Visible Spectrum Image Analysis For Estimation of Phenological Stages in Irrigated Bean Cropping

Abstract

Objective: Analyze the spectro-temporal behavior based on vegetation indices based on the visible portion of the electromagnetic spectrum, using images acquired by a drone in comparison with satellite images.   Theoretical Framework: Beans (Phaseolus vulgaris L.) are one of the most economically important crops in Brazil and applying technologies aimed at precision agriculture have been more accessible and are fundamental tools for crop management and monitoring.   Method: Drone and satellite image captures were carried out in seven moments to obtain vegetation indices, the products generated are thematic maps of: GLI. VARI. NGRDI and VEG, which were tested using various statistical tools to ensure reliability and validity.   Results and Discussion: In normality tests at a level of statistical significance of 5% for the satellite and drone data sets, both showed the same behavior, in all drone data indicated normality assumptions (p-value = 2.2e-16) and the satellite data followed the same behavior, (p-value < 2.2e-16).   Research Implications: These results highlight the great potential of using visible spectrum images from UAVs and Sentinel-2 for harvest management due to the spatial variability of bean maturation.   Originality/Value: The use of precision agriculture to estimate phenological stages optimizes the use of water, fertilizers and pesticides, influencing the efficiency of resource use and the profitability of the crop.