Exploiting SAR and VHR Optical Images to Quantify Damage Caused by the 2003 Bam Earthquake

被引:110
作者
Chini, Marco [1 ]
Pierdicca, Nazzareno [2 ]
Emery, William J. [3 ]
机构
[1] INGV, I-00143 Rome, Italy
[2] Univ Roma La Sapienza, Dept Elect Engn, I-00184 Rome, Italy
[3] Univ Colorado, Colorado Ctr Astrodynam Res, Boulder, CO 80309 USA
来源
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 2009年 / 47卷 / 01期
关键词
Damage detection; earthquake; synthetic aperture radar (SAR); very high resolution (VHR) optical image; RESOLUTION SATELLITE IMAGES; URBAN AREAS; CLASSIFICATION;
D O I
10.1109/TGRS.2008.2002695
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Using satellite sensors to detect urban damage and other surface changes due to earthquakes is gaining increasing interest. Optical images at different resolutions and radar images represent useful tools for this application, particularly when more frequent revisit times will be available with the implementation of new missions and future possible constellations of satellites. Very high resolution (VHR) images (on the order of 1 m or less) may provide information at the scale of a single building, whereas images at resolutions on the order of tens of meters may give indications of damage levels at a district scale. Both types of information may be extremely important if provided with sufficient timeliness to rescue teams. The earthquake that hit the city of Bam, Iran, has been taken as a test case, where QuickBird VHR optical images and advanced synthetic aperture radar data were available both before and after the event. Methods to process these data in order to detect damage and to extract features used to estimate damage levels are investigated in this paper, pointing out the significant potential of these satellite data and their possible synergy.
引用
收藏
页码:145 / 152
页数:8
相关论文
共 27 条
  • [1] [Anonymous], 2003, Morphological Image Analysis: Principles and Applications
  • [2] AOKI H, 1998, P 19 AS C REM SENS C, V7, P1
  • [3] Classification of hyperspectral data from urban areas based on extended morphological profiles
    Benediktsson, JA
    Palmason, JA
    Sveinsson, JR
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2005, 43 (03): : 480 - 491
  • [4] Classification and feature extraction for remote sensing images from urban areas based on morphological transformations
    Benediktsson, JA
    Pesaresi, M
    Arnason, K
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2003, 41 (09): : 1940 - 1949
  • [5] Chesnel AL, 2007, INT GEOSCI REMOTE SE, P3736
  • [6] Chestnut-Andrews A., 2007, Pedagogical content knowledge and scaffolds: Measuring teacher knowledge of equivalent fractions in a didactic setting, P1
  • [7] Uplift and subsidence due to the 26 December 2004 Indonesian earthquake detected by SAR data
    Chini, M.
    Bignami, C.
    Stramondo, S.
    Pierdicca, N.
    [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 2008, 29 (13) : 3891 - 3910
  • [8] Comparing statistical and neural network methods applied to very high resolution satellite images showing changes in man-made structures at rocky flats
    Chini, Marco
    Pacifici, Fabio
    Emery, William J.
    Pierdicca, Nazzareno
    Del Frate, Fabio
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2008, 46 (06): : 1812 - 1821
  • [9] Decision fusion for the classification of urban remote sensing images
    Fauvel, Mathieu
    Chanussot, Jocelyn
    Benediktsson, Jon Atli
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2006, 44 (10): : 2828 - 2838
  • [10] A new statistical similarity measure for change detection in multitemporal SAR images and its extension to multiscale change analysis
    Inglada, Jordi
    Mercier, Gregoire
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2007, 45 (05): : 1432 - 1445