DocumentCode :
1922989
Title :
Hyperspectral remote sensing data to map hazardous materials in a rural and industrial district: The Podgorica dwellings case studies
Author :
Cavalli, Rosa Maria ; Pascucci, Simone ; Pignatti, Stefano
Author_Institution :
Inst. of Atmos. Pollution, Italian Nat. Res. Council, Rome, Italy
fYear :
2009
fDate :
26-28 Aug. 2009
Firstpage :
1
Lastpage :
4
Abstract :
In this paper, we present the results of a hyperspectral airborne and in situ campaign in Montenegro aimed at individuating and monitoring two hazardous materials. They are the residues of the bauxite processing, i.e. red mud, and the asbestos fibers applied in the building materials. We perform laboratory analyses of asbestoscement, red mud and soil samples collected in the study area for (a) recognizing the dominant minerals using XRay Diffraction and X-Ray Fluorescence; (b) identifying the optical characteristics of the samples using a portable field spectrometer; and (c) characterizing their spectral features and remote sensing detection requirements. A least-squares fitting procedure, on the basis of the significant red mud and asbestos-cement reflectance spectral features, was applied to airborne hyperspectral remote sensing data collected over the study area. Results show that hyperspectral remote sensing data can provide an efficient, fast and repeatable tool for mapping and monitoring the diffusion of pollutants providing the location of the hazardous areas to be checked.
Keywords :
X-ray diffraction; X-ray fluorescence analysis; asbestos; cements (building materials); geology; geophysical signal processing; hazardous materials; least squares approximations; object detection; remote sensing; Montenegro; Podgorica dwelling case study; airborne hyperspectral remote sensing data; asbestos fiber; bauxite processing; hazardous material; industrial district; least-squares fitting procedure; portable field spectrometer; red mud; rural district; spectral feature characterization; x-ray diffraction; x-ray fluorescence; Building materials; Character recognition; Hazardous materials; Hyperspectral imaging; Hyperspectral sensors; Laboratories; Performance analysis; Remote monitoring; Remote sensing; Soil; Hyperspectral data; XRD; XRF; asbestos; red mud; spectral feature analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2009. WHISPERS '09. First Workshop on
Conference_Location :
Grenoble
Print_ISBN :
978-1-4244-4686-5
Electronic_ISBN :
978-1-4244-4687-2
Type :
conf
DOI :
10.1109/WHISPERS.2009.5289026
Filename :
5289026
Link To Document :
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