To the question about remote sensing of the earth for precision farming tasks and assessment of the consequences of techno-environmental events

Abstract

Some issues of the use of unmanned aircraft and space vehicles in monitoring the consequences of technical and environmental events and precision farming are considered. The proposed technology is aimed at improving the recognition accuracy of infrastructure objects with obtaining the numerical values of their 3D coordinates. The aim of the research is to improve the quality of monitoring using neural network identification and classification of objects in multi-zone satellite images obtained from unmanned aerial vehicles (UAV). Research includes both theoretical research and applied problem solving. The mathematical basis of image processing is the image recognition computer. Practical research is based on experimentation, software implementation, testing of algorithms and technology. An effective method of video surveillance of the territory has been improved. The task of the authors' research is to improve the accuracy of objects recognition on the earth's surface (specific infrastructure objects, the sky, the state of vegetation of agricultural land). The authors have experience in this area. The solution to this problem occurs simultaneously in two directions. The first direction: the technical result is ensured by the fact that the technology offers the use of a UAV equipped with two video cameras. The second direction is the use of scientific idea consisting in the development of a method for joint computer processing of digital and analog images obtained from UAVs, as well as quasi-simultaneous and reusable multi-zone satellite images. A new result of the research is the developed data structure for storing the model of the recognition process, which allows to jointly save dissimilar characteristics and membership functions of different types in the same tables