• Title of article

    A laser scanning-based method for fast estimation of seismic-induced building deformations

  • Author/Authors

    Pesci، نويسنده , , Arianna and Teza، نويسنده , , Giordano and Bonali، نويسنده , , Elena and Casula، نويسنده , , Giuseppe and Boschi، نويسنده , , Enzo، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2013
  • Pages
    14
  • From page
    185
  • To page
    198
  • Abstract
    Monitoring damaged buildings in an area where an earthquake has occurred requires the use of techniques which provide rapid and safe measurements even in emergency conditions. In particular, remote sensing techniques like terrestrial laser scanning (TLS) can satisfy these requirements, since they produce very dense point clouds in little time and also allow an accurate geometric modeling of observed buildings. Nevertheless, strong constraints on TLS data acquisition geometry, such as acquisition distance and incidence angles, typically characterize an area in seismic emergency conditions. In order to correctly interpret the data, it is necessary to estimate errors affecting TLS measurements in these critical conditions. A reliable estimation can be achieved by means of experiments and numerical simulations aimed at quantifying a realistic noise level, with emphasis on reduction of artifacts due to data acquisition, registration and modeling. This paper proposes a data analysis strategy in which TLS-based morphological maps computed as point-to-primitive differences are created. The method can be easily used for accurate surveying in emergency conditions. In order to demonstrate the proposed method in very diverse situations, it was applied to rapidly detect deformation traces in the San Giacomo Roncole Campanile (Modena), the Asinelli tower (Bologna) and the Cantalovo Church (Verona), three buildings damaged by the Mw 5.9 Emilia Romagna 2012 earthquake (Italy).
  • Keywords
    Architecture , Laser scanning , Change detection , Model , Performance
  • Journal title
    ISPRS Journal of Photogrammetry and Remote Sensing
  • Serial Year
    2013
  • Journal title
    ISPRS Journal of Photogrammetry and Remote Sensing
  • Record number

    2229232