Airborne remote sensing to support precision farming

Spatial variability of crops within fields depend on soil variability. This spatial distribution of plant growth conditions, detected by airborne remote sensing, can provide modellers, regional planners and at least farmers with valuable information. Ground truth data of crop parameters were collected and related to spectral information in red, middle and thermal infrared wavebands derived from airborne scanner data. Simple regression analysis has been used to obtain classification functions. The classified spectral images are finally compared with soil properties. Results of three years under study indicate a high applicability of airborne remote sensing technique in order to detect spatial variability of plant growth conditions at field level