Researchers today released a long-awaited tool that reveals the extent of forest cover loss and gain on a global scale. Powered by Google’s massive computing cloud, the interactive forest map establishes a new baseline for measuring deforestation and forest recovery across all of the world’s countries, biomes, and forest types.

The map has far-reaching implications for efforts to slow deforestation, which accounts for roughly ten percent of greenhouse gas emissions produced by human activities, according to the authors of the paper that describes the tool and details its first findings.

“People will use these data in ways we can’t even imagine today,” said Matthew Hansen, a University of Maryland geographer who is the lead author of the study, which will be published in tomorrow’s issue of the journal Science. “Brazil had used Landsat data to document its deforestation trends and to inform policy and they also shared their data publicly. But such data has not been widely available for other parts of the world. Our global mapping of forest cover lifts the veil—revealing what’s happening on the ground in places people could only conjecture about before.”

The map does not distinguish between natural forests and plantations, but the underlying database will support the development of additional layers, which can be used to create masks for oil palm and timber plantations, enabling users to distinguish between deforestation, replanting of plantations, and conversion of forests to plantations.

The study finds that some 2.3 million square kilometers (888,000 square miles) of forest was lost between 2000 and 2012. But that area was partly offset by 800,000 sq km of forests that regrew. Forest loss was highest in the tropics, which was the only region in the world where deforestation is increasing.

But the power of the map lies in its granularity which comes from its 30 meter resolution and consistency in defining forest cover. For example, while Brazil’s sharp fall in forest loss since 2004 is widely known, the drop has been outpaced by surging deforestation in Indonesia, Malaysia, Paraguay, Bolivia, Zambia, and Angola. Counterintuitively, Indonesia experienced a jump in deforestation after it established a moratorium on granting new concessions in primary forest areas and peatlands.

Outside the tropics, Russia is losing upwards of 3.6 million hectares of forest per year, an area that is only partially offset by forest recovery. Even the United States experienced significant forest clearing between 2000 and 2012, amounting to a net less of 12.6 million hectares. Disturbance rates in the southeastern United States were more four times greater than those of South American rainforests.

At the ecozone level, tropical rainforests (601,071 sq km), boreal coniferous forest (350,135 sq km), and tropical moist deciduous forest (300,149) experienced the largest area of forest loss. But it was less well-known forests were most heavily decimated during the study period.

“The tropical dry forests of South America had the highest rate of tropical forest loss, due to deforestation dynamics in the Chaco woodlands of Argentina, Paraguay, and Bolivia,” the researchers write. “Eurasian rainforests and dense tropical dry forests of Africa and Eurasia also had high rates of loss.”





Unlike most previous forest assessments — like the industry standard Forest Resource Assessments (FRA) from the U.N. Food and Agriculture Organization (FAO) — the new data go beyond mapping simple net change in forest cover, which can mask subtle but important ecological transformation like the shift from biodiversity-rich and carbon-dense old-growth forests to scrubbier degraded and secondary forests.



Animation showing forest loss in Riau, on the Indonesian island of Sumatra. Much of this deforestation was to establish plantations for pulp and paper, timber, and palm oil production. Click image to enlarge.

“Net deforestation targets are mostly ambiguous with respect to carbon emissions, biodiversity, and hydrological services because, according to the FAO-FRA methodology, low or even negative net deforestation may be reported even when there are large losses of native forests, if those losses are offset by increases in young secondary forests or tree plantations with inferior carbon, biodiversity, and hydrological service values,” write Sandra Brown and Daniel Zarin in a commentary accompanying the Science paper. “For this reason, and to safeguard the customary rights to native forests of indigenous and other local people, UNFCCC negotiators agreed to prohibit counting any carbon accumulation in plantations that substitute for native forests within countries’ voluntary commitments to REDD+.”

The new tool therefore represents a significant advancement toward understanding ecological changes that accompany changes in forest cover.

“This is the first map of forest change that is globally consistent and locally relevant,” said Hansen. “Losses or gains in forest cover shape many important aspects of an ecosystem including, climate regulation, carbon storage, biodiversity and water supplies, but until now there has not been a way to get detailed, accurate, satellite-based and readily available data on forest cover change from local to global scales.”



Regional subsets of 2000 tree cover and 2000 to 2012 forest loss and gain. (A) Paraguay, centered at 21.9°S, 59.8°W; (B) Indonesia, centered at 0.4°S, 101.5°E; (C) the United States, centered at 33.8°N, 93.3°W; and (D) Russia, centered at 62.1°N, 123.4°E. Image and caption courtesy of Science

The map wouldn’t have been possible without long-term collaboration between several institutions, including the University of Maryland, Google Inc, NASA, USGS, South Dakota State University, and the Woods Hole Research Center, among others. First touted publicly in 2008, the project has been in development nearly five years with significant financial support from the Gordon and Betty Moore Foundation.

Clarifying Google’s forest map



(11/18/2013) The forest map released last week by a team of remote-sensing experts has produced some confusion — and criticism — over exactly what it shows.

The project leverages the massive computing power of Google Earth Engine, which processed some 650,000 NASA Landsat images to map forest loss and gain. According to Google, a process that “would have taken a single computer 15 years to perform was completed in a matter of days.”

“By combining the extensive Landsat database with the computing power of Google Earth Engine, Dr. Hansen saw an opportunity to do something that had never been done before,” said Rebecca Moore, head of Google Earth Engine and Earth Outreach at Google. “To date, this is the largest-scale scientific application of Earth Engine technology to measurement and mapping of earth’s natural resources.”

Google Earth Engine is also being used by other forest scientists, at places like the Carnegie Institution and Brazil-based Imazon, for other forest monitoring and mapping applications. Improved understanding of the state of forests through tools like these should boost the ability of decision makers — from lawmakers to business leaders — to establish policies that better protect forests.

“Brazil used Landsat data to document its deforestation trends, then used this information in its policy formulation and implementation,” said Hansen. “Now, with our global mapping of forest changes every nation has access to this kind of information, for their own country and the rest of the world.”



Forest map showing deforestation in the Chaco ecosystem



Forest map showing historical deforestation in the Brazilian Amazon

CITATIONS:

Sandra Brown and Daniel Zarin. What Does Zero Deforestation Mean? SCIENCE VOL 342 15 NOVEMBER 2013

Matt Hansen et al. High-Resolution Global Maps of 21st-Century Forest Cover Change. SCIENCE VOL 342 15 NOVEMBER 2013

50 countries with largest forest loss, 2000-2012

(sq km)

country Forest loss Forest gain Net loss* Russia 365015 162292 202723 Brazil 360277 75866 284411 United States 263944 138082 125862 Canada 263943 91071 172872 Indonesia 157850 69701 88149 China 61130 22387 38743 DRCongo 58963 13926 45037 Australia 58736 14142 44594 Malaysia 47278 25798 21480 Argentina 46958 6430 40528 Paraguay 37958 510 37448 Bolivia 29867 1736 28131 Sweden 25533 15281 10252 Colombia 25193 5516 19677 Mexico 23862 6333 17529 Mozambique 21552 1446 20106 Tanzania 19903 3041 16862 Finland 19516 10849 8667 Angola 19320 638 18682 Peru 15288 1910 13378 Myanmar 14958 3149 11809 Cote d’Ivoire 14889 2298 12591 Madagascar 14659 4051 10608 Zambia 13163 181 12982 Venezuela 12958 1910 11048 Cambodia 12595 1096 11499 Vietnam 12289 5643 6646 Laos 12084 3379 8705 Thailand 12049 4992 7057 Chile 11879 14611 -2732 Nigeria 10239 603 9636 South Africa 9526 8313 1213 India 8971 2549 6422 Guatemala 8883 1094 7789 Nicaragua 8225 662 7563 France 7664 5062 2602 Spain 6908 4482 2426 New Zealand 6883 7102 -219 Papua New Guinea 6337 2308 4029 Philippines 6227 2726 3501 Poland 5829 5041 788 Ukraine 5657 3529 2128 Ghana 5406 1345 4061 Ecuador 5246 1027 4219 Portugal 4987 2866 2121 Germany 4890 2585 2305 Honduras 4860 582 4278 Cameroon 4816 651 4165 Mongolia 4779 103 4676 Central African Republic 4719 395 4324 Japan 4303 2570 1733 Belarus 4167 3755 412



* negative number represents net gain in forest cover.

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