Automatic three-dimensional features extraction: The case study of L'Aquila for collapse identification after April 06, 2009 earthquake

Abstract This paper illustrates an innovative methodology for post-earthquake collapsed building recognition, based on satellite-image classification methodologies and height variation information. Together, the techniques create a robust classification that seems to yield good results in this application field. In the first part of this study, two different feature extraction methodologies were compared, based respectively on pixel-based and object-oriented approaches. Then the classification results of the most accurate classification methodology. obtained on an eight band WorldView-2 monoscopic image, were completed with height variation information before and after the event. The height difference is calculated, comparing a photogrammetric DSM, obtained using a photogrammetric rigorous orbital model on some EROS-B 0.7 metre across-track stereopairs with a ‘roof model’ before the earthquake.

[1]  F. Nex,et al.  UAV for 3D mapping applications: a review , 2014 .

[2]  Carol J. Friedland,et al.  A SURVEY OF UNMANNED AERIAL VEHICLE ( UAV ) USAGE FOR IMAGERY , 2011 .

[3]  Valerio Baiocchi,et al.  Rapid building damage assessment using EROS B data: the case study of L'Aquila earthquake , 2012 .

[4]  Valerio Baiocchi,et al.  DSMs Extraction Methodologies from EROS-B "Pseudo-Stereopairs", PRISM Stereopairs in Coastal and Post-seismic Areas , 2013, ICCSA.

[5]  Valerio Baiocchi,et al.  Three-dimensional multispectral classification and its application to early seismic damage assessment , 2010 .

[6]  Fumio Yamazaki,et al.  Applications of remote sensing and GIS for damage assessment , 2001 .

[7]  Masanobu Shinozuka,et al.  Structural Safety and Reliability , 2000 .

[8]  R. Santamaria,et al.  Increasing Geometric Resolution of Data Supplied by Quickbird Multispectral Sensors , 2013 .

[9]  D. Grigillo,et al.  Automatic extraction and building change detection from digital surface model and multispectral orthophoto , 2011 .

[10]  Valerio Baiocchi,et al.  Development of a Software to Plan UAVs Stereoscopic Flight: An Application on Post Earthquake Scenario in L'Aquila City , 2013, ICCSA.

[11]  Siyka Zlatanova,et al.  Geospatial Information Technology for Emergency Response , 2009 .

[12]  A. A. Tronin,et al.  Remote sensing and earthquakes: A review , 2006 .

[13]  Marco Piras,et al.  Low cost UAV for post-disaster assessment , 2008 .

[14]  V. Singhroy,et al.  Sar integrated techniques for geohazard assessment , 1995 .

[15]  C. Padwick,et al.  WORLDVIEW-2 PAN-SHARPENING , 2010 .

[16]  Valerio Baiocchi,et al.  Test of a building vulnerability model for L’Aquila earthquake , 2012 .

[17]  D. Al-Khudhairy,et al.  Structural Damage Assessments from Ikonos Data Using Change Detection, Object-Oriented Segmentation, and Classification Techniques , 2005 .

[18]  E. Baltsavias,et al.  Automatic Extraction of Man-Made Objects from Aerial and Space Images (II) , 1995 .

[19]  Christian Bignami,et al.  Earthquake Damages Rapid Mapping by Satellite Remote Sensing Data: L'Aquila April 6th, 2009 Event , 2011, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[20]  Henri Eisenbeiss,et al.  Investigation of uav systems and flight modes for photogrammetric applications , 2011 .

[21]  Beniamino Murgante,et al.  High-Detail Damage Pattern in Towns Hit by Earthquakes of the Past: An Approach to Evaluate the Reliability of the Historical Sources , 2014 .

[22]  Sergey V. Samsonov,et al.  A review of the status of satellite remote sensing and image processing techniques for mapping natural hazards and disasters , 2009 .

[23]  Ashbindu Singh,et al.  Review Article Digital change detection techniques using remotely-sensed data , 1989 .

[24]  A. Cracknell.  Review article Synergy in remote sensing-what's in a pixel? , 1998 .

[25]  M. Turker,et al.  Automatic detection of earthquake‐damaged buildings using DEMs created from pre‐ and post‐earthquake stereo aerial photographs , 2005 .

[26]  D. Dominici,et al.  Multispectral automatic feature extraction methodologies comparison , 2014 .

[27]  Piero Boccardo,et al.  Earthquake damage assessment based on remote sensing data. The Haiti case study , 2011 .

[28]  X. Tong,et al.  Building-damage detection using pre- and post-seismic high-resolution satellite stereo imagery: A case study of the May 2008 Wenchuan earthquake , 2012 .

[29]  P. Boccardo.  New perspectives in emergency mapping , 2013 .

[30]  Uwe Weidner.  Digital Surface Models for Building Extraction , 1997 .

[31]  Lorenzo Bruzzone,et al.  Earthquake Damage Assessment of Buildings Using VHR Optical and SAR Imagery , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[32]  Babak Mansouri,et al.  Streamlining Post-Earthquake Data Collection and Damage Assessment for the 2003 Bam, Iran, Earthquake using VIEWS™ (Visualizing Impacts of Earthquakes with Satellites) , 2005 .

[33]  Thierry Toutin,et al.  Review of developments in geometric modelling for high resolution satellite pushbroom sensors , 2012 .

[34]  Thomas Blaschke,et al.  Object based image analysis for remote sensing , 2010 .

[35]  D. Lu,et al.  Change detection techniques , 2004 .