Evaluation of Winter Wheat Yield Simulation Based on Assimilating LAI Retrieved From Networked Optical and SAR Remotely Sensed Images Into the WOFOST Model
文献类型：期刊论文
| 作者 | Wu, Shangrong1; Ren, Jianqiang1; Chen, Zhongxin1; Yang, Peng1; Li, He2; Liu, Jia1 |
| 刊名 | IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
 |
| 出版日期 | 2021-11-01 |
| 卷号 | 59期号:11页码:9071-9085 |
| ISSN号 | 0196-2892 |
| 关键词 | Agriculture Remote sensing Synthetic aperture radar Optical sensors Optical imaging Data models Yield estimation Crop growth model data assimilation leaf area index (LAI) synthetic aperture radar (SAR) winter wheat yield simulation |
| DOI | 10.1109/TGRS.2020.3038205 |
| 通讯作者 | Chen, Zhongxin(chenzhongxin@caas.cn) ; Yang, Peng(yangpeng@caas.cn) |
| 英文摘要 | To obtain sufficient observation data and simulate higher-precision crop yields, a crop yield simulation scheme was built based on the WOrld FOod STudies (WOFOST) crop growth model and a 4-D ensemble square root filter (4-DEnSRF) assimilation algorithm, and the time series of the leaf area index (LAI) retrieved by optical and synthetic aperture radar (SAR) networking data was introduced into the crop yield estimation scheme. Taking Shenzhou County, Hebei Province, as the study area, using the field-measured data as verification data, the regional application of winter wheat yield estimation was effectively carried out with a grid size of 500 m. Comparisons were made between the simulated yields based on different networked data of three key phenologies of winter wheat. The regional yield estimation results revealed an R-2 and normalized root mean squared error (NRMSE) between the simulated yield based on optical LAIs and the field-measured yield of 0.517 and 17.60%, respectively, while the R-2 and NRMSE between the simulated yield based on networked optical-SAR LAIs filtered by the Gaussian filtering algorithm (GFA) and the field-measured yield were 0.573 and 12.98%, respectively. From the comparisons between the simulated yields based on networked data of different combinations of key phenologies, the R-2 and NRMSE between the simulated yield based on the introduced SAR LAI at the jointing stage and the field-measured yield were 0.437 and 21.49%, respectively, and were higher correlation among the three modes of networked data of different combinations of key phenologies. The winter wheat yield simulation results showed that the introduction of SAR LAIs at key crop growth stages (especially the jointing and booting stage) as outer observation data had a mild impact on the value of simulated winter wheat yield. Moreover, Gaussian filtering could reduce errors caused by multisource networked data to a certain extent. Thus, it can be concluded that using some radar images instead of optical images to retrieve LAI and assimilating multisource remotely sensed LAI into the crop model to simulate crop yield could enhance the reliability and robustness of the crop yield simulation system to some extent. |
| WOS关键词 | LEAF-AREA INDEX ; CROP GROWTH ; MERIS DATA ; BIOMASS ; SYSTEM ; OPTIMIZATION ; FORMULATION ; PARAMETERS ; PHENOLOGY ; STRESS |
| 资助项目 | National Natural Science Foundation of China[41871353] ; National Natural Science Foundation of China[41801286] ; National Natural Science Foundation of China[41921001] ; National Natural Science Foundation of China[41871358] ; National Natural Science Foundation of China[61661136006] ; Young Elite Scientists Sponsorship Program by the China Association for Science and Technology (CAST)[2018CAASS04] ; Open Project Fund for Key Laboratory of Agricultural Remote Sensing, Ministry of Agriculture and Rural Affairs[201708] ; Fundamental Research Funds for Central Nonprofit Scientific Institution[1610132019026] ; Agricultural Science and Technology Innovation Program of Chinese Academy of Agricultural Sciences (CAAS) ; Outstanding Talents and Innovative Team of Agricultural Scientific Research, Ministry of Agriculture and Rural Affairs |
| WOS研究方向 | Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| WOS记录号 | WOS:000711850900016 |
| 资助机构 | National Natural Science Foundation of China ; Young Elite Scientists Sponsorship Program by the China Association for Science and Technology (CAST) ; Open Project Fund for Key Laboratory of Agricultural Remote Sensing, Ministry of Agriculture and Rural Affairs ; Fundamental Research Funds for Central Nonprofit Scientific Institution ; Agricultural Science and Technology Innovation Program of Chinese Academy of Agricultural Sciences (CAAS) ; Outstanding Talents and Innovative Team of Agricultural Scientific Research, Ministry of Agriculture and Rural Affairs |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/167907]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Chen, Zhongxin; Yang, Peng |
| 作者单位 | 1.Chinese Acad Agr Sci, Key Lab Agr Remote Sensing, Minist Agr & Rural Affairs Inst Agr Resources, Beijing 100081, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wu, Shangrong,Ren, Jianqiang,Chen, Zhongxin,et al. Evaluation of Winter Wheat Yield Simulation Based on Assimilating LAI Retrieved From Networked Optical and SAR Remotely Sensed Images Into the WOFOST Model[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2021,59(11):9071-9085. |
| APA | Wu, Shangrong,Ren, Jianqiang,Chen, Zhongxin,Yang, Peng,Li, He,&Liu, Jia.(2021).Evaluation of Winter Wheat Yield Simulation Based on Assimilating LAI Retrieved From Networked Optical and SAR Remotely Sensed Images Into the WOFOST Model.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,59(11),9071-9085. |
| MLA | Wu, Shangrong,et al."Evaluation of Winter Wheat Yield Simulation Based on Assimilating LAI Retrieved From Networked Optical and SAR Remotely Sensed Images Into the WOFOST Model".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 59.11(2021):9071-9085. |
入库方式： OAI收割
来源：地理科学与资源研究所
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