Detecting coal fires with a neural network to reduce the effect of solar radiation on Landsat Thematic Mapper thermal infrared images

Deng, Weiwei; Wan, Y. Q.; Zhao, Ran

doi:10.1080/014311601300074469

Cited by 15 publications

(2 citation statements)

References 10 publications

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“…The Centralia (Pennsylvania, USA) mine fire started to burn in May 1962 (Tietz 2004) and continues to burn, and the fire has resulted in most of the town being abandoned. They occur worldwide in leading countries in coal production such as China, Russia, the USA, Indonesia, Australia and South Africa (Dalverny and Chaiken 1991;Glover 1998;Prakash and Gupta 1998;Prakash et al 1999;Bell et al 2001;Deng et al 2001;Boekemeier et al 2002;Page et al 2002;Kim 2004;Michalski 2004;Kuenzer et al 2006Kuenzer et al , 2007Wessling et al 2008). As reported by DeRosa (2004), 1,060 fires in the United States (US) were recorded from 1990 to (DeRosa 2004.…”

Section: Introductionmentioning

confidence: 78%

Monitoring and analysis of burning in coal tailing dumps: a case study from the Czech Republic

et al. 2014

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The tailings are significant geological environments in mining and industrial regions. They represent special engineering-geological zones of anthropogenic sediments that require specific engineering-geological investigation. In particular, it is important to examine the sites in detail with regard to their potential heterogeneity. The article deals with an important engineering-geological issue of burning in coal mine and coal tailing dumps. A case study was implemented in a tailing dump in Heřma-nice located in Ostrava which is a major industrial city of the Czech Republic. In this urban agglomeration, anthropogenic sediments form 20 % of all foundation soils. Thermometric monitoring in Heřmanice detected a thermally active coal tailing dump with burning as deep as 9 m. The burning is predominantly related to the content of oxygen in the body of the tailing. It belongs to the limiting conditions of the pyrophoric and consequently self-sustained burning. Other factors are sufficient contents and quality of coal mass and capacity to accumulate thermal energy of exothermal reactions. Dynamics of changes in the burning processes were identified in dependence on time, depth and distribution. There was a considerable heterogeneity of thermal activity as for all parameters, and changes were observed from the point of view of time. Considering the depth, burning gradually spread deeper. However, in the depth of 12 m, no significant thermal activity was observed within the overall studied locality. It may be stated that thermal activity is observed as much as 40 % of the studied area. Directionally, there was a progression of the process from west to east. The identified facts may be applied in final designed levels of coal tailing dumps where observational experiences identified intense cooling up to the height of 5 m preventing higher stages of self-ignition process (best situation). Tailing dumps from 5 to 12 m may already be thermally active (meeting other boundary conditions), and in tailing dumps over 12 m, it is clear that there is no thermal activity below 12 m.

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Section: Introductionmentioning

confidence: 78%

Monitoring and analysis of burning in coal tailing dumps: a case study from the Czech Republic

et al. 2014

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“…Thermal anomalies induced by underground coal fires can be extracted from TIR data using an exclusion method 43 , together with field temperature measurements. TIR data are widely used to delineate subtle surface thermal anomalies associated with underground coal fires 44 .…”

Section: Resultsmentioning

confidence: 99%

Application of unmanned aerial vehicle (UAV) thermal infrared remote sensing to identify coal fires in the Huojitu coal mine in Shenmu city, China

Yang

Luo

et al. 2020

Sci Rep

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China is a major coal-producing country that consumes large amounts of coal every year. Due to the existence of many small coal kilns using backward mining methods, numerous worked-out areas have been formed. The coal mines were abandoned with no mitigation, so air penetrates into the roadways and contacts the coal seams; as a result, the residual coal seams spontaneously ignite to form coal fires. These coal fires have burned millions of tons of valuable coal resources and caused serious environmental problems. To implement fire suppression more effectively, coal fire detection is a key technology. In this paper, thermal infrared remote sensing from unmanned aerial vehicle combined with a surface survey is used to identify the range of coal fires in the Huojitu coal mine in Shenmu city. The scopes and locations of the fire zones are preliminarily delineated, which provides an accurate basis for the development of fire suppression projects.

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Coal Fire Study Over East Basuria Colliery

Pal

Vaish

2020

Springer Geophysics

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Detecting coal fires with a neural network to reduce the effect of solar radiation on Landsat Thematic Mapper thermal infrared images

Cited by 15 publications

References 10 publications

Monitoring and analysis of burning in coal tailing dumps: a case study from the Czech Republic

Monitoring and analysis of burning in coal tailing dumps: a case study from the Czech Republic

Application of unmanned aerial vehicle (UAV) thermal infrared remote sensing to identify coal fires in the Huojitu coal mine in Shenmu city, China

Coal Fire Study Over East Basuria Colliery

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