Continuous simulation of crop growth parameters at spatial-time scale is a key technique for monitoring crop growth status and precision agriculture.This paper realized the spatial-time scale continuous simulation of growth parameters with the assimilation of remote sensing information into crop growth model

monitoring growth parameters changes on spatial-time scale.Construct a model named WOPROSAIL with the coupling of crop growth model WOFOST and canopy radiative transfer model Prospect+Sail（PROSAIL）.Then particle swarm optimization（PSO） algorithm was used to minimize difference between observed values of soil adjusted vegetation index（SAVI） derived from CCD data and simulated values of soil adjusted vegetation index（SAVI’） calculated by coupling model for optimizing initial parameters of WOFOST.Regionalization of parameters was achieved with MODIS data retrieval

then by inputting these regional parameters

optimized WOFOST model

initial parameters of which were optimized

was driven for each pixel and then regional growth parameters were calculated

achieving continuous simulation of crop growth parameters on spatial-time scale.Finally

a region scale remote sensing-crop simulation assimilation framework model named RS-WOPROSAIL was constructed.The results indicated that assimilation model solved the discontinuity of spatial scale simulation by crop growth model and time scale retrieval by remote sensing information.Growth parameters simulated by optimized crop growth model

including leaf area index（LAI）

weight of storage organs（WSO） and total above ground production（TAGP）

preferably reflected the changes of rice growth status on spatial-time scale

and the relative error between simulation yield and actual measurements was 27.4%.