Tree cover gain 2000-2012: Thailand, Vietnam, Laos, Cambodia, Myanmar

Forest gain during the period 2000–2012, defined as the inverse of loss, or a non-forest to forest change entirely within the study period. Encoded as either 1 (gain) or 0 (no gain). 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.

Data Resources (1)

Additional Info

Field Value
Dataset topic category
  • Environment and natural resources
  • Forest classifications
  • Forest cover
  • Forest policy and administration
  • Forests and forestry
  • English
Use limitations You are free to copy and redistribute the material in any medium or format, and to transform and build upon the material for any purpose, even commercially. You must give appropriate credit, provide a link to the license, and indicate if changes were made. Use the following credit when these data are displayed: Source: Hansen/UMD/Google/USGS/NASA
Dataset reference date 2012-07-11
Temporal extent's start date 2000-02-03
Temporal extent's end date 2012-02-03
  • Cambodia
  • China
  • Lao People's Democratic Republic
  • Myanmar
  • Thailand
  • Viet Nam
Positional Accuracy There are no known issues with accuracy.
Logical Consistency There are no known issues with logical consistency.
Completeness 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).
Process Step 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. Open Development Mekong has trimmed this data to the area of interest visualised here.
Lineage 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:
Responsible party Department of Geographical Sciences University of Maryland, 2181 Samuel J. LeFrak Hall, 7251 Preinkert Drive, College Park, MD 20742 Phone: 301-405-4050
Metadata creator information Metadata last updated on 2016-02-03. For inquiries contact: Open Development Cambodia,, +855 23 221 164,, 43 St. 208, Sangkat Boeung Riang, Khan Daun Penh, Phnom Penh, Cambodia.
License CC-BY-4.0
Copyright No
Version 1.0
Date uploaded July 9, 2015, 10:05 (UTC)
Date modified November 10, 2018, 14:01 (UTC)