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Remote Sens. 2016, 8(5), 434;

Mapping Paddy Rice in China in 2002, 2005, 2010 and 2014 with MODIS Time Series

Department of Remote Sensing, Institute of Geography and Geology, University of Wuerzburg, Oswald-Kuelpe-Weg 86, D-97074 Wuerzburg, Germany
Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, 100101 Beijing, China
German Remote Sensing Data Center (DFD), Earth Observation Center (EOC), German Aerospace Center (DLR), Oberpfaffenhofen, D-82234 Wessling, Germany
Author to whom correspondence should be addressed.
Academic Editors: Anton Vrieling, Yoshio Inoue and Prasad S. Thenkabail
Received: 4 March 2016 / Revised: 3 May 2016 / Accepted: 9 May 2016 / Published: 23 May 2016
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Rice is an important food crop and a large producer of green-house relevant methane. Accurate and timely maps of paddy fields are most important in the context of food security and greenhouse gas emission modelling. During their life-cycle, rice plants undergo a phenological development that influences their interaction with waves in the visible light and infrared spectrum. Rice growth has a distinctive signature in time series of remotely-sensed data. We used time series of MODIS (Moderate Resolution Imaging Spectroradiometer) products MOD13Q1 and MYD13Q1 and a one-class support vector machine to detect these signatures and classify paddy rice areas in continental China. Based on these classifications, we present a novel product for continental China that shows rice areas for the years 2002, 2005, 2010 and 2014 at 250-m resolution. Our classification has an overall accuracy of 0.90 and a kappa coefficient of 0.77 compared to our own reference dataset for 2014 and correlates highly with rice area statistics from China’s Statistical Yearbooks (R2 of 0.92 for 2010, 0.92 for 2005 and 0.90 for 2002). Moderate resolution time series analysis allows accurate and timely mapping of rice paddies over large areas with diverse cropping schemes. View Full-Text
Keywords: rice; China; MODIS; time series; SVM; OCSVM; agriculture; change detection rice; China; MODIS; time series; SVM; OCSVM; agriculture; change detection

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Clauss, K.; Yan, H.; Kuenzer, C. Mapping Paddy Rice in China in 2002, 2005, 2010 and 2014 with MODIS Time Series. Remote Sens. 2016, 8, 434.

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