2024-07-11T15:09:23.802886

2025-01-15T20:49:26.901862

30 × 30 meters

Global land area (excluding Antarctica and other Arctic islands)

Every three years

global

Use the following credit when these data are displayed: Source: Hansen/UMD/Google/USGS/NASA, accessed through Global Forest Watch Use the following credit when these data are cited: Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend. 2013. “High-Resolution Global Maps of 21st-Century Forest Cover Change.” *Science* 342 (15 November): 850–53. Data available on-line from:http://earthenginepartners.appspot.com/science-2013-global-forest. Accessed through Global Forest Watch on [date]. www.globalforestwatch.org

Tree cover gain

(12 years, 30m, global, Hansen/UMD/Google/USGS/NASA)

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

[CC BY 4.0](http://creativecommons.org/licenses/by/4.0/)

English

This data set, a collaboration between the [GLAD](http://glad.geog.umd.edu/) (Global Land Analysis & Discovery) lab at the University of Maryland, Google, USGS, and NASA, 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](http://landsat.usgs.gov/) 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.<br><br>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.<br><br>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).<br><br>The tree cover canopy density of the displayed data is >50%.<br>

Identifies areas of tree cover gain

In this data set, “tree cover” is defined as all vegetation greater than 5 meters in height, and may take the form of natural forests or plantations across a range of canopy densities. “Gain” is 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. <br><br>Due to variation in research methodology and date of content, tree cover, loss, and gain data sets cannot be compared accurately against each other. Accordingly, “net” loss cannot be calculated by subtracting figures for tree cover gain from tree cover loss, and current (post-2000) tree cover cannot be determined by subtracting figures for annual tree cover loss from year 2000 tree cover. <br><br>The authors evaluated the overall prevalence of false positives (commission errors) in this data at 24%, and the prevalence of false negatives (omission errors) at 26%, though the accuracy varies by biome and thus may be higher or lower in any particular location. Read our [blog series](http://blog.globalforestwatch.org/data/how-accurate-is-accurate-enough-examining-the-glad-global-tree-cover-change-data-part-1.html) on the accuracy of this data for more information.<br>

CC BY 4.0

Best available global data of tree cover gain

http://science.sciencemag.org/content/342/6160/850

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