Post-Disaster Damage Assessment Through Coherent Change Detection on Sar Imagery

Abstract

Damage assessment is a fundamental step to support emergency response and recovery activities in a post-earthquake scenario. In recent years, UAVs and satellite optical imagery was applied to assess major structural damages before technicians could reach the areas affected by the earthquake. However, bad weather conditions may harm the quality of these optical assessments, thus limiting the practical applicability of these techniques. In this paper, the application of Synthetic Aperture Radar (SAR) imagery is investigated and a novel approach to SAR-based damage assessment is presented. Coherent Change Detection (CCD) algorithms on multiple interferometrically pre-processed SAR images of the area affected by the seismic event are exploited to automatically detect potential damages to buildings and other physical structures. As a case study, the 2016 Central Italy earthquake involving the cities of Amatrice and Accumoli was selected. The main contribution of the research outlined above is the integration of a complex process, requiring the coordination of a variety of methods and tools, into a unitary framework, which allows end-to-end application of the approach from SAR data pre-processing to result visualization in a Geographic Information System (GIS). A prototype of this pipeline was implemented, and the outcomes of this methodology were validated through an extended comparison with traditional damage assessment maps, created through photo-interpretation of high resolution aerial imagery. The results indicate that the proposed methodology is able to perform damage detection with a good level of accuracy, as most of the detected points of change are concentrated around highly damaged buildings.

Assessment of Earthquake-Induced Damage Level on Buildings: Analysis of Two Different Survey Methods for a Case Study

“…In cases where it is required to intervene in areas that present problems of security and access, the possibility to define a correct correspondence between rapidity of surveying, accuracy of acquired data and surveying and processing techniques available is a key task. For what concerns the surveying methods, the use of remote-sensing data, such as LiDAR data, GNSS techniques and aerial images, offer a significant approach to BDA after the occurrence of natural or man-made hazard: in this regard, Guida et al (2018), Vetrivel et al (2018), Poli et al (2017) and Quest et al (2016) have offered interesting recent examples of application.…”

Evaluation of Coherent and Incoherent Landslide Detection Methods Based on Synthetic Aperture Radar for Rapid Response: A Case Study for the 2018 Hokkaido Landslides

“…These procedures are usually fast and efficient for rapid responses. When the stack of SAR imagery, which consists of more than three images, is available, the multi-temporal approach can be adopted [11,[28][29][30]. In the multi-temporal approach, the historical and time-series changes induced by the natural phenomena, such as seasonal change, and trend can be extracted and analyzed as well as alleviating the noise.…”