<![CDATA[Coal mining, particularly open-pit mining methods, induces severe environmental degradation, including deforestation, loss of flora and fauna, and soil erosion. Consequently, extensive revegetation efforts are necessary to restore and rehabilitate the damaged vegetation. This study uses remote sensing techniques to investigate the correlation between land surface temperature (LST) and vegetation density over six years of revegetation activities. Temporal Landsat 8 imagery from 2015 to 2021 was used for data analysis. Image processing involved transforming the Normalized Difference Vegetation Index (NDVI) and extracting LST data. Statistical correlation analysis using Pearson correlation was employed to analyze the data. Results indicate a notable decline in land surface temperature at the project site from 2015 to 2021, attributed to the gradual reduction of open spaces from coal mining activities, which were gradually replaced by vegetation cover. Concurrently, NDVI values at the site significantly increased over the same period, indicating the successful transition from barren land to vegetated land. Moreover, a substantial correlation between LST and NDVI values was observed, as denoted by Pearson coefficient exceeding 0.7, with a strong negative correlation. This underscores the significant relationship between vegetation cover and land surface temperature dynamics. These findings emphasize the effectiveness of revegetation efforts in mitigating the adverse impacts of coal mining on the environment. They highlight the crucial role of remote sensing in monitoring and assessing the progress of rehabilitation activities, guiding future revegetation strategies for sustainable land management and ecosystem restoration.]]>
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