物候学
水田
增强植被指数
洪水(心理学)
植被(病理学)
环境科学
植被指数
遥感
水文学(农业)
归一化差异植被指数
数学
林业
农学
地理
叶面积指数
生物
地质学
医学
心理学
岩土工程
病理
心理治疗师
作者
Peng Li,Chiwei Xiao,Zhiming Feng
标识
DOI:10.1109/lgrs.2018.2865516
摘要
Obtaining annually updated data of actually planted rice paddy is essential for evaluating food security and estimating methane emission. Paddy field in southern China generally displays unique phenological landscape changes from exposed soils, shallow flooding water, to rice plants during the whole growth period in a year. A phenology-based algorithm was developed to map the rice planted paddies in the Poyang Lake Plain (PLP), China, in 2014, a typical region in Central China single- and double-rice cropping belt. This algorithm, or a normalized vegetation index, was based on the normalization of Landsat-8 Operational Land Imager-derived enhanced vegetation index and soil-adjusted vegetation index. It highlighted the temporal differences in vegetation cover and background soil between two critical growth phases of paddy rice, i.e., the flooding to transplanting stage and reproductive to ripening stage. There was estimated to be 7148.31 km 2 in the PLP, with an overall accuracy of 96.8% and the kappa coefficient of 0.97. Comparison between Landsat-detected results and the statistics of paddy field at the county level showed a high determination coefficient with the $R^{2}$ of 0.88. The phenology-based algorithm greatly facilitates rice farming monitoring at the regional scale.
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