Study on the Method of Recognizing Abandoned Farmlands Based on Multispectral Remote Sensing
CHENG Wei-fang1,2, ZHOU Yi1*, WANG Shi-xin1, HAN Yu1，2, WANG Fu-tao1,2, PU Qing-yang3
1. The State Key Laboratory of Remote Sensing Science，Institute of Remote Sensing Application, Chinese Academy of Sciences, Beijing 100101, China 2. Graduate University of Chinese Academy of sciences, Beijing 100049, China 3. The Affiliated High School of the Institute of Steel and Iron Beijing, Beijing 100083
Abstract：Being abandoned for farmland seriously affected China’s grain output for farmlands. It has become an important phenomenon over the past 20 years in China. Multispectral remote sensing has the advantage of wide range and high speed in requiring data. It has great potential in the research on land use. Therefore, to extract abandoned farmland in China, the authors’ used the NDVI data of Modis/Terra from 2000 to 2009 which is one of multispectral remote sensing data and the Remote Sensing Image of ALOS satellite in Japan. The authors’ used the parameter of NDVI of time series to describe the character of the main land use types. After drawing the time-series curves of the main land use type samples, the authors’ analyzed them with consulting the life character of these types. Then, the authors’ compared these curves; finally we recognized abandoned farmland from the others. At last the authors’ went to experimental plot to survey the land use. The results demonstrated that the method of using multispectral remote sensing data can abstract abandoned farmland and classify the main kind of land use, and the accuracy is as high as 90%. So the method is feasible in recognizing abandoned farmland.
程维芳1,2, 周 艺1*，王世新1, 韩 昱1,2, 王福涛1,2，浦青阳3 . 基于多光谱遥感的撂荒地识别方法研究[J]. 光谱学与光谱分析, 2011, 31(06): 1615-1620.
CHENG Wei-fang1,2, ZHOU Yi1*, WANG Shi-xin1, HAN Yu1，2, WANG Fu-tao1,2, PU Qing-yang3 . Study on the Method of Recognizing Abandoned Farmlands Based on Multispectral Remote Sensing. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2011, 31(06): 1615-1620.
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