Paper
26 August 2020 Satellite imagery segmentation in lignite mine areas
Author Affiliations +
Proceedings Volume 11524, Eighth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2020); 115240F (2020) https://doi.org/10.1117/12.2570751
Event: Eighth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2020), 2020, Paphos, Cyprus
Abstract
Lignite mining in Greece has been a huge industry. Especially, in the extraction site of Western Macedonia many villages were relocated due to the site's spatial growth. Public Power Corporation (PPC) SA Ptolemaida lignite mine is the biggest in Balkans that contributes significantly to country's electricity production. This paper aims at formulating a methodological procedure in order to delineate rapidly the lignite coal mine boundaries through an object based image analysis, in Orfeo ToolBox and QGIS. Site boundaries can be modified through expansion of mining activities or unexpectedly due to a natural disaster. For that reason, a Sentinel-2A imagery was obtained and three frequent segmentation approaches were applied including MeanShift, Watershed and Morphological profiles, from a notable remote sensing open source package (Orfeo Toolbox). Following various tests, the optimal parameters for each segmentation algorithm are presented alongside with the corresponding results regarding lignite mine area boundaries delineation. In addition, the proposed methodological framework may apply to different environmental subjects monitoring including large constructions, mineral extraction, landfills and archaeological sites.
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Ioannis Kotaridis and Maria Lazaridou "Satellite imagery segmentation in lignite mine areas", Proc. SPIE 11524, Eighth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2020), 115240F (26 August 2020); https://doi.org/10.1117/12.2570751
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KEYWORDS
Image segmentation

Mining

Satellites

Earth observing sensors

Image processing algorithms and systems

Satellite imaging

Image processing

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