Contributions to Books:

C. Künzer, J. Zhang, A. Tetzlaff, S. Voigt, W. Wagner:
"Automated Demarcation, Detection, and Quantification of Coal Fires in China Using Remote Sensing Data";
in: "Spontaneous coal seam fires: Mitigating a global disaster. International Research for sustainable control and management. ERSEC Ecological Book Series - 4", issued by: UNESCO Office Beijing; Tsinghua University Press and Springer Verlag, Beijing, 2007, 423 - 445.

English abstract:
This paper briefly summarizes the results of three PhD theses completed as part of the Sino-German Coal Fire Research Initiative "Innovative Technologies for Exploration, Extinction, and Monitoring of Coal Fires in North China." They had a common topic - the analysis of coal fire areas based on remote sensing data. The first work focused on the automated demarcation of coal fire risk areas. The second investigated methods to detect subtle thermal anomalies from
thermal remote sensing data. The third dealt with thermal anomaly quantification of coal fires. Compared to remote sensing-based coal fire research before 2001, a major challenge in these works was the development of automated analysis methods. These methods had to be applicable on a large spatial scale so as to provide a basis for a coal fire monitoring system covering extensive areas in northern China as well as transfer regions. The major sensors providing multispectral
and thermal data were the common earth-observing satellites Landsat 5 TM, 7 ETM+, the US-Japanese ASTER satellite, the German experimental satellite BIRD, as well as the US sensor MODIS. The coal fire risk area demarcation algorithm was based on a multi-spectral knowledge-based test sequence, which automatically extracted land cover surfaces with increased likelihood of hosting coal fires. The algorithm for thermal anomaly extraction from thermal data bands employed a moving window approach to extract subtle local thermal anomalies based on filter-window histogram analysis. The quantification algorithm linked thermal radiance received at the satellite sensor with the energy release of a pixel through a linear relationship. All three algorithms allowed large-scale data processing and spatial transfer of results.

remote sensing, thermal anomalies, coal fire, Landsat, gas emission, quantification

Created from the Publication Database of the Vienna University of Technology.