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Remote Sens. 2015, 7(1), 319-341; doi:10.3390/rs70100319

Annual Change Detection by ASTER TIR Data and an Estimation of the Annual Coal Loss and CO2 Emission from Coal Seams Spontaneous Combustion

1
State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology, Beijing 100083, China
2
College of Survey Engineering and Geosciences, China University of Mining and Technology, Beijing 100083, China
3
Department of Geography, Center for Geospatial Research, The University of Georgia, Athens, GA 30602, USA
4
Faculty of Resources and Safety Engineering, China University of Mining and Technology, Beijing 100083, China
5
College of Resource and Environment, Graduate University of Chinese Academy of Sciences, Beijing 100049, China
*
Author to whom correspondence should be addressed.
Academic Editors: Dale A. Quattrochi and Prasad S. Thenkabail
Received: 22 July 2014 / Accepted: 16 December 2014 / Published: 30 December 2014
View Full-Text   |   Download PDF [2961 KB, uploaded 30 December 2014]   |  

Abstract

Coal fires, including both underground and coal waste pile fires, result in large losses of coal resources and emit considerable amounts of greenhouse gases. To estimate the annual intensity of greenhouse gas emissions and the loss of coal resources, estimating the annual loss from fire-influenced coal seams is a feasible approach. This study assumes that the primary cause of coal volume loss is subsurface coal seam fires. The main calculation process is divided into three modules: (1) Coal fire quantity calculations, which use change detection to determine the areas of the different coal fire stages (increase/growth, maintenance/stability and decrease/shrinkage). During every change detections, the amount of coal influenced by fires for these three stages was calculated by multiplying the coal mining residual rate, combustion efficiency, average thickness and average coal intensity. (2) The life cycle estimate is based on remote sensing long-term coal fires monitoring. The life cycles for the three coal fire stages and the corresponding life cycle proportions were calculated; (3) The diurnal burnt rates for different coal fire stages were calculated using the CO2 emission rates from spontaneous combustion experiments, the coal fire life cycle, life cycle proportions. Then, using the fire-influenced quantity aggregated across the different stages, the diurnal burn rates for the different stages and the time spans between the multi-temporal image pairs used for change detection, we estimated the annual coal loss to be 44.3 × 103 tons. After correction using a CH4 emission factor, the CO2 equivalent emissions resulting from these fires was on the order of 92.7 × 103 tons. We also discovered that the centers of these coal fires migrated from deeper to shallower parts of the coal seams or traveled in the direction of the coal seam strike. This trend also agrees with the cause of the majority coal fires: spontaneous combustion of coalmine goafs. View Full-Text
Keywords: coal spontaneous combustion; thermal remote sensing; change detection; CO2 emission; coal fire migration coal spontaneous combustion; thermal remote sensing; change detection; CO2 emission; coal fire migration
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Du, X.; Peng, S.; Wang, H.; Bernardes, S.; Yang, G.; Li, Z. Annual Change Detection by ASTER TIR Data and an Estimation of the Annual Coal Loss and CO2 Emission from Coal Seams Spontaneous Combustion. Remote Sens. 2015, 7, 319-341.

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