大面积小麦遥感估产区划是一项专项应用区划,主要服务于小麦遥感估产研究与实践。本文结合农作物区划理论和小麦遥感估产的具体要求,并重点考虑后者,提出了小麦遥感估产区划的原则和依据,建立了区划指标体系,藉此把我国分为１４个估产区和３２个估产亚区。

egionalization for estimating the wheat yield by using remote sensing data is the foundation of estimating the wheat yield in a large area by using remote sensing data.It is a special applied regionalization.It intends to offer a spatial framework suitable to the system of the estimation of wheat yield, and to provide the scientific bases for the selection of information sources,temporals of remote sensing,information processing,wheat discrimination,and the estimation methods of wheat area and yield.First,this paper puts forward some regionalization principles.They are the principle of combining the integrative analysis with the analysis of leading factors,the principle of combining the regionalization with classification,the principle of combining crop analysis with the condition analysis of remote sensing,the principle of combining the spatial analysis with the process analysis,the principle of combining the analysis of elements with the analysis of their relations, and the principle of keeping the grass roots administrative regions unbroken.Secondly,it analyses the bases of this regionalization which comprise the spatial differences of ground types and combinations, the succession of crop aspects,the relation of wheat yield to vegetation indices and environmental factors,the atmospheric and soil spectral noise the variance of solar elevation,etc.Thirdly,it works out the schemes about the optimum temporal for the estimation of wheat yield by remote sensing, the information sources of space remote sensing and the land use structure. Finally, it divides the country into 14 regions of crop yield estimation using the optimum temporal as a leading index and the total growing period,the ecological type,the climatic yield and the cropping system as reference indices and 32 subregions of yield estimation taking the ratio of farmland area, and the ratio of planting area of wheat as leading indices and the days of clear sky and the days of overcast sky as reference indices.