Tracking paddy rice acreage, flooding impacts, and mitigations during El Nino flooding events using Sentinel-1/2 imagery and cloud computing
文献类型：期刊论文
| 作者 | Liu, Ruoqi; Dong, Jinwei5; Ge, Yong4,5; Lin, Hui4; Che, Xianghong3; Di, Yuanyuan5; Chen, Xi5; Qi, Shuhua4; Ding, Mingjun4; Xiao, Xiangming2 |
| 刊名 | ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
 |
| 出版日期 | 2024-11-01 |
| 卷号 | 217页码:165-178 |
| 关键词 | In-season rice mapping Flood mapping Post-flood rice replanting Extreme weather Agricultural mitigation |
| DOI | 10.1016/j.isprsjprs.2024.08.010 |
| 产权排序 | 2 |
| 文献子类 | Article |
| 英文摘要 | The frequent occurrence of El Nino events, in the context of climate change, brings heavy precipitation and extreme heat, severely disrupting agricultural production. Previous efforts have focused on monitoring crop planting areas and evaluating affected crops during disasters. Nevertheless, a comprehensive analysis, including crop planting area mapping, crop damage assessment, and mitigation effectiveness throughout the entire course of a disaster, has been seldom addressed. In this study, we built a comprehensive framework to rapidly investigate the areas of early rice, the extent of flooding impacts, and the post-flood mitigations of early rice during the El Nino flooding event in a typical rice production region - Jiangxi Province in 2023. Early rice planting areas were first mapped by integrating 15-day time series gap-filled Sentinel-1/2 datasets using the Google Earth Engine (GEE) platform, based on a random forest classifier built with the 55 optimized training features. Then the flood-affected early rice map was produced by integrating the early rice planting areas and the Sentinel-1 images-based flood map. Finally, the post-flood newly planted rice fields were identified using the random forest algorithm and classification features from the Sentinel-1/2 images composited during four phenology phases of newly planted rice. The results showed the early rice planting area map, the flooding map, and the newly planted early rice map have overall accuracies of over 90 %. The early rice planting areas reached 120 x 104 ha, and an area of 3.60 x 104 ha (3 %) was flooded due to the heavy rain, and 3.43 x 104 ha flooded areas were newly planted, eventually mitigating the flooding impacts on the production of early rice. This study showcases the potential of all the available Sentinel-1/2 data, cloud computing, and well-established mapping algorithms for tracking rice areas, flooding impacts, and mitigations (i.e., after-flooding replanting) during extreme climate events. The established framework is expected to serve as an early warning system for agricultural adaptation to extreme climate events. |
| WOS关键词 | TIME-SERIES ; LANDSAT ; AREAS ; DYNAMICS ; INDEX |
| WOS研究方向 | Physical Geography ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| WOS记录号 | WOS:001311314400001 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/207934]  |
| 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, Dept Microbiol & Plant Biol, Norman, OK 73019 USA 2.Chinese Acad Surveying & Mapping, Res Ctr Geospatial Big Data Applicat, Beijing, Peoples R China 3.Jiangxi Normal Univ, Sch Geog & Environm, Key Lab Poyang Lake Wetland & Watershed Res, Minist Educ, Nanchang 330022, Peoples R China 4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 5.China Agr Univ, Coll Land Sci & Technol, Beijing 100193, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liu, Ruoqi,Dong, Jinwei,Ge, Yong,et al. Tracking paddy rice acreage, flooding impacts, and mitigations during El Nino flooding events using Sentinel-1/2 imagery and cloud computing[J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,2024,217:165-178. |
| APA | Liu, Ruoqi.,Dong, Jinwei.,Ge, Yong.,Lin, Hui.,Che, Xianghong.,...&Zhang, Geli.(2024).Tracking paddy rice acreage, flooding impacts, and mitigations during El Nino flooding events using Sentinel-1/2 imagery and cloud computing.ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,217,165-178. |
| MLA | Liu, Ruoqi,et al."Tracking paddy rice acreage, flooding impacts, and mitigations during El Nino flooding events using Sentinel-1/2 imagery and cloud computing".ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 217(2024):165-178. |
入库方式： OAI收割
来源：地理科学与资源研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。