Please use this identifier to cite or link to this item: http://dspace.iitrpr.ac.in:8080/xmlui/handle/123456789/4132
Title: Investigating the environmental impacts of coal mining using remote sensing and in situ measurements in Ruqigou Coalfield, China
Authors: Saini, V.
Li, J.
Yang, Y.
Li, J.
Wang, B.
Tan, J.
Keywords: Coal mine fires
Environmental impact
Support vector machine (SVM)
Vegetation index (NDVI)
Water quality
Flue gas analysis
Issue Date: 30-Oct-2022
Abstract: China is the largest producer and consumer of coal in the world. The extraction of coal is increasing intensively to meet the needs of the ever-increasing population and industries. However, coal mining has resulted in environmental changes, including deforestation, air, water, soil, and landform deterioration. This study investigates the impact of mining on the environment in Ruqigou coalfield by utilising in situ and remote sensing data. Field data collected include temperature, gas compositions, and water samples. Multi-temporal Landsat data of 1991, 2003, and 2019 were used in monitoring the impact of mining on different land covers, especially vegetation. A supervised classification was performed to assess the changes in land cover. In order to track the changes in vegetation, normalised difference vegetation index (NDVI) was employed. To study the changes in coal fire areas, thermal anomalies were extracted from the thermal infrared data using a dynamic thresholding technique. The results of in situ analyses show that water quality is unfit for domestic, industrial, and agricultural use. All the gas sampling sites emit noxious gases such as CO2, CO, NO2 and degrade the local air quality. The classified maps and vegetation indices show a significant decrease in vegetation. The thermal anomalies show an increase in fire areas over the years. Thus, it could be concluded that the conjunctive use of field-based measurements and remote sensing data can be a powerful tool for gaining a comprehensive understanding of the environmental impacts associated with largescale mining.
URI: http://localhost:8080/xmlui/handle/123456789/4132
Appears in Collections:Year-2022

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