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Global - Forest Change 2000 to 2016 - Global Land Analysis & Discovery

This data set, a collaboration between the GLAD (Global Land Analysis & Discovery) lab at the University of Maryland, Google, USGS, and NASA, measures areas of tree cover loss across all global land (except Antarctica and other Arctic islands) at approximately 30 × 30 m resolution. 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 600,000 Landsat 7 images for the 2000-2012 interval, and more than 400,000 Landsat 5, 7, and 8 images for updates for the 2011-2016 interval. The clear land surface observations in the satellite images were assembled and a supervised learning algorithm was applied to identify per pixel tree cover loss. In this data set, “tree cover” is defined as all vegetation greater than 5 m in height and may take the form of natural forests or plantations across a range of canopy densities. 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. This data set has been updated 4 times since its creation and now includes loss up to 2016 (Version 1.4) These modifications improve change detection for 2011-2016, including better detection of boreal loss due to fire, smallholder rotation agriculture in tropical forests, selective losing, and short cycle plantations.

Dataset Details

This global dataset is divided into 10x10 degree tiles, consisting of seven files per tile. All files contain unsigned 8-bit values and have a spatial resolution of 1 arc-second per pixel, or approximately 30 meters per pixel at the equator.

Tree canopy cover for year 2000 (treecover2000) Tree cover in the year 2000, defined as canopy closure for all vegetation taller than 5m in height. Encoded as a percentage per output grid cell, in the range 0–100. Global forest cover gain 2000–2012 (gain) 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).

Year of gross forest cover loss event (lossyear) Forest loss during the period 2000–2016, defined as a stand-replacement disturbance, or a change from a forest to non-forest state. Encoded as either 0 (no loss) or else a value in the range 1–16, representing loss detected primarily in the year 2001–2016, respectively.

Data mask (datamask) Three values representing areas of no data (0), mapped land surface (1), and permanent water bodies (2).

Circa year 2000 Landsat 7 cloud-free image composite (first) Reference multispectral imagery from the first available year, typically 2000. If no cloud-free observations were available for year 2000, imagery was taken from the closest year with cloud-free data, within the range 1999–2012. Circa year 2016 Landsat cloud-free image composite (last) Reference multispectral imagery from the last available year, typically 2016. If no cloud-free observations were available for year 2016, imagery was taken from the closest year with cloud-free data, within the range 2010–2015.

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 and Resources

Additional Info

Field Value
Source http://earthenginepartners.appspot.com/science-2013-global-forest/download_v1.4.html
Author Global Land Analysis & Discovery - University of Maryland
Last Updated April 12, 2018, 11:21 (Etc/UTC)
Created April 12, 2018, 11:18 (Etc/UTC)
Origin Places Europe, Americas, Africa, Asia, Oceania
Price, £ -

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