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Yousefi, B., Sojasi, S., Castanedo, C.I., Beaudoin, G., Huot, F., Xavier, P.V., Maldague, X., Chamberland, M. and Lalonde, E. (2016) Mineral Identification in Hyperspectral Imaging Using Sparse-PCA. Proc. SPIE 9861, Thermosense: Thermal Infrared Applications XXXVIII, Baltimore, 11 May 2016, 986118.
https://doi.org/10.1117/12.2224393

has been cited by the following article:

• TITLE: Using Longwave Infrared Hyperspectral Imaging for a Quantitative Atmospheric Tracer Monitoring in Outdoor Environments

  AUTHORS: Eitan Hirsch, Eyal Agassi, Alon Manor

  KEYWORDS: Hyperspectral, Infrared, Gaseous Plumes, Concentration-Length, Quantification, Atmospheric Transport and Diffusion (T&D) Model

  JOURNAL NAME: International Journal of Geosciences, Vol.12 No.3, March 22, 2021

  ABSTRACT: Quantitative real-time retrieval of concentration-lengths (CL) through gaseous plumes is an important tool for environmental monitoring, enabling remote monitoring of emissions from industrial facilities and risk assessment in scenarios of toxic gas releases. The adoption of LWIR (Long Wave InfraRed) hyperspectral imaging as a leading technique for remote gas plume detection paved the way for an introduction of a precise CL estimation and two-dimensional (2D) mapping. A novel methodology for evaluating and characterizing the performance of a retrieval algorithm is presented. The algorithm utilizes state-of-the-art retrieved hyperspectral 2D mapping and is applied on a series of localized atmospheric tracer gas (SF6) releases in monitored environmental conditions. The retrieved CL distributions are compared to a numeric atmospheric T&D (Transport and Diffusion) model. Satisfactory agreement between retrieved and simulated CL prediction is manifested, and the uncertainty involved is quantified. Possible sources for the remained discrepancies between retrieved and simulated CL values are characterized, and methods to minimize them are discussed.