{"title":"Vegetation cover change in Ugam Chatkal National Park, Uzbekistan, in relation to climate variables during the post-Soviet period (1991-2022)","authors":"B. Alikhanov, B. Pulatov, L. Samiev","doi":"10.23917/forgeo.v38i1.3824","DOIUrl":null,"url":null,"abstract":"This paper presents a comprehensive study relating to the vegetation cover change in Ugam Chatkal National Park (Uzbekistan) and its relation to climate change during the post-Soviet period (1991-2022). The study utilises remote sensing technology, specifically the Normalised Difference Vegetation Index (NDVI) and the Soil-Adjusted Vegetation Index (SAVI), to monitor spatio-temporal changes in vegetation. Landsat satellite imagery and meteorological data, including temperature and precipitation records form the basis of the analysis. The research aims to understand the impact of climatic factors, such as air temperature, soil temperature and precipitation on vegetation cover. Statistical methods, for example Pearson’s correlation analysis are employed to determine the strength and direction of relationships between these variables. The study reveals that both NDVI and SAVI are strongly correlated with air and soil temperatures, indicating the significant influence of these climatic factors on vegetation health and growth. The findings suggest that changes in vegetation cover in the Ugam Chatkal National Park are closely tied to climate change, with air temperature revealing a substantial correlation with time, indicating a trend towards increasing temperatures. The study also forecasts future climatic and vegetation trends, predicting an increase in air temperature, precipitation and vegetation cover over the next four decades. In particular, the research highlights the magnitude of monitoring and understanding the complex interactions between climate change and vegetation dynamics, which are crucial for environmental management and policy-making in the region.","PeriodicalId":31244,"journal":{"name":"Forum Geografi","volume":"73 12","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Forum Geografi","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23917/forgeo.v38i1.3824","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper presents a comprehensive study relating to the vegetation cover change in Ugam Chatkal National Park (Uzbekistan) and its relation to climate change during the post-Soviet period (1991-2022). The study utilises remote sensing technology, specifically the Normalised Difference Vegetation Index (NDVI) and the Soil-Adjusted Vegetation Index (SAVI), to monitor spatio-temporal changes in vegetation. Landsat satellite imagery and meteorological data, including temperature and precipitation records form the basis of the analysis. The research aims to understand the impact of climatic factors, such as air temperature, soil temperature and precipitation on vegetation cover. Statistical methods, for example Pearson’s correlation analysis are employed to determine the strength and direction of relationships between these variables. The study reveals that both NDVI and SAVI are strongly correlated with air and soil temperatures, indicating the significant influence of these climatic factors on vegetation health and growth. The findings suggest that changes in vegetation cover in the Ugam Chatkal National Park are closely tied to climate change, with air temperature revealing a substantial correlation with time, indicating a trend towards increasing temperatures. The study also forecasts future climatic and vegetation trends, predicting an increase in air temperature, precipitation and vegetation cover over the next four decades. In particular, the research highlights the magnitude of monitoring and understanding the complex interactions between climate change and vegetation dynamics, which are crucial for environmental management and policy-making in the region.