Remote Sensing of Environment | 2019

A multi-disciplinary approach for the damage analysis of cultural heritage: The case study of the St. Gerlando Cathedral in Agrigento

 
 
 
 
 
 

Abstract


Abstract Protocols for structural safety assessment methods for Cultural Heritage assets affected by ground instability phenomena have still not been standardized. Accordingly, huge attention is directed towards the development of innovative and reliable approaches for the damage analysis of the Cultural Heritage assets. Within this framework, this paper deals with an integrated approach for the combination of deformation time series, derived from the Tomographic processing of X-Band Synthetic Aperture Radar (SAR) data acquired by the Italian COSMO-SkyMed satellite constellation, with ground-based measurements obtained by in-situ survey, laser scanner acquisition and structural analysis. The approach exploits satellite deformation measurements to validate the first interpretation of the structural behaviour of a construction threatened by ground instability based on visual inspection and the analysis of the crack pattern, when geotechnical studies and interpretation, as well as in-situ monitoring systems, are not available. The methodology has been tested on the St. Gerlando Cathedral, located on the westernmost and highest area of the Agrigento hill. The Cathedral is affected by complex ground instability phenomena, that have led to several and continuous cracks over centuries. The spatially dense Tomographic SAR measurements allows accessing differential displacement trends in the different sections of the Cathedral and thereby analyzing the overall kinematic behavior of such a complex and heterogeneous structure. This provides essential information for the definition of the structural models, which are fundamental to better understand the behavior and damage evolution of structures subject to ground instabilities and consequently address the most suitable restoration actions.

Volume 235
Pages 111464
DOI 10.1016/j.rse.2019.111464
Language English
Journal Remote Sensing of Environment

Full Text