{"title":"印度以采矿为主的 Paschim Bardhaman 地区因采矿引起的森林植被变化","authors":"Ankita Biswas, Sasanka Ghosh","doi":"10.1016/j.rsase.2024.101348","DOIUrl":null,"url":null,"abstract":"<div><p>Mining activities are a recognized factor for Forest Cover Loss (FCL) worldwide. Huge forest cover areas are lost due to mining activities worldwide and in India. This study is conducted to identify the villages that experienced more FCL as a result of mining activities and also focuses on identifying the role of individual coal mines on FCL. Results indicate that the mining area increased to 70.79 km2 in 2020 from 25.56 km2 in 1990, and the vegetation area reduced to 149.22 km<sup>2</sup> from 271 km<sup>2</sup> at the same time. Mostly Jamuria, Barabani, Raniganj, and Pandabeswar blocks have lost large amounts of forest cover due to mining activities. Results also indicate that mining areas have increased nearly threefold and influenced the rate of FCL in the district. Village-level analysis of mining-induced FCL identified that more than ten villages had lost more than 10% of the total forest cover areas due to coal mine expansion resulting in environmental degradation. Analysis of spatial matrices indicates a fragmentation nature of vegetation cover areas of the selected coal mines and indicates that available vegetation areas are concentrated in some pocket areas. Local Indicators of Spatial Autocorrelation (LISA) based spatial patterns of mining-induced FCL show high cluster location in and around major coal mines of the area proving the role of open-cast coal mines on FCL and forest fragmentation. The analysis results may help the planners maintain the healthy environment of the affected villages by formulating alternative ways of forest cover increase.</p></div>","PeriodicalId":53227,"journal":{"name":"Remote Sensing Applications-Society and Environment","volume":"36 ","pages":"Article 101348"},"PeriodicalIF":3.8000,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Mining-induced forest cover change of Paschim Bardhaman, a mining-based district of India\",\"authors\":\"Ankita Biswas, Sasanka Ghosh\",\"doi\":\"10.1016/j.rsase.2024.101348\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Mining activities are a recognized factor for Forest Cover Loss (FCL) worldwide. Huge forest cover areas are lost due to mining activities worldwide and in India. This study is conducted to identify the villages that experienced more FCL as a result of mining activities and also focuses on identifying the role of individual coal mines on FCL. Results indicate that the mining area increased to 70.79 km2 in 2020 from 25.56 km2 in 1990, and the vegetation area reduced to 149.22 km<sup>2</sup> from 271 km<sup>2</sup> at the same time. Mostly Jamuria, Barabani, Raniganj, and Pandabeswar blocks have lost large amounts of forest cover due to mining activities. Results also indicate that mining areas have increased nearly threefold and influenced the rate of FCL in the district. Village-level analysis of mining-induced FCL identified that more than ten villages had lost more than 10% of the total forest cover areas due to coal mine expansion resulting in environmental degradation. Analysis of spatial matrices indicates a fragmentation nature of vegetation cover areas of the selected coal mines and indicates that available vegetation areas are concentrated in some pocket areas. Local Indicators of Spatial Autocorrelation (LISA) based spatial patterns of mining-induced FCL show high cluster location in and around major coal mines of the area proving the role of open-cast coal mines on FCL and forest fragmentation. The analysis results may help the planners maintain the healthy environment of the affected villages by formulating alternative ways of forest cover increase.</p></div>\",\"PeriodicalId\":53227,\"journal\":{\"name\":\"Remote Sensing Applications-Society and Environment\",\"volume\":\"36 \",\"pages\":\"Article 101348\"},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2024-09-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Remote Sensing Applications-Society and Environment\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S235293852400212X\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Remote Sensing Applications-Society and Environment","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S235293852400212X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Mining-induced forest cover change of Paschim Bardhaman, a mining-based district of India
Mining activities are a recognized factor for Forest Cover Loss (FCL) worldwide. Huge forest cover areas are lost due to mining activities worldwide and in India. This study is conducted to identify the villages that experienced more FCL as a result of mining activities and also focuses on identifying the role of individual coal mines on FCL. Results indicate that the mining area increased to 70.79 km2 in 2020 from 25.56 km2 in 1990, and the vegetation area reduced to 149.22 km2 from 271 km2 at the same time. Mostly Jamuria, Barabani, Raniganj, and Pandabeswar blocks have lost large amounts of forest cover due to mining activities. Results also indicate that mining areas have increased nearly threefold and influenced the rate of FCL in the district. Village-level analysis of mining-induced FCL identified that more than ten villages had lost more than 10% of the total forest cover areas due to coal mine expansion resulting in environmental degradation. Analysis of spatial matrices indicates a fragmentation nature of vegetation cover areas of the selected coal mines and indicates that available vegetation areas are concentrated in some pocket areas. Local Indicators of Spatial Autocorrelation (LISA) based spatial patterns of mining-induced FCL show high cluster location in and around major coal mines of the area proving the role of open-cast coal mines on FCL and forest fragmentation. The analysis results may help the planners maintain the healthy environment of the affected villages by formulating alternative ways of forest cover increase.
期刊介绍：
The journal ''Remote Sensing Applications: Society and Environment'' (RSASE) focuses on remote sensing studies that address specific topics with an emphasis on environmental and societal issues - regional / local studies with global significance. Subjects are encouraged to have an interdisciplinary approach and include, but are not limited by: " -Global and climate change studies addressing the impact of increasing concentrations of greenhouse gases, CO2 emission, carbon balance and carbon mitigation, energy system on social and environmental systems -Ecological and environmental issues including biodiversity, ecosystem dynamics, land degradation, atmospheric and water pollution, urban footprint, ecosystem management and natural hazards (e.g. earthquakes, typhoons, floods, landslides) -Natural resource studies including land-use in general, biomass estimation, forests, agricultural land, plantation, soils, coral reefs, wetland and water resources -Agriculture, food production systems and food security outcomes -Socio-economic issues including urban systems, urban growth, public health, epidemics, land-use transition and land use conflicts -Oceanography and coastal zone studies, including sea level rise projections, coastlines changes and the ocean-land interface -Regional challenges for remote sensing application techniques, monitoring and analysis, such as cloud screening and atmospheric correction for tropical regions -Interdisciplinary studies combining remote sensing, household survey data, field measurements and models to address environmental, societal and sustainability issues -Quantitative and qualitative analysis that documents the impact of using remote sensing studies in social, political, environmental or economic systems
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