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Establishing a Global Forest Monitoring Capability Using Multi-Resolution and Multi-Temporal Remotely Sensed Data Sets
Project Start Date
01/01/2005
Project End Date
01/01/2008
Project Call Name
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Solicitation
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Team Members:

Person Name Person role on project Affiliation
Matthew Hansen Principal Investigator University of Maryland, College Park, College Park, United States
Abstract

Quantifying rates of forest-cover change is important for improved carbon accounting and climate change modeling, management of forestry and agricultural resources, and biodiversity monitoring. A practical solution to examining trends in forest cover change at global scale is to employ remotely sensed data. Satellite-based monitoring of forest cover can be implemented consistently across large regions at annual and inter-annual intervals. This research extends previous research on global forest cover dynamics and land-cover change estimation to establish a robust, operational forest monitoring and assessment system. The approach integrates both MODIS and Landsat data to provide timely biome scale forest change estimation. This is achieved by using annual MODIS change indicator maps to stratify biomes into low, medium and high change categories. Landsat image pairs can then be sampled within these strata and analyzed for estimating area of forest cleared. Results for the humid tropics reveal that 27.2 million hectares of forest were cleared from 2000 to 2005, with nearly 50% of this change occurring in Brazil. Indonesia was a distant second in forest loss, accounting for 12% of the biome total. The approach enables regional intercomparisons such as these and can be implemented repeatedly over time in a monitoring context. For example, a national-scale study of Indonesia using the method with AVHRR forest loss indicator maps and Landsat sample blocks for the 1990 to 2000 epoch estimated average clearing to be 1.78 million hectares. Clearing from 2000 to 2005 averaged 0.71 million hectares per year. This dramatic downturn may be related to the drivers of forest clearing having changed at the turn of the century, including political and social upheaval, an economic downturn, and the occurrence of widespread, human-induced fire during the ENSO event of 1997 and 1998. Boreal forest clearing from 2000 to 2005 actually exceeded that of the humid tropics, totaling 35.1 million hectares. The proportion of year 2000 forest lost was 4.02%, compared to 2.36% for the humid tropics. In the boreal biome, fire is a major cause of forest cover loss and was estimated to account for nearly 60% of the total. As a percent of year 2000 forest cover, forest loss in North America was nearly twice that of Eurasia (5.63% to 3.00%). Overall, the method enables global, biome and targeted national/regional-scale quantification of forest cover change. The method requires less effort than exhaustive mapping approaches, includes a measure of uncertainty, and through regression estimation, provides a spatial depiction of the estimated change.