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Study on Extraction of Paddy Rice Planting Area in Low Fragmented Regions based on GF-1 WFV Images |
Haidong Zhang1(),Ting Tian1,Qing Zhang1(),Zhou Lu2,Chunlin Shi3,Changwei Tan4,Ming Luo4,Chunhua Qian5 |
1. Institute of Agricultural Sciences in Taihu Area of Jiangsu,Suzhou 215155,China 2. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy Sciences, Beijing 100101, China 3. Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China 4. Yangzhou University, Yangzhou 225009, China, 5. Suzhou Polytechnic Institute of Agriculture,Suzhou 215008, China 5. Suzhou Polytechnic Institute of Agriculture,Suzhou 215008,China |
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Abstract The extraction of paddy rice planting area in low fragmented regions based on remote sensing images is a hotspot in crop monitoring. Taking Gaoxin district of Suzhou city in Taihu Lake region as a case study, the rice and underlying water spectral characteristics in critical phenophase were studied in-depth to reduce the demand of remote sensing images, and only two GF-1 WFV images with resolution of 16 m during rice tillering and full heading stages were employed to extract the paddy rice planting area. Two vegetation index methods, including difference of Normalized Differential Vegetation Index (NDVI) and the combination of difference of Normalized Differential Water Index (NDWI) and Ratio Vegetation Index (RVI) were studied. The results suggested that both the methods effectively promoted the extraction precision, comparing with the results of supervised classification and unsupervised classification methods. The area recognition accuracy, space consistency mapping accuracy and kappa coefficient of NDVI method were 86.2%, 66.1%, 92.2% and 0.72, while those of NDWI-RVI method were up to 95.5%, 78.4%, 93.5% and 0.85, respectively. The two methods realized the purpose of accurately extracting rice area in low fragmented regions by using a few medium and high resolution remote sensing images, and can be effectively serviced for actual production and relevant decision support in Taihu Lake region.
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Received: 21 August 2018
Published: 16 October 2019
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Corresponding Authors:
Qing Zhang
E-mail: zhdsznky@163.com;qzhangsaas@163.com
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