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Gutierrez-Velez, VH; DeFries, R (2013). Annual multi-resolution detection of land cover conversion to oil palm in the Peruvian Amazon. REMOTE SENSING OF ENVIRONMENT, 129, 154-167.

Oil palm expansion is a major threat to forest conservation in the tropics. Oil palm can also be a sustainable economic alternative if incentives for expansion outside forests are set in place. Consistent methods to monitor the time and location of oil palm expansion and the area converted from different land covers are essential for the success of such incentives. We developed methods to detect and quantify annual land cover changes associated with oil palm expansion in the Peruvian Amazon between 2001 and 2010 at two spatial scales and for two production modes. At the coarse scale, comprising the whole Peruvian Amazon, we used MODIS data to detect forest conversion to large-scale, industrial oil palm plantations based on metrics characterizing temporal changes in vegetation greenness associated with the conversion. At the fine scale, we used data from the satellite sensors Landsat TM/ETM + and ALOS-PALSAR to map and quantify the area from different land covers converted into large and small-scale oil palm plantations annually, in a focus area near the city of Pucallpa. Estimates were obtained from the elaboration and further combination of maps representing oil palm plantations by ages in 2010 and non-oil palm land covers in each year between 2001 and 2010. Validation data were obtained in the field and from geospatial information from previous studies. At the coarse scale, MODIS detected deforestation in 73% of training events larger than 50 ha. Detected events added up to 95% of the training areas. Total area converted to oil palm annually was quantified visually by using data from Landsat TM/ETM + with 96.3% accuracy. At the fine scale, the combination of data from Landsat TM/ETM + and ALOS-PALSAR identified oil palm expansion in areas larger than 5 ha with 94% accuracy and the year of expansion with an uncertainty of +/- 1.3 years. This work underscores the need for data from multiple satellite sensors for a comprehensive monitoring of oil palm expansion, considering needs for information not only on the area expanded but also the time of conversion and land cover transitions associated with large- and small-scale plantations. (C) 2012 Elsevier Inc. All rights reserved.



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