Cross-Year Reuse of Historical Samples for Crop Mapping Based on Environmental Similarity
文献类型：期刊论文
| 作者 | Liu, Zhe4,5; Zhang, Lin4; Yu, Yaoqi4; Xi, Xiaojie4; Ren, Tianwei4; Zhao, Yuanyuan4,5; Zhu, Dehai4,5; Zhu, A-xing1,2,3,6 |
| 刊名 | FRONTIERS IN PLANT SCIENCE
 |
| 出版日期 | 2022-03-04 |
| 卷号 | 12页码:18 |
| 关键词 | crop classification historical samples environmental similarity generating samples remote sensing |
| ISSN号 | 1664-462X |
| DOI | 10.3389/fpls.2021.761148 |
| 通讯作者 | Liu, Zhe(liuz@cau.edu.cn) |
| 英文摘要 | Crop classification maps are fundamental data for global change research, regional agricultural regulation, fine production, and insurance services. The key to crop classification is samples, but it is very time-consuming in annual field sampling. Therefore, how to use historical samples in crop classification for future years at a lower cost is a research hotspot. By constructing the spectral feature vector of each historical sample in the historical year and its neighboring pixels in the target year, we produced new samples and classified them in the target year. Specifically, based on environmental similarity, we first calculated the similarities of every two pixels between each historical year and target year and took neighboring pixels with the highest local similarity as potential samples. Then, cluster analysis was performed on those potential samples of the same crop, and the class with more pixels is selected as newly generated samples for classification of the target year. The experiment in Heilongjiang province, China showed that this method can generate new samples with the uniform spatial distribution and that the proportion of various crops is consistent with field data in historical years. The overall accuracy of the target year by the newly generated sample and the real sample is 61.57 and 80.58%, respectively. The spatial pattern of maps obtained by two models is basically the same, and the classification based on the newly generated samples identified rice better. For areas with majority fields having no rotation, this method overcomes the problem of insufficient samples caused by difficulties in visual interpretation and high cost on field sampling, effectively improves the utilization rate of historical samples, and provides a new idea for crop mapping in areas lacking field samples of the target year. |
| WOS关键词 | RANDOM FOREST ; CLASSIFICATION ; SELECTION ; CLIMATE ; YIELD |
| 资助项目 | National Key Research and Development Program of China[2021YFE0205100] ; National Natural Science Foundation of China[41871300] ; Fundamental Research Funds of China Agricultural University[2021TC023] |
| WOS研究方向 | Plant Sciences |
| 语种 | 英语 |
| WOS记录号 | WOS:000772592100001 |
| 出版者 | FRONTIERS MEDIA SA |
| 资助机构 | National Key Research and Development Program of China ; National Natural Science Foundation of China ; Fundamental Research Funds of China Agricultural University |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/172531]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Liu, Zhe |
| 作者单位 | 1.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China 3.Univ Wisconsin, Dept Geog, Madison, WI 53706 USA 4.China Agr Univ, Coll Land Sci & Technol, Beijing, Peoples R China 5.Minist Agr & Rural Affairs, Key Lab Remote Sensing Agri Hazards, Beijing, Peoples R China 6.Nanjing Normal Univ, Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Key Lab Virtual Geog Environm, Minist Educ,Sch Geog, Nanjing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liu, Zhe,Zhang, Lin,Yu, Yaoqi,et al. Cross-Year Reuse of Historical Samples for Crop Mapping Based on Environmental Similarity[J]. FRONTIERS IN PLANT SCIENCE,2022,12:18. |
| APA | Liu, Zhe.,Zhang, Lin.,Yu, Yaoqi.,Xi, Xiaojie.,Ren, Tianwei.,...&Zhu, A-xing.(2022).Cross-Year Reuse of Historical Samples for Crop Mapping Based on Environmental Similarity.FRONTIERS IN PLANT SCIENCE,12,18. |
| MLA | Liu, Zhe,et al."Cross-Year Reuse of Historical Samples for Crop Mapping Based on Environmental Similarity".FRONTIERS IN PLANT SCIENCE 12(2022):18. |
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。