considered a party to a treaty from the date of the succession of states or from the date of entry into force of the treaty, whichever is later.

Citation: CITES, 2013

The Ramsar Convention on Wetlands (Ramsar)

The Ramsar Convention, known as the Convention on Wetlands of International Importance, is an “intergovernmental treaty that provides the framework for national action and international cooperation for the conservation and wise use of wetlands and their resources.” The treaty entered into force on 21 December 1971.

Terms
Contracting parties have "signaled a commitment on the part of the national government to work actively to support the ‘three pillars’ of the Convention: 1) ensuring the conservation and wise use of wetlands it has designated as Wetlands of International Importance, 2) including as far as possible the wise use of all wetlands in national environmental planning, and 3) consulting with other Parties about implementation of the Convention, especially in regard to transboundary wetlands, shared water systems, and shared species."

Citation: www.ramsar.org

World Heritage Convention

Created in 1972, the World Heritage Convention aims to identify and preserve the world’s cultural and natural heritage. The convention lays out the responsibilities of a state’s parties in identifying potential sites of outstanding universal value and the parties’ role in protecting and preserving these sites.

Terms
All terms—“ratification,” “accession,” “approval,” and “acceptance”—signify a state’s consent to be bound by a treaty. The legal incidents and implications of ratification, accession, approval, and acceptance are the same. The treaty becomes legally binding on the state or the regional economic integration organization. Countries that have not ratified the treaty are identified as “Non Parties.”

Ratification and Accession
Ratification and accession have the same legal effect. The main distinction concerns when a state accepts the offer or the opportunity to become a party to a treaty. Only states that have signed a treaty, while it was open for signature, can proceed to ratify it. The signature does not establish consent to be bound, hence the need for ratification. Accession is the act whereby a state becomes a party to a treaty that has already been negotiated and signed by other states

Acceptance and Approval
The terms “acceptance” and “approval” originated more recently and apply under the same conditions as those for ratification. The legal effect is the same as ratification. The use of one term or the other results from differences in legal systems.

Certain countries, especially some East European states, use the terms “acceptance” or “approval” for participation in treaties. The terms are also used when organizations rather than states become parties to an international treaty (for example, the EU).

Succession
Succession occurs when one state replaces another in the responsibility for the international relations of a territory. Generally, a newly independent state which makes a notification of succession is considered a party to a treaty from the date of the succession of states or from the date of entry into force of the treaty, whichever is later.

Citation: UNESCO, 2013

Non-Legally Binding Instrument

The Non–Legally Binding Instrument (NLBI) on All Types of Forests was adopted on 17 December 2007. The main purposes of this instrument are to (1) strengthen political commitment and action at all levels to implement sustainable management of all forest types and to achieve shared global objectives on forests; (2) enhance the contribution of forests to the achievement of international development goals; and (3) provide a framework for national action and international cooperation.

The NLBI includes all UN member states. It is not legally binding and does not require ratification.

Citation: UNFF, 2013

ILO 169

Convention No. 169 of the International Labour Organization is a legally binding international instrument dealing with the rights of indigenous and tribal peoples. The convention entered into force on 5 September 1991 and is open for ratification.

Citation: ILO, 2013

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 UMD/Google tree cover loss and extent displayed in the graphs and rankings. TCC density represents the estimated percent of a UMD/Google 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.

Adjustments to the minimum TCC density will only affect UMD/Google tree cover loss and extent. This feature does not pertain to UMD/Google tree cover gain or to other GFW data layers or statistics. UMD/Google tree cover gain is displayed with a set minimum TCC density greater than 50%.

This feature is also available for the map visualization and analysis and in the global overview pages. The TCC density minimum selected in the country pages will be applied to the country or subnational country analysis and related map visualization if accessed through the country pages. However, an adjustment to the TCC density minimum through the map settings will not affect the country page statistics. Adjustments made in individual country pages will not be reflected automatically in the global overview pages.
University of Maryland/Google tree cover loss (annual, 30m, global)

Download at project website

Function

Identifies areas of tree cover loss

Resolution/scale

30 × 30 meters

Geographic coverage

Global land area (excluding Antarctica and other Arctic islands)

Source data

Landsat 7 ETM+

Frequency of updates

Annual

Date of content

2001–2012

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. “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) annually at 30 × 30 meter resolution. 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 chronologically and a supervised learning algorithm was then applied to identify per pixel tree cover loss or gain.

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 indicate a number of potential activities, such as timber harvesting, fires or disease, the conversion of natural forest to other land uses, or the crop rotations 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.

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]. www.globalforestwatch.org.

Learn more or download data
University of Maryland/Google tree cover loss (annual, 30m, global)

Overview

These infographics were created using tree cover, loss, and gain data from the University of Maryland (UMD)/Google. For more information on this data set, please visit the Data Page.

The UMD/Google infographics can be viewed by country or by subnational boundary. Click "SELECT AREA" to view data for a different region.

Note: "SELECT AREA" and "SETTINGS" only affect infographics within the UMD/Google data portion of the country pages and do not apply to FORMA, FOREST TYPE, PEOPLE & ECONOMY" or to other parts of this page.

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.

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]. www.globalforestwatch.org.

Learn more or download data
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

12-year cumulative, updated annually

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).

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.

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]. www.globalforestwatch.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]. www.globalforestwatch.org.

Learn more or download data
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:
1. 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.
2. 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.
3. 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)
Publications:
- Alerts of forest disturbance from MODIS imagery (International Journal of Applied Earth Observation and Geoinformation 33 (2014) 1–9) [pdf]
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
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].www.globalforestwatch.org.

Learn more or download data

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.

Download data from CartoDB
QUICC alerts (quarterly, 5km, <37 degrees north)

Download

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].www.globalforestwatch.org.

Learn more or download data

Geographic coverage of QUICC alerts

The geographic coverage of QUICC alerts is global, except for 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 square kilometer 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]. www.globalforestwatch.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://www.globalforestwatch.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].www.globalforestwatch.org.

Forest cover

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

Tree cover extent

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+

Frequency of updates

Update coming in 2015

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.

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 Extent.” University of Maryland, Google, USGS, and NASA. Accessed through Global Forest Watch on [date]. www.globalforestwatch.org.

Learn more or download data
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 their degradation 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 and may contain inconsistencies and inaccuracies because of limitations in the spatial resolution of the imagery and lack of ancillary information about local land-use practices in some regions. In addition, the treatment of fire as a form of degradation in the IFL methodology may vary from the understanding of fire dynamics in different regions and ecozones.

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 to allow for repeated assessments over time as well for verification. The criteria were separated into two groups to assess the spatial extent of developed areas and the degradation of these areas. These were then mapped and identified from Landsat satellite imagery for the year 2013. Degraded areas were identified as areas that had changed from 2000-2013 based on comparison with the 2000 IFL data – either through tree cover loss or fragmentation by roads or other infrastructure. The landscapes identified as unfragmented were at least 50,000 hectares in size with a minimum width of 10 kilometers. 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., Yaroshenko A., Turubanova S., Dubinin M., Laestadius L., Thies C., Aksenov D., Egorov A., Yesipova Y., Glushkov I., Karpachevskiy M., Kostikova A., Manisha A., Tsybikova E., Zhuravleva I. 2008. Mapping the World's Intact Forest Landscapes by Remote Sensing. Ecology and Society, 13 (2) http://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 degradation from 2000-2013. Accessed through Global Forest Watch on [date]. www.globalforestwatch.org

Learn more or download data
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

Learn more or download data
Mangroves

Download at project website

Function

Shows the global distribution of mangrove forests, derived from earth observation satellite imagery

Resolution/scale

Mapped from 30 meter Landsat imagery

Geographic coverage

Global

Source data

Landsat Global Land Survey Collection

Frequency of updates

None planned

Date of content

2011

Cautions

Results were validated using existing distribution data and published literature.
Note that small patches (< 900-2,700 m²) 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 ihe status and distribution of global mangroves were mapped using recently available Global Land Survey (GLS) data and the Landsat archive.The project interpreted approximately 1,000 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 square kilometers 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 (2011a). Global distribution of mangroves forests of the world using earth observation satellite data. In Supplement to: Giri et al. (2011b). Cambridge (UK): UNEP World Conservation Monitoring Centre. Giri C, Ochieng E, Tieszen LL, Zhu Z, Singh A, Loveland T, Masek J, Duke N (2011b). Status and distribution of mangrove forests of the world using earth observation satellite data. Global Ecology and Biogeography 20: 154-159

Learn more or download data

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.

Logging
Download

Function

Displays boundaries of areas allocated by governments to companies for logging

Resolution/scale

Varies by country

Geographic coverage

Currently available for Cameroon, Canada, Central African Republic, Democratic Republic of the Congo (DRC), Equatorial Guinea, Gabon, Republic of the Congo, Liberia, 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 be comprehensive of all existing concessions in a country, and the location of certain concessions can be inaccurate.

Overview

“Logging concession” refers to an area allocated by a government for logging in a public forest. Logging concessions are distinct from wood fiber concessions, where plantation forests are established for the 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 from public forests; terminology varies at the national level, however, and includes "forest permits," "tenures," "licenses," and other terms.

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

Logging concession 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 Data page for details on specific data sets.

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

Suggested citation for data as displayed on GFW: “Logging.” World Resources Institute. Accessed through Global Forest Watch on [date]. www.globalforestwatch.org.

Learn more or download data
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.

Download

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.

Download

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

Download

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)

Download

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

Download

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

Download

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
Mining
Download

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, Colombia, Democratic Republic of the Congo (DRC), Gabon, 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

“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.

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

Mining concession 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 Data page for details on specific data sets.

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]. www.globalforestwatch.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)

Download

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.
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.

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

Oil palm concession 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 Data page for details on specific data sets.

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]. www.globalforestwatch.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.
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 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.

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

Wood fiber concession 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 Data page for details on specific data sets.

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]. www.globalforestwatch.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.

Conservation

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

Protected Areas
Download at 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

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 Canada, Brazil 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 Data page 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]. www.globalforestwatch.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)

Download

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

Not currently available for download

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)
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 Data page 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]. www.globalforestwatch.org.

Learn more or download data
GFW currently includes resource rights data for the following countries:
Select a country
Cameroon Community Forest

Equatorial Guinea Community Forests

Liberia Community Forests

Namibia Community Forests
Download

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

Download

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

Currently unavailable for download

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-

Download

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)
Population Density

Download at project website

Function
<<<<<<< HEAD
Measures human population per square kilometer
=======
The Population Density layer measures human population per square km.
>>>>>>> 4cceb2d3a0b95fe6fbae627653f9284fa21dbc01

Resolution/scale

Square Kilometer Grid (30 Arc Seconds)

Geographic coverage

Global

Source data

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

<<<<<<< HEAD
Frequency of updates

None planned

======= >>>>>>> 4cceb2d3a0b95fe6fbae627653f9284fa21dbc01
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 1 kilometer global grid. The population density grids measure population per square kilometer.

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. www.globalforestwatch.org.

Base maps

Base maps provide a variety of map backgrounds for visual comparison with other data.

Default

The default base map is derived from Google Maps and shows political boundaries, major geological features, and other key areas of interest. Read the terms of service here.
Terrain

Google Maps’ terrain base map shows geographical and topographical details. Scale varies by location. Read the terms of service here.
Satellite

Google Maps’ satellite base map consists of a mix of recent (1–3 years old) mid-resolution and high-resolution satellite and aerial imagery from multiple providers for a given area. TerraMetrics TruEarth 15-meter imagery is the baselayer imagery that covers the entire globe, and Google adds high-resolution imagery, where available, over TruEarth 15-meter imagery to provide additional visual details. Read the terms of service here.
Roads

Google Maps Road Network base map shows the extent of collected and generated road features. The map is proprietary to Google and cannot be downloaded. Scale varies by location. Read the terms of service here.
Tree Height

This base map depicts the highest points in the forest canopy. Its spatial resolution is 0.6 miles (1 km) and was validated against data from a network of nearly 70 ground sites around the world. It was developed by a team of scientists from NASA’s Jet Propulsion Laboratory, Pasadena, California; the University of Maryland, College Park; and Woods Hole Research Center, Falmouth, Massachusetts. The map was created using 2.5 million carefully screened, globally distributed laser pulse measurements from space. The light detection and ranging (Lidar) data were collected in 2005 by the Geoscience Laser Altimeter System instrument on NASA’s Ice, Cloud, and land Elevation Satellite (ICESat).

Source: www.nasa.gov/topics/earth/features/forest20120217.html
Landsat Composites

These base maps show a composite of the best annual Landsat satellite imagery (USGS/NASA) from 1999 to 2012. The annual composites were generated by Google in the Google Earth Engine. The Landsat composites display “Top-of-Atmosphere,” or the most cloud-free, images at 30-meter resolution. More information on Landsat imagery is available from the Landsat website. Read the terms of service here.

Note: Because of the very large file size of the annual Landsat composite layers, images will take some time to reload on the website and as you zoom in and out.

Countries

Data provided on the country pages come from a range of sources. Read below to learn more about each.

Food and Agriculture Organization of the United Nations (FAO)

Many figures on the country pages come from the FAO’s Global Forest Resources Assessment (FRA). As stated on the FAO website, the FRA is a comprehensive assessment of forests and forestry that examines the current status and recent trends for different variables covering the extent, condition, uses and values of forests. To create the report, information was collated from 233 countries and territories for four points in time: 1990, 2000, 2005 and 2010. FAO worked closely with countries and specialists in the design and implementation of FRA 2010 - through regular contact, expert consultations, training for national correspondents and ten regional and subregional workshops. More than 900 contributors were involved, including 178 officially nominated national correspondents and their teams. To learn more, visit the FAO website or download the full report.

The country pages also present data from FAOSTAT, FAO’s platform for data collection and dissemination. According to FAO, the FAOSTAT Emissions Land Use database provides country-level estimates of greenhouse gas (GHG) emissions based on FAOSTAT activity data using Tier 1 computations, following 2006 Intergovernmental Panel on Climate Change (IPCC) Guidelines for National GHG Inventories. Changes in carbon stocks and ecosystem function linked to anthropogenic activities such as land-use change and land management determine emissions and removals of GHG that are reported by countries for the IPCC Land Use, Land-Use Change and Forestry (LULUCF) categories. To learn more, visit the FAOSTAT website.

Data on the economic value and employment in national forestry sectors are reported from “Contribution of the forestry sector to national economies, 1990-2006” by A. Lebedys. Forest Finance Working Paper FSFM/ACC/08. FAO, Rome. To learn more, download the full report.

Figures: type of forest, economic value of the forestry sector, employment, carbon stocks, emissions

University of Maryland (UMD)/Google

Figures for tree cover extent, loss, and gain presented on the country and global overview pages were calculated using tabular data from a 2013 publication, “High-Resolution Global Maps of 21st-Century Forest Cover Change" by Hansen et al.

To learn more, visit the Forest Change tab on the Data page.

Figures: UMD/Google circle graphs, 2012 tree cover extent, all global overview graphs and rankings

European Space Agency (GlobCover)

Data from the European Space Agency’s GlobCover was used to visualize tree cover extent on the country pages. As stated on the ESA website, GlobCover is an initiative which began in 2005 in partnership with a number of organizations. The aim of the project was to develop a service capable of delivering global composites and land cover maps using input observations from the 300m MERIS sensor on board the ENVISAT satellite mission. ESA makes available the land cover maps, which cover 2 periods: December 2004 - June 2006 and January - December 2009. To learn more, visit the GlobCover website or download the 2009 GlobCover map.

Figures: Map of tree cover extent

The Rights and Resources Initiative (RRI)

Figures on forest tenure come from the Rights and Resource Initiative and are based on data adapted from the Tropical Forest Tenure Assessment. The goal of the report is to present and analyze the state of forest tenure in much of the world’s tropical forests. As stated on RRI's website, the tenure systems represented by this data is sourced from governments, and therefore only reflects those systems of natural resource management that are legally recognized by those governments. Such officially outlined tenure systems fall under the category of statutory tenure regimes within these studies. The official data often presents an incomplete picture of the institutions that actually manage natural resources, particularly at a local level. To learn more, visit the RRI forest tenure page.

Figures: Forest tenure

Data policy & standards

Learn more about Global Forest Watch’s commitment to high quality, open data.

Data standards

Global Forest Watch is committed to providing the highest-quality data on the world’s forests that is currently available. All of the data provided on GFW have been assessed with respect to several indicators of quality, including timeliness, accuracy, completeness, geographic coverage, innovation, and objectivity.

In some cases, the best available data still have known shortcomings with respect to one or more of these indicators. In those cases, we provide a “caution” explaining known issues or inaccuracies.

Global Forest Watch has an open data policy and commits to make our data, and that of our partners, open, discoverable, downloadable, and usable. We believe that open data enables the innovation, information sharing, analysis, and transparency required to support policies that better manage and sustain the world’s forests.
Open data policy

Global Forest Watch has an open data policy, intended to provide information free of constraints and restrictions on use. All of the data we produce is shared using licensing which conforms to open data standards and made available for download whenever possible.

For data sets not produced by GFW, we provide links to download data from the original source when they are available.
Data sharing
Terms of use
- For data sets produced by GFW, you are free to use, distribute, copy, modify, and display the data for commercial and noncommercial purposes.
- You are free to use maps, graphics, charts, and other representations of data on the GFW website, with The MIT License (MIT).
- Licensing is determined for each individual data set—please refer to the licensing text for detailed information.
- You must attribute the data as indicated in the metadata or licensing for each individual data set.
- You must not imply that Global Forest Watch endorses your use of the data, or use the Global Forest Watch logo in conjunction with such use.
- Through accessing the GFW site you have acknowledged and agreed to our Terms of Service.
- The GFW site includes data sets produced by many organizations, some of which may have more restrictive data licensing. Please refer to the licensing of the original data source for more information.
Permissions & licensing

Except as noted below, all material on this site carries The MIT License (MIT), which permits unrestricted reuse of GFW content when proper attribution is provided. This means you are free to copy, display, and distribute GFW’s work, or include our content in derivative works, under the following conditions:
- Attribution. You must clearly attribute the work and provide a link back to the work on www.globalforestwatch.org. Doing so ensures that people access the latest available information, in the event that the publication is revised or more research is published. Click here for the full legal code of The MIT License (MIT). Some content on this site may carry additional copyright restrictions. GFW has made every effort to clearly label such content.
- Photographs. Most of the photographs featured on this site have either been licensed under nontransferable terms, or have been acquired from photo-sharing sites such as Flickr that have their own policies for public use. Unless indicated otherwise, The MIT License (MIT) described above does not apply to photographs and images used on this site.
- Charts, Graphs, & Maps. Charts, graphs, and maps produced by GFW may be used according to The MIT License (MIT). Where graphs employ data from third parties, we may not be able to grant permissions to the original data used in these charts, although such permissions may be granted by the owners of the data. In these cases, please contact the third-party organizations directly to ask about permissions. If you have any questions about citing or reusing GFW content, please visit the How to page or contact us.

Nov	DEC	Jan
	04
2013	2014	2015

Tree cover (2000)

Percent Tree Cover (2000)

LOSS AND GAIN (2001 - 2012)

There were FORMA alerts in

The forestry sector contributed USD 19.8 billion to the economy in 2011, which is appoximately 1.2% of the GDP.

234 thousand people are directly employed by the forestry sector, according to 2011 FAO data.

This country has 13,908 million metric tons of carbon stocks in living forest biomass.

According to FAO data, 15.5% of GHG emissions in this country came from land-use change and forestry in 2011.

Canada stories

How do we save the worlds vanish...

State of the forest

People & economy

Tenure & laws

Climate change

Conventions change

Forest change

Overview

Overview

Overview

Overview

Methodology

Explanation

Temporal and spatial resolution

Geographic extent

Data applications

Accuracy and validation

Additional resources on FORMA

Geographic coverage of FORMA alerts

Overview

Geographic coverage of Imazon SAD alerts

Overview

Geographic coverage of QUICC alerts

Overview

Overview

Forest cover

Overview

Overview

Overview

Overview

Overview

Forest use

Overview

Select a country

Overview

Select a country

Overview

Select a country

Overview

Select a country

Conservation

Overview

Other Important Designations

Overview

People

Overview

Select a country

Overview

Select a country

Overview

Stories

Base maps

Countries

Food and Agriculture Organization of the United Nations (FAO)

University of Maryland (UMD)/Google

European Space Agency (GlobCover)

The Rights and Resources Initiative (RRI)

Code

GFW on Google Earth Engine

GFW on ArcGIS Online

Data policy & standards

Terms of use

Permissions & licensing

Please confirm

Why accept?

234
thousand people are directly employed by the forestry sector, according to 2011 FAO data.