Integration of UAV data with soil water balance models for evaluation/monitoring of maize water stress

Abstract

UAV based photogrammetry and 3D mapping are gaining fast and wide applications around the world majorly due to the relatively low-cost advantage it offers in the acquisition of high resolution multispectral acquisitions, compared to Aerophotogrammetry and satellite acquisitions. This research seeks to demonstrate the applicability of UAV photogrammetry visible, multispectral and thermal in investigating some physiological indexes of plants, reflecting plant physiological traits. A maize field in Latina (Italy) was acquired using a Fly Novex drone and with different cameras for the various acquisitions and consequently for different flight heights. The obtained images were processed using different photogrammetric models and a variable number of Ground Control Points (GCPs) for the georeferencing and accuracy assessment as well. Subsequently, by combining hydrological simulation methods and the use of physical indicators of the state of water stress, a method is proposed for predicting crop water consumption. The study conducted on the agricultural land of test site has provided useful results in terms of water savings, with an estimated value of three quarters of the total cubic meters of water needed to bring the land to saturation.