Preliminary Results of Multispectral Camera Mounted on Unmanned Aerial Vehicle for Soil Properties Estimation and Mapping
Soil quality continuously deteriorates due to extensive agricultural practices, risking food security. Thus, soil quality sustainability is vital to extend agricultural land productivity potential. However, soil properties estimation entails time consuming, laborious and expensive procedures. Smart agriculture schemes include novel and potentially low cost in situ observations such as unmanned aerial vehicles (UAVs) that are rapidly maturing and becoming viable alternatives to costlier traditional solutions for digital soil mapping. The objective of this research was to evaluate the capabilities of multispectral imagery (400-810 nm) predictive ability for soil properties estimation acquired in bare soil conditions in a 6-ha experimental field in Rizomilos, Thessaly, Greece. A comparative analysis was performed with laboratory spectral measurements of 18 soil samples (0–30 cm) collected from the same field covering the complete VNIR-SWIR range (400-2500 nm). The soil samples were also determined by wet chemistry methods to calibrate the developed prediction models. Considering the imagery data values, the laboratory spectral signatures and the produced spectral indices as input features, a support vector machine for regression algorithm (SVR) was used for model calibration. Laboratory soil spectroscopy resulted in R 2= 0.58 while UAV application R2= 0.48.
Authors: Theodora Angelopoulou | Nikolaos Tziolas | Athanasios Balafoutis | Georgios Zalidis | Dionysis Bochtis
Keywords: UAV, soil organic matter, multispectral, spectral indices
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