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Tetzlaff, Anke (2004): Coal fire quantification using ASTER, ETM and BIRD satellite instrument data. Dissertation, LMU München: Faculty of Geosciences
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Abstract

Coal fires cause severe environmental and economic problems. Although satellite remote sensing has been used successfully to detect coal fires, a satellite data based concept that can quantify the majority of the detected coal fires is still missing. Recently, the determination of fire radiative energy (FRE) has been introduced as a new remote sensing tool to quantify forest and grassland fires. This thesis tests the concept of remotely measured FRE, with a view to ascertaining its potential applicability to coal fires. It contains an investigation of a new generation of satellite instruments, including the operational Enhanced Thematic Mapper (ETM) instrument, the experimental Bi-spectral InfraRed Detection (BIRD) satellite sensor and the experimental Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), which explores the potential of these sensors to determine coal fire radiative energy (CFRE). Additionally, based on the results of this analysis, the thesis presents a new, automated ETM and ASTER data based algorithm, adapted to quantify coal fires in semi-arid to arid regions in northern China. Field observations carried out in September 2002 and 2003 in three coalfields in northern China (the Wuda, Gulaben and Ruqigou coalfields) demonstrate that coal fire related, surface anomalies are significantly cooler than forest and grassland fires. The theoretical investigation of the ASTER, ETM and BIRD instruments outlines the fact that the thermal infrared (TIR) or mid infrared (MIR) spectral channels of the ASTER, ETM and BIRD instrument are particularly effective in registering these ‘warm spots’, whilst the short wave infrared (SWIR) spectral range is, however, insufficiently sensitive to be able to register spectral coal fire radiances. The commonly used bi-spectral fire quantification method (Dozier, 1981) can be applied to BIRD data in order to quantify relatively large and / or hot coal fires. However, existing FRE retrieval approaches fail to quantify coal fires via ASTER and ETM instrument data. In this thesis, a new CFRE retrieval method is presented, which links the fire and background TIR spectral radiances to the CFRE through an empirical relationship. This newly developed TIR method is applied to visually detected fire clusters from night-time ASTER data, and from both day- and night-time ETM data, taken from the three study coalfields in northern China. The ASTER and ETM CFRE values, calculated via the TIR method, are compared to CFRE estimates from BIRD data, calculated via the existing bi-spectral method. Despite the different spatial resolution and spectral properties of the ETM, ASTER and BIRD instruments, CFRE computed from ASTER, ETM and BIRD data show good correlations with one another. However, CFRE retrievals from daytime data appear to be very undependable to background temperature variations, while CFRE, estimated from night-time data, appears to be relatively stable. A comparison between night-time ETM-derived CFRE and the figures given by local mining authorities for total coal fire induced, coal loss estimates in the Wuda coalfield gives a clear indication that the overall dimension of the coal fire problematic can in fact be approximated via satellite data CFRE retrievals. It is thus expected that CFRE derived from night-time satellite data will become a crucial tool in obtaining reliable, quantitative information for coal fires. A multi-temporal comparison of CFRE retrievals from night-time BIRD and ETM data, covering the Ruqigou and Wuda coalfields, indicates that only major shifts or activity changes in coal fire induced, surface anomalies can be observed by means of these data. These results, which could only partially be verified by field observations, indicate that ETM or BIRD data can be used to monitor major changes in coal fire related, surface anomalies. These data however cannot entirely replace detailed field observations, especially in case of smaller and / or cooler coal fire related, surface anomalies.