首页 | 本学科首页   官方微博 | 高级检索  
     

基于遥感和作物生长模型的多尺度冬小麦估产研究
引用本文:余新华,赵维清,朱再春,徐保东,赵志展. 基于遥感和作物生长模型的多尺度冬小麦估产研究[J]. 光谱学与光谱分析, 2021, 41(7): 2205-2211. DOI: 10.3964/j.issn.1000-0593(2021)07-2205-07
作者姓名:余新华  赵维清  朱再春  徐保东  赵志展
作者单位:北京师范大学地理科学学部,地表过程与资源生态国家重点实验室,北京 100875;北京大学深圳研究生院,城市规划与设计学院,广东 深圳 518055;华中农业大学资源与环境学院,宏观农业研究院,湖北 武汉 430070;南京大学大气科学学院,江苏 南京 210023
基金项目:国家重点研发计划子课题(2017YFD0300402-6)和国家自然科学基金面上项目(41977405)资助
摘    要:粮食安全是社会和谐、政治稳定和经济可持续发展的重要保障.准确预测区域乃至全球的农作物产量能够为各级政府、相关部门制定农业农村政策提供技术支持,保障粮食安全.目前关于农作物估产的研究大多具有地域性、经验性,过分依赖地面实测数据,一种基于多光谱卫星遥感数据和作物生长模型估算农作物产量的模型框架SCYM(Scalable C...

关 键 词:遥感  农作物估产  WOFOST模型  冬小麦  安徽省
收稿时间:2020-07-09

Research in Crop Yield Estimation Models on Different Scales Based on Remote Sensing and Crop Growth Model
YU Xin-hua,ZHAO Wei-qing,ZHU Zai-chun,XU Bao-dong,ZHAO Zhi-zhan. Research in Crop Yield Estimation Models on Different Scales Based on Remote Sensing and Crop Growth Model[J]. Spectroscopy and Spectral Analysis, 2021, 41(7): 2205-2211. DOI: 10.3964/j.issn.1000-0593(2021)07-2205-07
Authors:YU Xin-hua  ZHAO Wei-qing  ZHU Zai-chun  XU Bao-dong  ZHAO Zhi-zhan
Abstract:Food security is a guarantee for social harmony, political stability and sustainable development of the economy. However, current research on crop yield estimation is mostly regional and empirical, relying too much on ground-measured data. Scalable Crop Yield Mapping (SCYM) is a satellite data based framework for estimating crop yield.It can be quickly applied to the estimated yield of different spatial scales and different types of crops without relying on measured data. This framework provides an important theoretical basis for multi-scale crop yield estimation research. We took the winter wheat of Anhui Province from 2012 to 2018 as the study object. Firstly, the sensitive parameters determined by the predecessors and their fluctuation ranges in the study area are summarized. Combined with a large amount of site data, the parameters optimization of the WOFOST model was completed. Secondly, random forest models were established based on the simulated yield, simulated leaf area index (LAI) at different periods, and selected meteorological indicators. Finally, the MODIS-LAI under the best observation date combination replaced the simulated LAI for the corresponding time periods to estimate the winter wheat yield in Anhui Province. The main outcomes in this study are as follows: (1) The overall correlation between the estimated outputs and the measured data of the stations is 0.758 (R2 is 0.575), and the RMSE is 790.92 kg·ha-1. The sites with higher production accuracy are mainly distributed in the Huaibei Plain (<1%), while the areas with high errors are concentrated in the hilly areas of southern Anhui (>40%). (2) The winter wheat yield in Anhui Province from 2012 to 2018 was estimated by SCYM. According to the spatial distribution of the 7-year average yield estimation, the yield is gradually decreasing from north to south. The high-value areas are located in the Huaibei Plain in northern Anhui, and the low-value areas are distributed in central Anhui and southern Anhui. (3) The average measured yield from 2012 to 2018 is 6 058.00 kg·ha-1, while the average yield of the SCYM is 5 984.95 kg·ha-1. The correlation between them in the interannual time series is 0.822, and the RMSE is 189.96 kg·ha-1. In seven years, the relative error each year does not exceed 6%. This study shows that the SCYM framework is feasible for estimating winter wheat yield in Anhui Province and has a good effect on yield forecast. This method can improve the regionality and empiricism of the previous crop yield estimation models to a certain extent. Meanwhile, it also solves the shortcomings of computationally intensive methods, which are costly and difficult to popularize. Thus, SCYM has great potential in applying of regional scales, and it will provide an extremely important theoretical basis and practical value for agricultural production in the future.
Keywords:Remote sensing  Yield estimation  WOFOST  Winter wheat  Anhui Province  
本文献已被 CNKI 万方数据 等数据库收录!
点击此处可从《光谱学与光谱分析》浏览原始摘要信息
点击此处可从《光谱学与光谱分析》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号