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Information on rice growing areas and rice production is critical for most rice growing countries to make state and economic policies. However, the areas where rice crop is cultivated are often cloudy and rainy, which entails the use of radar remote sensing data for rice monitoring. In this paper, a practical scheme to integrate multi-temporal and multi-polarization ENVISAT ASAR data into rice crop model for regional rice yield estimation has been presented. To achieve this, rice distribution information should be obtained first by rice mapping method to retrieve rice fields from ASAR images, and then an assimilation method is applied to use the observed multi-temporal rice backscattering coefficients which are grouped for each rice pixel to re-initialize ORYZA2000 to predict rice yield. The assimilation method re-initializes the model with optimal input parameters, allowing a better temporal agreement between the rice backscattering coefficients retrieved from ASAR data and the rice backscattering coefficients simulated by a coupled model, i.e., the combination of ORYZA2000 and a semi-empirical rice backscatter model through LAI. The SCE-UA optimization algorithm is employed to determine the optimal set of input parameters. After the re-initialization, rice yield for each rice pixel is calculated, and the yield map over the area of interest is produced. The scheme was validated over Xinghua study area located in the middle of Jiangsu Province of China by using the data set of an experimental campaign carried out during the 2006 rice season. The result shows that the obtained rice yield map generally overestimates the actual rice production by 13% on average and with a root mean square error of approximately 1133 kg/ha on validation sites, but the tendency of rice growth status and spatial variation of the rice yield are well predicted and highly consistent with the actual production variation.rice yield map, crop model, data assimilation, optimization algorithm, classification, ASAR

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It is a critical important task to find out cultivated land change quickly, as the sharply reducing of cultivated land use because of the rapid development of industry and agriculture in Yangtze Delta region. It is satisfied well to investigate land use change with the technology of remote sensing. According to the method of view distinguishing of "dynamic graph and point comparing", cultivated land changes from 1992 to 1995 were investigated for every county in the region, using 1/100000 "TM" imagine data as an information source. The results showed that the cultivated land was decreased sharply as much as 61000 hectares for the region in three years.The mean changing rate was 10. 8% per year. And in the three cities, Suzhou, Wuxi and Changzhou, the rates were as high as 15.6%o/year. Among the decreased cultivated land , construction land was occupied as the part of 51. 8-62%. In order to protect limited land resources, a dynamic measuring system of land use must be organized. According to the "TM" imagine data using the method of remote sensing measurement, a macro-dynamic change of cultivated land in the level of county can be measured rapidly. The precision can be as high as 90-95%. The fixed number of measuring years may be determined according to the dynamic change of cultivated land in the region. The measuring contents of dynamic land use may be expanded to classifying of agriculture, breeding, industry and fishing.