Assessment of asbestos-cement roof distribution and prioritized intervention approaches through hyperspectral imaging.

ABSTRACT

The discernment of asbestos-cement (AC) roofs within urban areas stands as a pivotal concern pertinent to communal well-being and ecological oversight, particularly in emerging nations where asbestos continues to be extensively employed. Conventional methodologies entailing the recognition of asbestos-cement roofs and the characterization of their degradation status, such as tangible examinations and laboratory assays, prove to be temporally protracted, financially demanding, and arduous to extrapolate comprehensively across expansive urban domains. In this paper, it is presented a novel approach for identifying asbestos-cement roofs in urban areas using hyperspectral airborne acquisition and carry out a diagnosis that allows to identify the state of asbestos-cement roofs and thus provide a tool for the competent authorities to develop and prioritize intervention strategies to mitigate the problem. Four different methodologies were implemented and compared, three of which are new in the literature, to identify the deterioration of asbestos-cement (AC) roof state in large urban areas. This, in turn, furnishes a tool for competent authorities to identify the state of AC roofs, develop and prioritize intervention strategies to mitigate the problem. The control points in field allowed validating the classification and the proposed methodology for the prioritization of intervention in AC roofs. Some neighborhoods in the city showed peaks in the area of asbestos-cement roofs of 47% of the total area of the neighborhood, representing practically all of the roofs present in the neighborhood. On average around 20% of the total area of a neighborhood in Cartagena is covered by AC. Furthermore, it was found a total area of AC roofs throughout the city of more than 9 km2 (9 million square meters). On the other hand, two of the 4 methods used showed encouraging results that demonstrate their ability to identify covers in poor and good condition at a large scale from hyperspectral images. This academic novelty suggests that there is a possibility of practical application of these methods in other urban contexts with high concentrations of AC roofs, helping in the planning and optimization of intervention strategies to mitigate the risk in public and environmental health due to the presence of asbestos.