TY - JOUR A1 - Neumann, Patrick P. A1 - Lazik, D. A1 - Bartholmai, Matthias T1 - Tomographic reconstruction of soil gas distribution from multiple gas sources based on sparse sampling T2 - IEEE Sensors Journal N2 - A monitoring method is introduced that creates twodimensional (2D) maps of the soil gas distribution. The method combines linear gas sensing technology for in-situ monitoring of gases in soil with the mapping capabilities of Computed Tomography (CT) to reconstruct spatial and temporal resolved gas distribution maps. A weighted iterative algebraic reconstruction method based on Maximum Likelihood with Expectation Maximization (MLEM) in combination with a source-by-source reconstruction approach is introduced that works with a sparse setup of orthogonally-aligned linear gas sensors. The reconstruction method successfully reduces artifact production, especially when multiple gas sources are present, allowing the discrimination between true and non-existing so-called ghost source locations. Experimental validation by controlled field experiments indicates the high potential of the proposed method for rapid gas leak localization and quantification with respect to Pipeline or underground gas storage issues. PB - IEEE - Inst. Electrical Electronics Engineers Inc CY - Hoes Lane, NJ, USA KW - Computed tomography KW - Gas distribution mapping and gas source localization KW - Discrimination of multiple gas sources KW - Distributed linear sensor KW - Membrane-based gas sensing KW - Subsurface monitoring KW - Gas storage areas PY - 2016 UR - https://opus4.kobv.de/opus4-bam/frontdoor/index/index/docId/36228 AN - OPUS4-36228 SN - 1530-437X VL - 16 IS - 11 SP - 4501 EP - 4508 AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany