Presentation + Paper
20 September 2020 Monitoring of soil movement in a self-burning coal waste pile with UAV imagery
Author Affiliations +
Abstract
The São Pedro da Cova coal mine, in Gondomar (Portugal), left a substantial ecological footprint in the form of a 28,000 m2 waste pile. This waste pile has been undergoing continuous self-combustion since 2005, leading to the mobilization of pollutants. As a result, it is of vital importance to monitor the condition and evolution of the waste pile, to assess the current and potential risks posed to the inhabitants and to propose adequate mitigation measures. To evaluate and monitor the waste pile surface soil movements, a comparison between different digital elevation models (DEM) was performed. The DEMs were obtained from photogrammetric processing of data collected by different sensors onboard of an unmanned aerial vehicle (UAV). As preliminary results, the waste pile seems to be suffering a generalized topographic recession, verified by the elevation decrease on multiple monitoring points, this effect may be caused by soil erosion or subsidence, potentially caused by the coal fires that have been active in this waste pile. As part of a larger evaluation of the study area within the CoalMine Project, which includes geochemical soil and water analysis, as well as, monitoring of the surface temperatures, the current assessment of soil movement provides crucial insight into the movement and deposit of soil in addition to the potential contaminants present in its composition.
Conference Presentation
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ana C. Teodoro, João Fernandes, Patrícia Santos, Lia Duarte, Jóse Alberto Gonçalves, and Deolinda Flores "Monitoring of soil movement in a self-burning coal waste pile with UAV imagery", Proc. SPIE 11534, Earth Resources and Environmental Remote Sensing/GIS Applications XI, 115340O (20 September 2020); https://doi.org/10.1117/12.2574059
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CITATIONS
Cited by 1 scholarly publication.
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KEYWORDS
Unmanned aerial vehicles

Soil contamination

Soil science

Cameras

Vegetation

RGB color model

Sensors

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