Correlation of UAV and satellite-derived vegetation indices with cotton physiological parameters and their use as a tool for scheduling variable rate irrigation in cotton

Autor: L. N. Lacerda, J. Snider, Y. Cohen, V. Liakos, M. R. Levi, G. Vellidis
Rok vydání: 2022
Předmět:
Zdroj: Precision Agriculture. 23:2089-2114
ISSN: 1573-1618
1385-2256
Popis: Current irrigation management zones (IMZs) for variable rate irrigation (VRI) systems are static. They are delineated in the beginning of the season and used thereafter. However, recent research has shown that IMZ boundaries are transient and change with time during the growing season. The primary goal of this study was to explore the potential of using vegetation indices (VIs) developed from unmanned aerial vehicle (UAV) and satellite images to predict cotton physiological parameters that can be used to delineate in-season boundaries of IMZs. A 2 year study was conducted in a 38 ha commercial cotton field in southwestern Georgia, USA. Throughout the two growing seasons, VIs were calculated from UAV, PlanetScope, and Sentinel-2 images. Predawn leaf water potential (LWPPD) and plant height were measured at 37 locations in the field on the same day as the flights and correlated with UAV and satellite based-VIs. GNDVI (Green normalized difference vegetation index) was the best predictor of plant height with correlation values of 0.72 (p −1, respectively. The DVRI system resulted in average yield 4.6% higher than conventional irrigation, while applying 14.0% less water. Despite the lower water application by the DRVI system, the performance comparison between the DRVI and the conventional irrigation was not conclusive.
Databáze: OpenAIRE
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