Wheat spatial variation based on spectral vegetation indices and soil analysis

Soil characteristics, proximal and remote spectral vegetation indices were geo-referentially assessed in a 4.15 ha wheat field in northern Italy. Data obtained in the three separate domains were submitted to principal component analysis (PCA), and the retained PCs were clustered to delineate homogeneous areas at low (L), intermediate (I) and high (H) potential, based on soil parameters (CLUsp), proximal (CLUpi) and remote spectral vegetation indices (CLUri). Spatial distribution of soil and crop data showed a low performing area (GY < 3 Mg ha-1) and a high performing one (GY > 8 Mg ha-1). CLUsp staged a lower GY difference between L and H area (60%) than CLUpi and CLUri (ca. 100%). Area levels (L, I, H) based on vegetation indices outlined a better degree of agreement with GY, compared to area levels based on soil parameters. In exchange for this, the above referred soil parameters are quite consistent in time, allowing soil data to be used for more crop seasons.