JIA-2019-11

2641 ZHANG Xi-wang et al. Journal of Integrative Agriculture 2019, 18(11): 2628–2643 derived from key temporal change features of time series MODIS NDVI is combined with the membership derived from spectral information of Landsat TM. In addition, the separability of targets is improved by narrowing the discriminant space. Specifically, the proposed method identifies winter wheat in a matrix of 10×10 pixels by comparing membership values. The result revealed that Aa andAs were 93.01 and 91.40%, respectively. These results are significantly higher than those obtained MLC and RFC using the same images. This study demonstrates the feasibility of improving identification accuracy by adding temporal information and limiting the size of the discriminant space. Furthermore, it also provides a new perspective and enriches research ideas for crop-type identification and acreage estimation using multi-source remote sensing data. Acknowledgements We acknowledge the financial support provided by the National Science & Technology Infrastructure Construction Project of China (2005DKA32300), the Key Science and Technology Project of Henan Province, China (152102110047), the Major Research Project of the Ministry of Education, China(16JJD770019), the Major Scientific and Technological Special Project of Henan Province, China (121100111300), and the Cooperation Base Open Fund of the Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River regions and CPGIS (JOF 201602). We also appreciate the helps and suggestions fromProf. Qiu Fang fromUniversity of Texas at Dallas. We especially thank the anonymous reviewers for their constructive comments and insightful suggestions that greatly improved the quality of this manuscript. References Aguilar C, Zinnert J C, Polo M J, Young D R. 2012. NDVI as an indicator for changes in water availability to woody vegetation. Ecological Indicators , 23 , 290–300. 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