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以江苏省如皋市和海安县冬小麦种植区域为研究对象,将基于小麦不同生育时期30m分辨率的HJ-1A/B CCD影像提取的归一化植被指数(NDVI)与土壤养分指标(全氮、有机质、有效磷、速效钾)分布状况有机结合,在空间变异性分析和主成分提取的基础上进行聚类分区.结果表明,基于抽穗期NDVI与土壤养分指标耦合的分区方法效果最佳,分区后各子区域内部NDVI值和土壤养分指标的变异系数分别在4.5%～6.1%和3.3%～87.9%,低于单纯基于土壤养分指标或NDVI进行分区的子区域内部的变异系数,大大缩小了区域管理单元内部的变异性.分区结果能提高按区管理作业的精度,可为区域性小麦生长管理和过程模拟奠定基础.
Taking the planting areas of winter wheat in Rugao and Haian counties of Jiangsu Province as the research object, the normalized NDVI (NDVI) extracted from the HJ-1A / B CCD images with a resolution of 30m at different growth stages of wheat and soil nutrients (total nitrogen, Organic Matter, Available Phosphorus and Available Potassium) were clustered on the basis of spatial variability analysis and principal components extraction.The results showed that the partitioning method based on the coupling of NDVI and soil nutrient index at heading stage had the best effect, The coefficient of variation (NDVI) and soil nutrient index of each sub-region were 4.5% -6.1% and 3.3% -87.9%, respectively, lower than the coefficient of variation of sub-region based solely on soil nutrient index or NDVI Variability within the regional management unit The zoning results can improve the precision of management by region and lay the foundation for regional wheat growth management and process simulation.