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Improved phenology-based rice mapping algorithm by integrating optical and radar data

文献类型：期刊论文

作者Zhao, Zizhang5,6; Dong, Jinwei4,5; Zhang, Geli6; Yang, Jilin3; Liu, Ruoqi6; Wu, Bingfang2; Xiao, Xiangming1
刊名REMOTE SENSING OF ENVIRONMENT
出版日期2024-12-15
卷号315页码:114460
关键词Rice mapping Phenology-based method Rice transplanting phase Sentinel-1 Sentinel-2
DOI10.1016/j.rse.2024.114460
产权排序2
英文摘要Information on rice planting areas is critically important for food and water security, as well as for adapting to climate change. Mapping rice globally remains challenging due to the diverse climatic conditions and various rice cropping systems worldwide. Synthetic Aperture Radar (SAR) data, which is immune to climatic conditions, plays a vital role in rice mapping in cloudy, rainy, low-latitude regions but it suffers from commission errors in high-latitude regions. Conversely, optical data performs well in high-latitude regions due to its high observation frequency and less cloud contamination but faces significant omission errors in low-latitude regions. An effective integrated method that combines both data types is key to global rice mapping. Here, we propose a novel adaptive rice mapping framework named Rice-Sentinel that combines Sentinel-1 and Sentinel-2 data. First, we extracted key phenological phases of rice (e.g., the flooding and transplanting phase and the rapid growth phase), by analyzing the characteristic V-shaped changes in the Sentinel-1 VH curve. Second, we identified potential flooding signals in rice pixels by integrating the VH time series from Sentinel-1 with the Land Surface Water Index (LSWI) and Enhanced Vegetation Index (EVI) from Sentinel-2, utilizing the generated phenology phases. Third, the rapid growth signals of rice following its flooding phase were identified using Sentinel-2 data. Finally, rice fields were identified by integrating flooding and rapid growth signals. The resultant rice maps in six different case regions of the world (Northeast and South China, California, USA, Mekong Delta of Vietnam, Sakata City in Japan, and Mali in Africa) showed overall accuracies over 90 % and F1 scores over 0.91, outperforming the existing methods and products. This algorithm combines the strengths of both optical and SAR time series data and leverages biophysical principles to generate robust rice maps without relying on any prior ground truth samples. It is well-positioned for global applications and is expected to contribute to global rice monitoring efforts.
WOS关键词PADDY RICE ; TIME-SERIES ; SOUTHEAST-ASIA ; LANDSAT IMAGES ; PLANTING AREA ; CHINA ; NORTHEAST ; AGRICULTURE ; INFORMATION ; CAPABILITY
WOS研究方向Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号WOS:001333236700001
源URL[http://ir.igsnrr.ac.cn/handle/311030/208241]  
专题陆地表层格局与模拟院重点实验室_外文论文
通讯作者Dong, Jinwei
作者单位1.Univ Oklahoma, Sch Biol Sci, Norman, OK 73019 USA
2.Chinese Acad Sci, Aerosp Informat Res Inst, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
3.China Agr Univ, Coll Grassland Sci & Technol, Beijing 100193, Peoples R China
4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
5.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
6.China Agr Univ, Coll Land Sci & Technol, Beijing 100193, Peoples R China
推荐引用方式
GB/T 7714		 Zhao, Zizhang,Dong, Jinwei,Zhang, Geli,et al. Improved phenology-based rice mapping algorithm by integrating optical and radar data[J]. REMOTE SENSING OF ENVIRONMENT,2024,315:114460.
APA Zhao, Zizhang.,Dong, Jinwei.,Zhang, Geli.,Yang, Jilin.,Liu, Ruoqi.,...&Xiao, Xiangming.(2024).Improved phenology-based rice mapping algorithm by integrating optical and radar data.REMOTE SENSING OF ENVIRONMENT,315,114460.
MLA Zhao, Zizhang,et al."Improved phenology-based rice mapping algorithm by integrating optical and radar data".REMOTE SENSING OF ENVIRONMENT 315(2024):114460.

入库方式： OAI收割

来源：地理科学与资源研究所

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