Song, X.P., Potapov, P.V., Krylov, A., King, L., Di Bella, C.M., Hudson, A., Khan, A., Adusei, B., Stehman, S.V., Hansen, M.C. (2017) National-scale soybean mapping and area estimation in the United States using medium resolution satellite imagery and field survey. Remote Sensing of Environment, 190, 383-395.
Research Associate Professor
My primary research interest is assessing and monitoring forest extent, structure, and composition on national to global extent using open satellite data archives. I received my M.S. degree in botany in 2000 from Moscow State University (Russia), and Ph.D. degree in ecology and natural resources in 2005 from the Russian Academy of Science. I started my career as remote sensing data analyst in 1998 working for Greenpeace (Russian office). From 2004 to 2006, I was the head of the Greenpeace GIS lab, where we developed a number of methods for forest change and degradation monitoring. One of our products, the global Intact Forest Landscapes (IFL) map, has been widely used in regional and global forest monitoring projects, nature conservation campaigns and scientific research. The historic and updated IFL data are freely available online from our website www.intactforests.org. I moved to South Dakota State University in 2006, where I worked with Dr. Matthew Hansen on global forest monitoring project. The main data we employed before year 2008 was MODIS imagery products. Our MODIS-based forest cover change products for 2000-2005 are available online (http://glad.geog.umd.edu/projects/gfm/) and were used for a number of applications, including carbon accounting and protected areas assessment. Since the opening of the Landsat archive in 2008, my work is focused on Landsat data mass-processing and integration with MODIS and high spatial resolution data. Our research team moved to the University of Maryland in 2011. During recent years, my research has focused on establishing a global operational Landsat-based forest monitoring algorithm that enables rapid quantitative estimation of forest cover change and forest degradation. A number of products that are based on the methodology developed by our team have been published recently, including global forest change assessment (http://earthenginepartners.appspot.com/science-2013-global-forest), and regional forest dynamics products for Eastern Europe (http://glad.geog.umd.edu/europe/), Central Africa (http://congo.iluci.org/carpemapper/), and Indonesia (http://glad.geog.umd.edu/indonesia/data2014/).