DocumentCode
2222455
Title
Airborne remote sensing for mapping asbestos roofs in aosta valley
Author
Frassy, Federico ; Candiani, Gabriele ; Maianti, Pieralberto ; Marchesi, Andrea ; Nodari, Francesco Rota ; Rusmini, Marco ; Albonico, Carlo ; Gianinetto, Marco
Author_Institution
Building Environ. Sci. & Technol. (BEST) Dept., Politec. di Milano, Milan, Italy
fYear
2012
fDate
22-27 July 2012
Firstpage
7541
Lastpage
7544
Abstract
This paper describes the use of airborne hyperspectral remote sensing for mapping asbestos roofs in an orographic complex area in Northern Italy, the Aosta Valley. Using training samples collected during field surveys, thematic classification was able to detect the majority of asbestos surfaces. Considering the total amount of asbestos areas validation showed a correct detection of about 80%, while considering the number of asbestos roofs correctly detected this value decreased to 43%. This difference pointed out a clear relationship between data spatial resolution and asbestos roofs area. The study served as a first approach to an extensive use of the remote sensing technology for asbestos mapping over large areas and the encouraging results will support Public Administrations for decision making strategies and policies for their removal.
Keywords
asbestos; geophysical image processing; government policies; image classification; image resolution; object detection; public administration; spectral analysis; terrain mapping; Aosta valley; Northern Italy; airborne hyperspectral remote sensing; asbestos removal policy; asbestos roof mapping; asbestos surface detection; data spatial resolution; decision making strategy; field survey; orographic complex area; public administration; remote sensing technology; thematic classification; Cancer; Hyperspectral imaging; Materials; Strips; Training; Aerial Survey; Asbestos; Hyperspectral; Mapping; Remote Sensing;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location
Munich
ISSN
2153-6996
Print_ISBN
978-1-4673-1160-1
Electronic_ISBN
2153-6996
Type
conf
DOI
10.1109/IGARSS.2012.6351886
Filename
6351886
Link To Document