Assessing Earthquake-Induced Urban Rubble by Means of Multiplatform Remotely Sensed Data

ISPRS International Journal of Geo-Information

Sergio Cappucci¹  Ludovica Giordano¹  Maurizio Pollino¹  Flavio Borfecchia¹  Vittorio Rosato¹  Danilo Bersan¹  Domenico Iantosca¹  Luigi De Cecco¹ 

[1] ENEA, Italian Agency for New Technologies, Energy and Sustainable Economic Development, Casaccia Research Centre, 000123 Rome, Italy;

关键词: seismic post-emergency;    disaster management;    environmental analysis LiDAR;    remote sensing;    WorldView-3;    COPERNICUS;   

DOI  :  10.3390/ijgi9040262

来源: DOAJ

【 摘 要 】

Earthquake-induced rubble in urbanized areas must be mapped and characterized. Location, volume, weight and constituents are key information in order to support emergency activities and optimize rubble management. A procedure to work out the geometric characteristics of the rubble heaps has already been reported in a previous work, whereas here an original methodology for retrieving the rubble’s constituents by means of active and passive remote sensing techniques, based on airborne (LiDAR and RGB aero-photogrammetric) and satellite (WorldView-3) Very High Resolution (VHR) sensors, is presented. Due to the high spectral heterogeneity of seismic rubble, Spectral Mixture Analysis, through the Sequential Maximum Angle Convex Cone algorithm, was adopted to derive the linear mixed model distribution of remotely sensed spectral responses of pure materials (endmembers). These endmembers were then mapped on the hyperspectral signatures of various materials acquired on site, testing different machine learning classifiers in order to assess their relative abundances. The best results were provided by the C-Support Vector Machine, which allowed us to work out the characterization of the main rubble constituents with an accuracy up to 88.8% for less mixed pixels and the Random Forest, which was the only one able to detect the likely presence of asbestos.

【 授权许可】

Unknown