Applying RGB-Based Vegetation Indices Obtained from UAS Imagery for Monitoring the Rice Crop at the Field Scale: A Case Study in Portugal

Abstract

Nowadays, Unmanned Aerial Systems (UASs) provide an efficient and relatively affordable remote sensing technology for assessing vegetation attributes and status across agricultural areas through wide-area imagery collected with cameras installed on board. This reduces the cost and time of crop monitoring at the field scale in comparison to conventional field surveys. In general, by using remote sensing-based approaches, information on crop conditions is obtained through the calculation and mapping of multispectral vegetation indices. However, some farmers are unable to afford the cost of multispectral images, while the use of RGB images could be a viable approach for monitoring the rice crop quickly and cost-effectively. Nevertheless, the suitability of RGB indices for this specific purpose is not yet well established and needs further investigation. The aim of this work is to explore the use of UAS-based RGB vegetation indices to monitor the rice crop. The study was conducted in a paddy area located in the Lis Valley (Central Portugal). The results revealed that the RGB indices, Visible Atmospherically Resistant Index (VARI) and Triangular Greenness Index (TGI) can be useful tools for rice crop monitoring in the absence of multispectral images, particularly in the late vegetative phase.