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.

Airborne remote sensing for mapping asbestos roofs in Aosta Valley

FRASSY, FEDERICO;CANDIANI, GABRIELE;MAIANTI, PIERALBERTO;MARCHESI, ANDREA;ROTA NODARI, FRANCESCO;RUSMINI, MARCO;GIANINETTO, MARCO
2012-01-01

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.
2012 IEEE International Geoscience And Remote Sensing Symposium (IGARSS)
978-1-4673-1159-5
Hyperspectral; Aerial Survey; Remote Sensing; Asbestos; Mapping
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/686915
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