The article includes a detailed description of various methods of forest fire prevention and risk management, including the use of regulatory, organizational, economic, socio-psychological, preventive, repressive and compensatory methods.
It has been determined that forest fires have serious consequences for ecosystems, causing the destruction of plants and animals, deterioration of air quality and increased emissions of greenhouse gases. They also cause significant economic losses, affecting forest resources, infrastructure and tourism. Climate change and changes in environmental conditions contribute to the spread of pests in forests, which can worsen the situation in forestry and biodiversity conservation. Addressing these challenges requires an integrated approach, including scientific research, strategic planning, risk management and active public engagement. The authors provide a classification of these methods, based on the method of influence, the nature of the influence and the direction of the action. The purpose of the study is to identify and analyze effective approaches and methods aimed at reducing the risk of forest fires and controlling the spread of pests in forest ecosystems. The research uses the methods of camera analysis and review of scientific works, supplemented by field research. This made it possible to develop reasonable recommendations for reducing the risk of forest fires. Special attention was paid to the analysis of forest management data, which included information on the distribution of forests by land category, the classification of plantations and their sanitary condition. Field studies have helped to update and clarify data on the state of plantations and identify key factors that increase the risk of fires. Modern methods of detecting forest fires were used, including video surveillance cameras, satellite surveillance, patrolling territories and the use of unmanned aerial vehicles. A forest fire early detection system is described, which includes IoT devices combined in a porous topology and equipped with sensors for temperature, carbon dioxide, hydrogen, and hydrocarbon gases. The article also describes the methods of multivariate data analysis and principal component methods for reducing data dimensionality and identifying key factors affecting the occurrence of fires. Regression analysis is used to establish the relationship between various variables and predict the probability of fire occurrence. Physico-mechanical, chemical, biological and silvicultural methods of reducing the risk of forest fires and the impact of pests and diseases are identified, including manual collection of insects, shaking off caterpillars, use of traps, chemical spraying and creation of mixed and multi-aged stands. Research perspectives may include the following key aspects: exploring and integrating advanced technologies, such as artificial intelligence, machine learning, and remote sensing of the Earth, for early detection of forest fires and monitoring of pest populations; study of the impact of climate change on the frequency and intensity of forest fires and the distribution of pests, as well as the development of adaptation strategies.
Presented a system for early detection of forest fires based on the use of IoT devices connected to a network with a porous topology. Various factors affecting the risk of fires were studied, and a multivariate analysis of these data was carried out. The early fire detection system is of great importance for the prevention and effective response to forest fires. Considered the use of different risk management methods, including regulatory, legal, organizational, economic and socio-psychological approaches, is critical to reducing the risk of fires. The use of combined methods that include preventive, repressive and compensatory approaches is effective in fighting fires. The use of video surveillance cameras, satellite surveillance, patrolling and unmanned aerial vehicles significantly increases the effectiveness of early detection of fires. It is emphasized that there is no universal method of fighting forest fires and pests, and a comprehensive approach is needed, which includes physical-mechanical, chemical, biological and special forestry measures. Overall, the study highlights the importance of integrated risk management strategies and the implementation of innovative technologies for forest fire risk reduction and pest control.
