Use of RGB and multispectral cameras, Lidar sensors, and image processing techniques on drones for data acquisition in agricultural applications

Abstract

Drones, also known as unmanned aerial vehicles (UAVs), hold significant promise for applications in agriculture. Their usage spans various purposes, with one of the most common being crop scouting. Equipped with video feeds that transmit live images to ground control stations, drones allow farmers and agronomists to observe fields from above in real-time. This aerial perspective provides a powerful and efficient tool for identifying problem areas within crops, enabling quicker, more targeted responses to emerging issues. Different types of cameras and sensors provide an even broader range of applications for drones in agriculture. Using different sensors and selecting methodology based on the various indices can facilitate a wide range of data collection. RGB sensors, multispectral sensors, hyperspectral cameras, thermal or infrared cameras, ground-level control sensors, and Lidar sensors are different kinds of sensors used per the application requirement. The objective of this review is to collect details of various sensors used for controlling drones, various techniques used for capturing data using drones and methods used to analyze captured data.