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A remotely sensed study of the impact of meteorological parameters on vegetation for the eastern basins of Afghanistan
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A remotely sensed study of the impact of meteorological parameters on vegetation for the eastern basins of Afghanistan
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Journal Article
A remotely sensed study of the impact of meteorological parameters on vegetation for the eastern basins of Afghanistan
2023
Overview
Despite the importance of the Amu Darya and Kabul River Basins as a region in which more than 15 million people live, and its vulnerability to global warming, only a few studies addressed the issue of the linkage of meteorological parameters on vegetation for the eastern basins of Afghanistan. In this study, data from the MODIS, Global Precipitation Measurement Mission (GPM), and Global Land Data Assimilation System (GLDAS) was used for the period from 2000 to 2021. The study utilized several indices, such as Precipitation Condition Index (PCI), Temperature Condition Index (TCI), Soil Moisture Condition Index (SMCI), Vegetation Condition Index (VCI), and Optical Integrated Drought Index (OIDI). The relationships between meteorological quantities, drought conditions, and vegetation variations were examined by analyzing the anomalies and using regression methods. The results showed that the years 2000, 2001, and 2008 had the lowest vegetation coverage (VC) (56, 56, and 55% of the study area, respectively). On the other hand, the years 2010, 2013, 2016, and 2020 had the highest VC (71, 71, 72, and 72% of the study area, respectively). The trend of the VC for the eastern basins of Afghanistan for the period from 2000 to 2021 was upward. High correlations between VC and soil moisture (R = 0.73, p = 0.0008), and precipitation (R = 0.63, p = 0.0014) were found and also significant correlation was found between VC and drought index OIDI. It was revealed that soil moisture, precipitation, land surface temperature, and area under meteorological drought conditions explained 45% of annual VC variability. It was also found that the orography had a significant influence on both the spatial distribution of the LST and VCI, as well as the spatial correlations between VCI and meteorological parameters.
