Study On Integration Of Remote Sensing Technology And ORYZA2000Model To Simulate Regional Paddy Growth In Chongqing

Accurate crop growth monitoring and yield forecasting have a great significance in ensuring food safety system in our country. Satellite remote sensing technology and crop model has each value in crop monitoring and yield estimation, remote sensing technology can perform yield estimation on regional scale, crop model can attain accurate single point analog yield estimation, Combination of crop model and remote sensing technology can realize strengthening mutual advantages each other and crop growth dynamic simulation on regional scale, it provides more effective tools for agricultural condition monitoring, production management, growth evaluation and crop yield estimation and other sides. In this paper, rice production research in Chongqing City was taken as a case to study regional crop growth simulation through combination of remote sensing technology and crop model.In this study, LAI was as a binding parameter, crop model and remote sensing technology were taken to realize regional rice growth simulation and yield estimation. Firstly, rice growth information in agricultural site in Jiangjing was used to realize parameters localized debugging and verification, and then crop model which adapted to rice growth in Chongqing City was built; Secondly based on HJ-1A/B remote sensing data which has30m spatial resolution, PROSAIL radiative transfer model was introduced and canopy LAI was obtained through LUT; Thirdly by finding out the similar counts on LAI growth curve which inverted by remote sensing technology and ORYZA2000model, rice growth trend can be simulated and rice yield can be estimated in Dianjiang, Fengdu, Jiangjing, Kaixian, Liangping, Nanchuang, Wanzhou, Yongchuang and Youyang nine representative areas according to early, middle and late three kinds of sowing time categories.Study results showed that:(1) localized ORYZA2000model was simulated well in experiment field, stem biomass NRMSE was25%, green leaf biomass NRMSE was35%, spike biomass NRMSE was34%, total biomass on the ground NRMSE was28%, LAI RMSE was28%, yield simulated error was8.7%;(2) RMSE of regional scale LAI inverted by PROSAIL model and remote sensing technology was0.82, the maximum deviation was0.42, result was feasible;(3) LAI was as an intermediate parameter in order to achieve combination of crop model and remote sensing technology, and significant effects were achieved on rice planting area extraction and yield forecasting, relative error of simulated rice area and yield respectively was6.8%and0.8%.In this study innovations were as follows:(1) Method this paper selected which combined with ORYZA2000model and remote sensing technology was easier than drive method and regulation method;(2) In order to invert rice LAI better, PROSAIL model which has strong physical properties was picked, and implemented method was LUT;(3) Rice yield estimation monitoring technology combined with remote sensing and crop model was built adapted to Chongqing, and it provided some reference value for rice monitoring through remote sensing technology in Chongqing.Because of limited by experiment data shortage in this study, its universality and application prospect remain be certified.