Abstract: Taking the winter wheat planting areas in Rugao City and Haian County of Jiangsu Province as test objects, the clustering defining of wheat growth management zones was made, based on the spatial variability analysis and principal component extraction of the normalized difference vegetation index (NDVI) data calculated from the HJ-1A/B CCD images (30 m resolution) at different growth stages of winter wheat, and of the soil nutrient indices (total nitrogen, organic matter, available phosphorus, and available potassium). The results showed that the integration of the NDVI at heading stage with above-mentioned soil nutrient indices produced the best results of wheat growth management zone defining, with the variation coefficients of NDVI and soil nutrient indices in each defined zone ranged in 4.5%-6.1% and 3.3%-87.9%, respectively. However, the variation coefficients were much larger when the wheat growth management zones were defined individually by NDVI or by soil nutrient indices, suggesting that the newly developed defining method could reduce the variability within the defined management zones and improve the crop management precision, and thereby, contribute to the winter wheat growth management and process simulation at regional scale.

Key words: remote sensing, geostatistics, spatial variability, principal component analysis, management zone defining