ANALYSIS OF THE IMPACT OF CLIMATE CHANGE ON THE "FOREST" LANDSCAPE COMPONENT USING THE "DECISION TREE" TECHNOLOGY

Climate change is expected to become significantly evident in the coming decades, leading to impacts such as population challenges, hindrances in agricultural development, soil salinization, river depletion, and an increase in natural disasters. Climate, as a fundamental element of environmental factors, plays a critical role in the development of the global economy, and its changes can result in profound socio-economic and political consequences. As a result of various natural and anthropogenic influences, landscape components, water bodies, soil cover, pastures and meadows, agricultural lands, forests, and dense vegetation areas can be damaged. Sudden climate changes are known to have a strong negative impact on the flora and fauna of affected areas. Considering these factors, the analysis of data derived from processing satellite information reflecting abrupt climate variability in various regions of the Republic of Azerbaijan through soft computing methods holds significant scientific and practical relevance. The article emphasizes the relevance of studying the interdependence of various climate parameters (distribution of solar radiation, air temperature up to two meters in height, soil surface temperature, absolute humidity up to two meters in height, precipitation amount, atmospheric pressure, wind speed at two meters, and relative humidity of the soil surface down to five centimeters) and their impact on landscapes using Artificial Intelligence. In the modern era, soft computing technologies are utilized to solve complex problems of a nature that cannot be addressed by traditional computational methods. Such problems include the analysis of abrupt climate changes. Soft Computing provides tools to manage uncertainties in the real world. Due to its dynamic and multi-dimensional nature, soft computing models serve as invaluable tools for tackling complex real-world problems. They are applied across numerous industrial and research fields. As a result of applying the Decision Tree tool of Artificial Intelligence to the forested areas of the Guba-Khachmaz economic region of the Republic of Azerbaijan, the most influential climate parameters for "Small," "Medium," and "Large" forest areas were identified. The article investigates the impact of certain key climate parameters on the "forest" landscape component of the Guba-Khachmaz economic region using Artificial Intelligence. The analysis utilized the ArcGIS software package, employing data on the areas of the "forest" landscape component (in square kilometers) calculated for the months of July from 1987 to 2022. Keywords: climate change, landscape, landscape components, forests, artificial intelligence, soft computing, decision tree.