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CLASSIFICATION OF CULTIVATED RICE FIELDS IN NORTHERN VIETNAM USING POLARIMETRIC RADARSAT-2 DATA

机译:越南北部栽培稻田的分类偏振雷达拉特2数据

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This paper presents two classification schemes to identify rice fields in a complex land-use watershed in northern Vietnam: Thresholding and Support Vector Machine (SVM) classification algorithm. The data used are C-band dual-polarization (HH, HV) and polarimetric (quad-pol) data from RADARSAT-2. Two questions are posed: firstly, what is the usefulness of different polarizations (HH and HV) for rice detection? Secondly, between different polarimetric parameters, which ones are the most suitable to separate the rice fields from others? The analysis shows that the rice intensity values increase in the middle of the crop season and are different from other vegetation types in HH polarization. In parallel, the coherence (T) matrix seems a suitable polarimetric parameter for rice extraction. Results suggest that both HH polarization intensity values and quad-pol data could identify rice fields at regional scale with a precision of 71% and 80%.
机译:本文提出了两个分类方案,用于识别越南北部的复杂土地水域中的稻田:阈值和支持向量机(SVM)分类算法。所使用的数据是来自Radarsat-2的C波段双极化(HH,HV)和偏振(四极管)数据。提出了两个问题:首先,不同偏振(HH和HV)对水稻检测的有用性是什么?其次,在不同的偏振参数之间,哪些是最适合从其他人分离稻田?分析表明,水稻强度值在作物季节中间增加,与HH极化中的其他植被类型不同。并行地,相干(T)基质似乎是水稻提取的合适偏振参数。结果表明,HH偏振强度值和四极管数据都可以以71%和80%的精度识别区域规模的稻田。

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