文章基本信息

标题：High resolution paddy rice maps in cloud-prone Bangladesh and Northeast India using Sentinel-1 data
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作者：Mrinal Singha ; Jinwei Dong ; Geli Zhang 等
期刊名称：Scientific Data
电子版ISSN：2052-4463
出版年度：2019
卷号：6
DOI：10.1038/s41597-019-0036-3
语种：English
出版社：Nature Publishing Group
摘要：Knowledge of where, when, and how much paddy rice is planted is crucial information for understating of regional food security, freshwater use, climate change, and transmission of avian influenza virus. We developed seasonal paddy rice maps at high resolution (10m) for Bangladesh and Northeast India, typical cloud-prone regions in South Asia, using cloud-free Synthetic Aperture Radar (SAR) images from Sentinel-1 satellite, the Random Forest classifier, and the Google Earth Engine (GEE) cloud computing platform. The maps were provided for all the three distinct rice growing seasons of the region: Boro, Aus and Aman. The paddy rice maps were evaluated against the independent validation samples, and compared with the existing products from the International Rice Research Institute (IRRI) and the analysis of Moderate Resolution Imaging Spectroradiometer (MODIS) data. The generated paddy rice maps were spatially consistent with the compared maps and had a satisfactory accuracy over 90%. This study showed the potential of Sentinel-1 data and GEE on large scale paddy rice mapping in cloud-prone regions like tropical Asia.