Mapping Asbestos-Cement Roofing with Hyperspectral Remote Sensing over a Large Mountain Region of the Italian Western Alps

Sensors

Federico Frassy³  Gabriele Candiani¹  Marco Rusmini⁴  Pieralberto Maianti³  Andrea Marchesi³  Francesco Rota Nodari³  Giorgio Dalla Via³  Carlo Albonico² 

[1] Optical Remote Sensing Group, IREA-CNR, Via Bassini 15, Milano 20133, Italy; E-Mail:;ARPA Valle d'Aosta, Loc. Grande Charrière, 44, Saint-Christophe (AO) 11020, Italy; E-Mail:;Laboratory of Remote Sensing (L@RS), Politecnico di Milano—Department of Architecture, Built Environment and Construction Engineering (ABC), Via Ponzio 31, Milano 20133, Italy; E-Mails:;ERM Italia S.p.A., Via San Gregorio 38, Milano 20124, Italy; E-Mail:

关键词: asbestos-cement;    hyperspectral;    remote sensing;    mapping;   

DOI  :  10.3390/s140915900

来源: mdpi

【 摘 要 】

The World Health Organization estimates that 100 thousand people in the world die every year from asbestos-related cancers and more than 300 thousand European citizens are expected to die from asbestos-related mesothelioma by 2030. Both the European and the Italian legislations have banned the manufacture, importation, processing and distribution in commerce of asbestos-containing products and have recommended action plans for the safe removal of asbestos from public and private buildings. This paper describes the quantitative mapping of asbestos-cement covers over a large mountainous region of Italian Western Alps using the Multispectral Infrared and Visible Imaging Spectrometer sensor. A very large data set made up of 61 airborne transect strips covering 3263 km² were processed to support the identification of buildings with asbestos-cement roofing, promoted by the Valle d'Aosta Autonomous Region with the support of the Regional Environmental Protection Agency. Results showed an overall mapping accuracy of 80%, in terms of asbestos-cement surface detected. The influence of topography on the classification's accuracy suggested that even in high relief landscapes, the spatial resolution of data is the major source of errors and the smaller asbestos-cement covers were not detected or misclassified.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.