A Decision-Tree Approach to Identifying Paddy Rice Lodging with Multiple Pieces of Polarization Information Derived from Sentinel-1
文献类型：期刊论文
| 作者 | Dai, Xuemei3,4,5; Chen, Shuisen2,4; Jia, Kai2,4; Jiang, Hao4; Sun, Yishan4; Li, Dan4; Zheng, Qiong1,4; Huang, Jianxi6 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2023 |
| 卷号 | 15期号:1页码:19 |
| 关键词 | paddy rice lodging remote sensing SAR backscattering coefficient polarization decomposition decision tree disaster |
| DOI | 10.3390/rs15010240 |
| 英文摘要 | Lodging is one of the typical abiotic adversities during paddy rice growth. In addition to affecting photosynthesis, it can seriously damage crop growth and development, such as reducing rice quality and hindering automated harvesting. It is, therefore, imperative to accurately and in good time acquire crop-lodging areas for yield prediction, agricultural insurance claims, and disaster-management decisions. However, the accuracy requirements for crop-lodging monitoring remain challenging due to complicated impact factors. Aiming at identifying paddy rice lodging on Shazai Island, Guangdong, China, caused by heavy rainfall and strong wind, a decision-tree model was constructed using multiple-parameter information from Sentinel-1 SAR images and the in situ lodging samples. The model innovatively combined the five backscattering coefficients with five polarization decomposition parameters and quantified the importance of each parameter feature. It was found that the decision-tree method coupled with polarization decomposition can be used to obtain an accurate distribution of paddy rice-lodging areas. The results showed that: (1) Radar parameters can capture the changes in lodged paddy rice. The radar parameters that best distinguish paddy rice lodging are VV, VV+VH, VH/VV, and Span. (2) Span is the parameter with the strongest feature importance, which shows the necessity of adding polarization parameters to the classification model. (3) The dual-polarized Sentinel-1 database classification model can effectively extract the area of lodging paddy rice with an overall accuracy of 84.38%, and a total area precision of 93.18%. These observations can guide the future use of SAR-based information for crop-lodging assessment and post-disaster management. |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000909244000001 |
| 源URL | [http://ir.gig.ac.cn/handle/344008/71578]  |
| 专题 | 中国科学院广州地球化学研究所 |
| 通讯作者 | Chen, Shuisen |
| 作者单位 | 1.Changsha Univ Sci & Technol, Sch Traff & Transportat Engn, Dept Geomat Engn, Changsha 410114, Peoples R China 2.Guangdong Acad Sci, Guangzhou Inst Geog, Guangzhou 510070, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 4.Guangdong Acad Sci, Guangzhou Inst Geog, Guangdong Engn Technol Res Ctr Remote Sensing Big, Guangdong Prov Key Lab Remote Sensing & Geog Infor, Guangzhou 510070, Peoples R China 5.Chinese Acad Sci, Guangzhou Inst Geochem, Guangzhou 510640, Peoples R China 6.China Agr Univ, Coll Land Sci & Technol, Beijing 100083, Peoples R China |
| 推荐引用方式 GB/T 7714 | Dai, Xuemei,Chen, Shuisen,Jia, Kai,et al. A Decision-Tree Approach to Identifying Paddy Rice Lodging with Multiple Pieces of Polarization Information Derived from Sentinel-1[J]. REMOTE SENSING,2023,15(1):19. |
| APA | Dai, Xuemei.,Chen, Shuisen.,Jia, Kai.,Jiang, Hao.,Sun, Yishan.,...&Huang, Jianxi.(2023).A Decision-Tree Approach to Identifying Paddy Rice Lodging with Multiple Pieces of Polarization Information Derived from Sentinel-1.REMOTE SENSING,15(1),19. |
| MLA | Dai, Xuemei,et al."A Decision-Tree Approach to Identifying Paddy Rice Lodging with Multiple Pieces of Polarization Information Derived from Sentinel-1".REMOTE SENSING 15.1(2023):19. |
入库方式： OAI收割
来源：广州地球化学研究所
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