The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLII-3/W3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W3, 129–136, 2017
https://doi.org/10.5194/isprs-archives-XLII-3-W3-129-2017
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W3, 129–136, 2017
https://doi.org/10.5194/isprs-archives-XLII-3-W3-129-2017

  19 Oct 2017

19 Oct 2017

TEMPERATURE – EMISSIVITY SEPARATION ASSESSMENT IN A SUB-URBAN SCENARIO

M. Moscadelli1, M. Diani2, and G. Corsini1 M. Moscadelli et al.
  • 1Dipartimento di Ingegneria dell'Informazione, Università di Pisa, Via Caruso 16, 56122 Pisa, Italy
  • 2Accademia Navale, Viale Italia 72, 57127 Livorno, Italy

Keywords: Temperature and Emissivity Separation (TES), Thermal InfraRed (TIR), Surface Emissivity, Surface Temperature, Airborne Surveillance, Material Identification

Abstract. In this paper, a methodology that aims at evaluating the effectiveness of different TES strategies is presented. The methodology takes into account the specific material of interest in the monitored scenario, sensor characteristics, and errors in the atmospheric compensation step. The methodology is proposed in order to predict and analyse algorithms performances during the planning of a remote sensing mission, aimed to discover specific materials of interest in the monitored scenario. As case study, the proposed methodology is applied to a real airborne data set of a suburban scenario. In order to perform the TES problem, three state-of-the-art algorithms, and a recently proposed one, are investigated: Temperature-Emissivity Separation '98 (TES-98) algorithm, Stepwise Refining TES (SRTES) algorithm, Linear piecewise TES (LTES) algorithm, and Optimized Smoothing TES (OSTES) algorithm. At the end, the accuracy obtained with real data, and the ones predicted by means of the proposed methodology are compared and discussed.