Assessing the Temporal and Spatial Variability of Coffee Plantation Using RPA-Based RGB Imaging

Abstract

The biophysical parameters of coffee plants can provide important information to guide crop management. An alternative to traditional methods of sparse hand measurements to obtain this type of information can be the 3D modeling of the coffee canopy using aerial images from RGB cameras attached to remotely piloted aircraft (RPA). This study aimed to explore the use of RGB aerial images to obtain 3D information of coffee crops, deriving plant height and volume information together with yield data during three growing seasons in a commercial production area of 10.24 ha, Minas Gerais state, Brazil. Seven data acquisition campaigns were conducted during the years 2019, 2020 and 2021. The flights were made at 70 m above ground level, with lateral and longitudinal overlaps of 75% and 80%, respectively. The images were processed, obtaining canopy surface models (CSMs) derived into plant height and volume data for each campaign. The results showed that it is possible to extract the plant height of coffee plants with an R2 of 0.86 and an RMSE of 0.4 m. It was possible to monitor the temporal variability of coffee plant height and volume based on aerial images and correlate this information with yield data. The results of the modeling analysis demonstrated the possibility of using these variables to help understand the spatial variability of coffee yield within the field.