Abstract
Remote sensing based monitoring of deforestation in the tropics is crucial to better understand global land use change and related changes in ecosystem service provision and to inform governments and civil society on the effectiveness their forest protection policies. In Brazil, deforestation has been closely coupled to the expansion of grazing and cropping systems primarily in the tropical forest, but no spatially explicit high resolution database on deforestation exists that captures tropical forest clearing prior to 2000. The open Landsat archive provides >45 years of imagery and is well suited for wall-to-wall assessments of historic deforestation dynamics which are valuable to policy development and environmental impact assessments. Image analysis procedures for reconstructing long-term deforestation dynamics over large areas need to cope with regions and time periods for which the archive contains heterogeneous data densities on a yearly and decadal basis. We create for the first time yearly 30 m maps of long term, annual deforestation dynamics (LTAD) covering the period from 1984 to 2014 for Pará and Mato Grosso, two Brazilian federal states that cover much of the Brazilian arc-of-deforestation. Our results provide valuable insights into historic deforestation trends, with annually increasing deforestation from 1990 to 1999 for both Pará and Mato Grosso. Peak deforestation occurred in 2004 after which deforestation leveled off – with a more pronounced decrease in Mato Grosso than in Pará. Contrary to Mato Grosso, Pará again experienced increasing annual forest clearing in recent years. For the time period after 2000, we provide an in-depth comparison with two widely used products, the Brazilian PRODES and the Global Forest Change maps (GFC, Hansen et al., 2013). Our deforestation estimates (407,000 ± 42,000 km2 at 95% confidence level) are above those provided by PRODES, while GFC results are closer to our estimates for the comparison period. Recent PRODES estimates are consistently below our and the GFC results. Overall, our results exemplify the potential of open image archives for multi-decadal, wall-to-wall and fine grain reconstruction of forest change. The presented approach prototypes similar assessments of tropical forest dynamics globally faced with issues of data scarcity.
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