Applications of georeferenced high-resolution images obtained with unmanned aerial vehicles. Part I: Description of image acquisition and processing

摘要

There are many aspects of crop management that might benefit from aerial observation. Unmanned aerial vehicle (UAV) platforms are evolving rapidly both technically and with regard to regulations. The purpose of this study was to acquire images with conventional RGB cameras using UAVs and process them to obtain geo-referenced ortho-images with the aim of characterizing the main plant growth parameters required in the management of irrigated crops under semi-arid conditions. The paper is in two parts, the first describes the image acquisition and processing procedures, and the second applies the proposed methodology to a case study. In the first part of the paper, the type of UAV utilized is described. It was a vertical take-off and landing quadracopter aircraft with a conventional RGB compact digital camera. Other types of on-board sensors are also described, such as near-infrared sensors and thermal sensors, and the problems of using these types of expensive sensor is discussed. In addition, software developed by the authors for photogrammetry processing, and information extraction from the geomatic products are described and analysed for agronomic applications. This software can also be used in other applications. To obtain agronomic parameters, different strategies were analysed, such as the use of computer vision for canopy cover extraction, as well as the use of vegetation indices derived from the visible spectrum, as a proper solution when very-high resolution imagery is available. The use of high-resolution images obtained with UAVs together with proper treatment might be considered a useful tool for precision in monitoring crop growth and development, advising farmers on water requirements, yield production, weed and insect infestations, among others. More studies, focusing on the calibration and validation of these relationships in other crops are required.