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Study on Regionalization for Estimation of Maize Yield Using Remote Sensing Data in China

Qian Huaisui Li Mingxia (Department of Geography,Henan University,Kaifeng,Henan 475001)  
Regionalization for estimation of maize yield using remote sensing data is attempted to offer a spatial framework suitable to the system for estimation of maize yield, selection of information sources, methods for information processing ,maize discrimination,estimation of maize area and yield.Some principles were put forth for combining comprehensive analysis with the analysis of leading factors,regionalization with classification,crop analysis with the condition analysis of remote sensing ,spatial analysis with dynamic analysis,analysis of elements with the analysis of their relations and maintaining a close link among grass root administrative regions. The bases of this regionalization was analyzed which comprised the spatial differences of ground types and combinations ,succession of cropping, maize yield relationships to the vegetation indices and environmental factors, atmospheric and soil spectral moistures and variance of solar energy. The optimum temporal and information sources of space remote sensing for the estimation of maize yield and land use structure all over China were classified. The region for planting maize was divided into 13 subregions for crop estimates using the optimum temporal as leading index and total growing period, climatic yield of maize and cropping system as reference indices and 28 subregions of crop yield estimation taking the percentage of farmland area and planting area of maize as leading indices and the days of clear sky and overcast sky as reference indices.
【Fund】: “八五”科技攻关课题
【CateGory Index】: S513
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