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Geo-spatial Estimation and Forecasting of LULC Vulnerability Assessment of Mining Activity: A Case Study of Jharia Coal Field, India

机译:采矿活动的LULC脆弱性评估的地理空间估计和预测:以印度Jharia煤田为例

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Coal is natural deposit minerals and vestibules effect in environment due to operation of mine. Preliminary phase is reconnaissance survey for extraction of coal ores and after that, next operation is happen. In addition, Mining has considered as an eco-unfriendly in natural action but in recent scenarios of Indian coal mines production is very hugs rate with undisciplined nature accompanied by large volumes of hazardous solid, liquid and gaseous material during various mining and related activities. Global aided for the eco-system of mining, associated activities in mining complexes, minimization prevention and extenuation of these encroachments. There are applying geospatial approaches for most important classified classes related to mining activity of land use land cover (LULC) estimation from landsat of four-year data. Vulnerability assessment of classified classes and forecasting of spatial data in future likes features agricultural land, forest, vegetation, mine plantation, scrub land, open cast mine, abandoned mine pit, overburden dump, settlement and water body respectively. It has focused on spatial feature change due to mining activities and mainly use to a case study of Jharia coalfield (JCF), Jharkhand.
机译:煤炭是天然矿物质,由于矿山的运营,其在环境中具有前庭效应。初步阶段是侦查煤炭矿石的勘测工作,此后将进行下一个作业。此外,采矿被认为对自然行为不利于生态,但是在最近的印度情景中,印度煤矿的产量非常高,自然规律无规,在各种采矿和相关活动中伴有大量危险的固态,液态和气态物质。全球为采矿生态系统,采矿综合体中的相关活动,最小化预防和扩大这些侵害提供了援助。对于来自四年期遥感数据的土地利用土地覆盖(LULC)采矿活动估计的最重要分类类别,正在应用地理空间方法。分类等级的脆弱性评估和未来空间数据的预测,分别是农业用地,森林,植被,矿山种植地,灌丛土地,露天矿,弃矿坑,表土堆放,沉降和水体。它专注于由于采矿活动而引起的空间特征变化,主要用于贾坎德邦(Jharkhand)贾里亚煤田(JCF)的案例研究。

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