Mapping paddy rice using Landsat time series data in the Ganfu Plain irrigation system, Southern China, from 1988−2017

作者：Jingjing Cao, Xueliang Cai, Junwei Tan, Yuanlai Cui, Hengwang Xie, Liu FangPing, Lin Yang, Yufeng Luo · 发表于：International Journal of Remote Sensing · 年份：2020 · DOI：10.1080/01431161.2020.1841321 · 被引用次数：43 · 研究领域：Remote Sensing in Agriculture、Remote Sensing and Land Use、Land Use and Ecosystem Services

The spatial pattern and temporal variation of paddy rice fields based on remote sensing have strong effects on the allocation of agricultural water resources on a regional scale. Free Land Remote-Sensing Satellite (Landsat) data have been successfully used to map paddy rice. However, due to frequent clouds and a temporal gap of 16 days, the shortage of Landsat data availability poses a great challenge to long-term paddy rice mapping. This study proposed a decision tree algorithm based on the Enhanced Vegetation Index (EVI) to map multi-season paddy rice in southern China. The study area is located in the Ganfu Plain Irrigation System (GFPIS), where double-cropping rice (early and late rice) and single-cropping rice (middle rice) are mixed. First, we explored the effects of the number and temporal distribution of Landsat images on the classification accuracy. With available cloud-free images in 2017, ten image combinations were set up to map rice fields using the proposed algorithm separately. Then, the algorithm was applied to map historical paddy rice planting in this study area. The results indicated that with a cropland mask, a single-date image in early rice growing season can map the total early rice with an overall accuracy varying from 82.02% to 93.26%, and the accuracy was mainly influenced by the temporal distribution of the images. In addition, through post-processing, multi-temporal images could be used to recognize early rice only, late rice only, double-cropping ...