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Rice growth monitoring using simulated compact polarimetric C band SAR

文献类型： 外文期刊

作者： Yang, Zhi 1 ; Li, Kun 1 ; Liu, Long 1 ; Shao, Yun 1 ; Brisco, Brian 3 ; Li, Weiguo 4 ;

作者机构： 1.Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Beijing, Peoples R China

2.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing, Peoples R China

3.Nat Resources Canada, Canada Ctr Mapping & Earth Observat, Ottawa, ON, Canada

4.Jiangsu Acad Agr Sci, Nanjing, Jiangsu, Peoples R China

关键词： rice;compact polarimetry;SAR;growth monitoring;phenology retrieval;decision tree classifier

期刊名称：RADIO SCIENCE （ 影响因子：1.431； 五年影响因子：1.541 ）

ISSN： 0048-6604

年卷期： 2014 年 49 卷 12 期

页码：

收录情况： SCI

摘要： In this study, a set of nine compact polarimetric (CP) images were simulated from polarimetric RADARSAT-2 data acquired over a test site containing two types of rice field in Jiangsu province, China. The types of rice field in the test site were (1) transplanted hybrid rice fields, and (2) direct-sown japonica rice fields. Both types have different yields and phenological stages. As a first step, the two types of rice field were distinguished with 94% and 86% accuracy respectively through analyzing CP synthetic aperture radar (SAR) observations and their behavior in terms of scattering mechanisms during the rice growth season. The focus was then on phenology retrieval for each type of rice field. A decision tree (DT) algorithm was built to fulfill the precise retrieval of rice phenological stages, in which seven phenological stages were discriminated. The key criterion for each phenological stage was composed of 1-4 CP parameters, some of which were first used for rice phenology retrieval and found to be very sensitive to rice phenological changes. The retrieval results were verified at parcel level for a set of 12 stands of rice and up to nine observation dates per stand. This gave an accuracy of 88-95%. Throughout the phenology retrieval process, only simulated CP data were used, without any auxiliary data. These results demonstrate the potential of CP SAR for rice growth monitoring applications.

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