后苏联时期(1991-2022 年)乌兹别克斯坦 Ugam Chatkal 国家公园植被变化与气候变量的关系

B. Alikhanov, B. Pulatov, L. Samiev
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引用次数: 0

摘要

本文介绍了有关乌干查特卡尔国家公园(乌兹别克斯坦)植被变化及其与后苏联时期(1991-2022 年)气候变化关系的综合研究。该研究利用遥感技术,特别是归一化植被指数(NDVI)和土壤调整植被指数(SAVI)来监测植被的时空变化。Landsat 卫星图像和气象数据(包括温度和降水记录)构成了分析的基础。研究旨在了解气温、土壤温度和降水量等气候因素对植被覆盖的影响。研究采用了皮尔逊相关分析等统计方法,以确定这些变量之间关系的强度和方向。研究结果表明,净植被指数(NDVI)和植被覆盖度指数(SAVI)与气温和土壤温度密切相关,表明这些气候因素对植被的健康和生长具有重要影响。研究结果表明,乌干查特卡尔国家公园植被覆盖度的变化与气候变化密切相关,气温与时间的相关性很大,表明气温呈上升趋势。研究还预测了未来的气候和植被趋势,预计未来四十年气温、降水量和植被覆盖率都将增加。研究特别强调了监测和了解气候变化与植被动态之间复杂的相互作用的重要性,这对该地区的环境管理和政策制定至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Vegetation cover change in Ugam Chatkal National Park, Uzbekistan, in relation to climate variables during the post-Soviet period (1991-2022)
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.
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