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23 October 2015 Advanced DInSAR analysis for building damage assessment in large urban areas: an application to the city of Roma, Italy
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Abstract
Remote sensing data play an important role for the environmental monitoring because they allow to provide systematic information on very large areas and for a long period of time. Such information must be analyzed, validated and incorporated into proper modeling tools in order to become useful for performing risk assessment analysis. These approaches has been already applied in the field of natural hazard evaluation (i.e. for monitoring seismic, volcanic areas and landslides). However, not enough attention has been devoted to the development of validated methods for implementing quantitative analysis on civil structures.

This work is dedicated to the comprehensive utilization of ERS / ENVISAT data store ESA SAR used to detect deformation trends and perform back-analysis of the investigated structures useful to calibrate the damage assessment models. After this preliminary analysis, SAR data of the new satellite mission (ie Cosmo SkyMed) were adopted to monitor the evolution of existent surface deformation processes and to detect new occurrence. The specific objective was to set up a data processing and data analysis chain tailored on a service that sustains the safe maintenance of the built-up environment, including critical construction such as public (schools, hospital, etc), strategic (dam, highways, etc) and also the cultural heritage sites.

The analysis of the test area, in the southeastern sector of Roma, has provided three different levels and sub-levels of products from metropolitan area scale (territorial analysis), settlement scale (aggregated analysis) to single structure scale (damage degree associated to the structure).
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Peppe J. V. D'Aranno, Maria Marsella, Silvia Scifoni, Marianna Scutti, Alberico Sonnessa, and Manuela Bonano "Advanced DInSAR analysis for building damage assessment in large urban areas: an application to the city of Roma, Italy", Proc. SPIE 9642, SAR Image Analysis, Modeling, and Techniques XV, 96420L (23 October 2015); https://doi.org/10.1117/12.2194808
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