Management Zones Delineation through Clustering Techniques Based on Soils Traits, NDVI Data, and Multiple Year Crop Yields

Availability of georeferenced yield data involving different crops over years, and their use in future crop management, are a subject growing debate. In 9 hectare field Northern Italy, seven years data, including wheat (3 years), maize for biomass (2 sunflower, sorghum, comprising remote (Landsat) normalized difference vegetation index (NDVI) during central stages, soil analysis (grid sampling), were subjected to geostatistical (semi-variogram fitting), spatial mapping (simple kriging), Pearson’s correlation interpolated at the same resolution (30 m) as actual NDVI values. Management Zone Analyst software indicated two management zones optimum zone number multiple (7 years) standardized data. Three traits (clay content, total limestone, nitrogen) five dates within dataset (acquired shown be best correlated with multiple- single-year respectively. These eight parameters combined into two-zone map compared map. This resulted 83% pixel agreement high low (89 10 respective pixels map; 73 26 map) between maps. The good agreement, which is due buffering across types, premise differential soil- NDVI-based cropping seasons.