Local knowledge helped researchers ground-truth desert forest tracking. (WRI)
No single person could ever hope to count the world’s trees. But a crowd of them just counted the world’s drylands forests—and, in the process, charted forests never before mapped, cumulatively adding up to an area equivalent in size to the Amazon rainforest. Current technology enables computers to automatically detect forest area through satellite data in order to adequately map most of the world’s forests. But drylands, where trees are fewer and farther apart, stymied these modern methods. To measure the extent of forests in drylands, which make up more than 40 percent of land surface on Earth, researchers from UN Food and Agriculture Organization (FAO), World Resources Institute and several universities and organizations had to come up with unconventional techniques. Foremost among these was turning to residents, who contributed their expertise through local map-a-thons.
Technical Challenges, Human Solutions
Traditional remote sensing algorithms detect tree cover in a pixel rather than capturing individual trees in a landscape. That means the method can miss trees in less-dense forests or individual trees in farm fields or grasslands, which is most often the nature of dryland areas.
Hansen/UMD/Google/USGS/NASA tree cover data displayed on Global Forest Watch. Green pixels represent tree cover with greater than 20 percent canopy density but do not count trees outside of these pixels. Note, coarse pixels as shown above may be more efficient for rapidly detecting large scales of deforestation, while individual mapping techniques as described below may be more effective for monitoring land restoration and degradation.
Google Earth collects satellite data from several satellites with a variety of resolutions and technical capacities. The dryland satellite imagery collection compiled by Google from various providers, including Digital Globe, is of particularly high quality, as desert areas have little cloud cover to obstruct the views. So while difficult for algorithms to detect non-dominant land cover, the human eye has no problem distinguishing trees in the landscapes. Using this advantage, the scientists decided to visually count trees in hundreds of thousands of high-resolution images to determine overall dryland tree cover.