A synergetic approach for quantification and analysis of coal fires in Jharia Coalfield, India

被引:4
作者
Raju, Ashwani [1 ]
Singh, Anjali [2 ]
Chandniha, Surendra Kumar [3 ]
机构
[1] Banaras Hindu Univ, Inst Sci, Dept Geol, Remote Sensing & GIS Lab, Varanasi 221005, Uttar Pradesh, India
[2] Mohanlal Sukhadia Univ, Dept Geol, Hydrolgeol Res Lab, Udaipur 313001, India
[3] BRSM Coll Agr Engn & Technol & Res Stn, Dept Soil & Water Engn, IGKV, Mungeli 249334, Chhattisgarh, India
关键词
Coal fire; Thresholding; Land surface temperature (LST); Temporal analysis; Mapping; Dynamics; TEMPERATURE; AREA;
D O I
10.1016/j.pce.2023.103441
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Temporal monitoring and understanding of the dynamics of coal fires in the Jharia Coalfield (JCF) are required to reduce its effect on sustainable industrial growth, environment & human safety. This research explores temporal dataset of Landsat 8 OLI Thermal Infrared Sensor (TIRS) from 2015 to 2019 to detect, map and quantify coal fire affected areas in JCF at the colliery level. The results indicated that the East Barora, Sijua, Katras, Kusunda, Kustore, Pootkee Balihari, Bastacolla, Jharia, and Lodna are intensely fire-affected collieries with a significant increase in risk area from 4.57 km2 in 2015 to 11.43 km2 in 2019. The central part of the area is highly affected. The extent of coal fire shows temporal fluctuation between 2015 and 2019, but overall exhibit a significant increase from 2.76 km2 to 7.52 km2. Sijua, Katras, Kusunda, Lodna, and Kustor occupying the central and southeastern parts of the JCF, respectively, constitute nearly -85% of the total fire. However, in comparison to the information inferred from the field-based knowledge, the results derived from satellite-based observations are slightly underestimated due to the reason that the coal fire-derived thermal anomalies are the function of depth, intensity and proportion of coal fire in a coarse resolution TIR pixel, structural attributes, interventions from the mining operation and regional land use planning. Further, the risk areas map out using the TIR-based approach have been integrated with the prevailing structural attributes and Landsat 8 OLI-derived surface thermal anomalies, which enabled an understanding of the dynamics of coal fire propagation in JCF.
引用
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页数:16
相关论文
共 53 条
[1]  
Ackersberg R., 2003, UNDERSTANDING UNPUB
[2]  
[Anonymous], 2005, PROCEEDING INT C COA
[3]  
Bharat Coking Coal Limited (BCCL), 2008, Master Plan for Dealing with Fire, Subsidence and Rehabilitation in the Leasehold of BCCL
[4]  
Bharti A.K., 2014, 51 ANN CONVENTION IN, P59
[5]   Studying the coal fire dynamics in Jharia coalfield, India using time-series analysis of satellite data [J].
Biswal, Shanti Swarup ;
Gorai, Amit Kumar .
REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT, 2021, 23
[6]  
Central Mine Planning and Design Institute (CMPDI), 1989, GEOL MAP JHAR COALF
[7]   Detecting, mapping and monitoring of land subsidence in Jharia Coalfield, Jharkhand, India by spaceborne differential interferometric SAR, GPS and precision levelling techniques [J].
Chatterjee, R. S. ;
Thapa, Shailaja ;
Singh, K. B. ;
Varunakumar, G. ;
Raju, E. V. R. .
JOURNAL OF EARTH SYSTEM SCIENCE, 2015, 124 (06) :1359-1376
[8]  
Finkelman RB, 2011, COAL AND PEAT FIRES: A GLOBAL PERSPECTIVE, VOL 1: COAL - GEOLOGY AND COMBUSTION, P115, DOI 10.1016/B978-0-444-52858-2.00007-4
[9]  
Gangopadhyay P.K., 2008, THESIS I GEOINFORMAT
[10]  
Gangopadhyay PK, 2007, REV ENG GEOL, V18, P239, DOI 10.1130/2007.4118(16)