Interactive Map Global Forest Watch. Forest change. Forest change data measure tree cover loss, tree cover gain, or forest disturbance.

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This layer displays the geographic coverage of FORMA alerts, which. WWF ecoregions. This layer displays the geographic coverage of FORMA alerts, which. WWF ecoregions. Drag the handle to adjust the minimum tree cover canopy (TCC) density for the visualization and analysis of Hansen/UMD/Google/USGS/NASA tree cover and tree cover loss. TCC density represents the estimated percent of a pixel that was covered by tree canopy in the year 2. For the tree cover loss data, TCC density therefore corresponds to the density of tree cover before loss occurred.

For example, if you select 2. TCC density, you will only see tree cover loss pixels for which the original tree cover density was greater than 2. Adjustments to the minimum TCC density only affect the tree cover and tree cover loss data layers.

This feature does not pertain to Hansen/UMD/Google/USGS/NASA tree cover gain or to other GFW data layers or statistics. Tree cover gain is displayed with a set minimum TCC density greater than 5. The minimum TCC density cannot be changed independently for tree cover and tree cover loss. A change made to one data layer will immediately take effect in the other.

This feature is also available for statistics within the Country Profiles & Rankings. Watch Online Watch In Secret Full Movie Online Film. However, the adjustment made to the visualization and analysis through the map view will not be automatically reflected in other areas of the website. To adjust the minimum TCC density within the Country Profiles & Rankings pages, click on the settings icon. Loss of tree cover may occur for many reasons, including deforestation, fire, and logging within the course of sustainable forestry operations. In sustainably managed forests, the “loss” will eventually show up as “gain”, as young trees get large enough to achieve canopy closure. Function. Identifies areas of gross tree cover loss.

Explore the status of forests worldwide by layering data to create custom maps of forest change, cover, and use.

RESOLUTION / SCALE3. Geographic coverage. Global land area (excluding Antarctica and other Arctic islands)Source data.

Landsat. Frequency of updates. Annual. Date of content.

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Tree cover canopy density. Varies according to selection (use the legend on the map to change the minimum tree cover canopy density threshold)Cautions. This data layer was updated in January 2. August 2. 01. 5 to extend the tree cover loss analysis to 2. The updates include new data for the target year and re- processed data for the previous two years (2.

The re- processing increased the amount of change that could be detected, resulting in some changes in calculated tree cover loss for 2. Calculated tree cover loss for 2. The integrated use of the original 2.

Version 1. 0) data and the updated 2. Version 1. 1) data should be performed with caution. For the purpose of this study, “tree cover” was defined as all vegetation taller than 5 meters in height. Tree cover” is the biophysical presence of trees and may take the form of natural forests or plantations existing over a range of canopy densities.

Loss” indicates the removal or mortality of tree canopy cover and can be due to a variety of factors, including mechanical harvesting, fire, disease, or storm damage. As such, “loss” does not equate to deforestation. When zoomed out (< zoom level 1.

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 1. Overview. This data set measures areas of tree cover loss across all global land (except Antarctica and other Arctic islands) at approximately 3.

The data were generated using multispectral satellite imagery from the Landsat 5 thematic mapper (TM), the Landsat 7 thematic mapper plus (ETM+), and the Landsat 8 Operational Land Imager (OLI) sensors. Over 1 million satellite images were processed and analyzed, including over 6. Landsat 7 images for the 2. Landsat 5, 7, and 8 images for updates for the 2. The clear land surface observations in the satellite images were assembled and a supervised learning algorithm was applied to identify per pixel tree cover loss. Tree cover loss is defined as “stand replacement disturbance,” or the complete removal of tree cover canopy at the Landsat pixel scale.

Tree cover loss may be the result of human activities, including forestry practices such as timber harvesting or deforestation (the conversion of natural forest to other land uses), as well as natural causes such as disease or storm damage. Fire is another widespread cause of tree cover loss, and can be either natural or human- induced. Update (Version 1. This data set has been updated twice since its creation, and now includes loss up to 2. The analysis method has been modified in numerous ways, and the update should be seen as part of a transition to a future “version 2. Key changes include: The use of Landsat 8 data for 2.

Landsat 5 data for 2. The reprocessing of data from the previous two years in measuring loss (2. Improved training data for calibrating the loss model. Improved per sensor quality assessment models to filter input data. Improved input spectral features for building and applying the loss model. These changes lead to a different and improved detection of global tree cover loss. However, the years preceding 2.

It must also be noted that a full validation of the results incorporating Landsat 8 has not been undertaken. Such an analysis may reveal a more sensitive ability to detect and map forest disturbance using Landsat 8 data. If this is the case then there will be a more fundamental limitation to the consistency of this data set before and after the inclusion of Landsat 8 data. Validation of Landsat 8- incorporated loss detection is planned. Some examples of improved change detection in the 2. Improved detection of boreal forest loss due to fire. Improved detection of smallholder rotation agricultural clearing in dry and humid tropical forests.

Improved detection of selective logging. These are examples of dynamics that may be differentially mapped over the 2. Version 1. 1. A version 2. The original version 1. 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. 2. High- Resolution Global Maps of 2. Century Forest Cover Change.” Science 3. November): 8. 50–5. Data available online from: http: //earthenginepartners. 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. 2. 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]. Learn more or download data. Function. Deforestation monitoring system for the Brazilian Amazon used by the Brazilian government to establish public policy. RESOLUTION / SCALE3.

Geographic coverage. Brazilian Amazon. Source data. Landsat, supplemented with CBERS, Resourcesat, and UK2- DMCFrequency of updates. Annual. Date of content. Cautions. PRODES only identifies forest clearings of 6. Frequent cloud cover over areas of the Amazon may change the reported year of deforestation.

The year reported is the first year deforestation is identified by analysts, but this does not necessarily correspond to the year of deforestation if the landscape has been covered by clouds in previous years. License. Creative Commons BY SA 3. Overview. The PRODES project monitors clear cut deforestation in the Brazilian Legal Amazon, and has produced annual deforestation rates for the region since 1.