Models and methods for automating the analysis of logging for the tasks of geographically distributed socio-economic systems

Abstract

Forests play a crucial role in maintaining the Earth's global biodiversity and preserving the ecological balance. In general, forest cover around the world is crucial and is an important indicator of the overall level of health on the planet. It is well known that forests properly purify the air, preserve watersheds, prevent erosion, improve water quality and provide natural resources. In addition, forests help in the face of global warming and absorb a lot of carbon dioxide, which is the main greenhouse gas, thus helping to protect the globe from climate change. In many cases, the range or extent of illegal logging cannot be accurately calculated, mainly due to the nature of the activity. It is estimated that illegal forest activities worldwide lead to the loss of approximately 10-15 billion US dollars in annual government revenues. In the mid-1990s, illicit trade accounted for almost 15% of world trade. In addition, it was pointed out that in the most vulnerable forest regions, more than half of all logging operations were carried out illegally. Despite recent work on environmental initiatives and the development of various tools for monitoring export forest products, more than ever before, it is necessary to use systems to detect illegal logging. Over the past decades, the development of remote sensing technologies, as well as advances in information and communication technologies (ICT), have made it possible to use automated or semi-automatic surveillance solutions in vast areas such as forests. Technologies such as video surveillance, wireless surveillance systems, aerial photographs and satellite images are used. The article discusses the main approaches for analyzing changes in the area of logging. These methods can be used in real time by studying and comparing changes in the areas of forest stands.