Damage assessment in urban areas using post-earthquake airborne PolSAR imagery

被引:59
|
作者
Zhao, Lingli [1 ]
Yang, Jie [1 ]
Li, Pingxiang [1 ]
Zhang, Liangpei [1 ]
Shi, Lei [1 ]
Lang, Fengkai [1 ]
机构
[1] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Hubei, Peoples R China
基金
中国国家自然科学基金;
关键词
HIGH-RESOLUTION SAR; BUILDING-DAMAGE; 2003; BAM; CLASSIFICATION; RADAR; DECOMPOSITION; TERRAIN; MODEL; IRAN;
D O I
10.1080/01431161.2013.860566
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Synthetic aperture radar (SAR) has often been used in earthquake damage assessment due to its extreme versatility and almost all-weather, day-and-night capability. In this article, we demonstrate the potential to use only post-event, high-resolution airborne polarimetric SAR (PolSAR) imagery to estimate the damage level at the block scale. Intact buildings with large orientation angles have a similar scattering mechanism to collapsed buildings; they are all volume-scattering dominant and reflection asymmetric, which seriously hampers the process of damage assessment. In this article, we propose a new damage assessment method combining polarimetric and spatial texture information to eliminate this deficiency. In the proposed method, the normalized circular-pol correlation coefficient is used first to identify intact buildings aligned parallel with the flight direction of the radar. The homogeneity' feature of the grey-level co-occurrence matrix (GLCM) is then introduced to distinguish building patches with large orientation angles from the severely damaged class. Furthermore, a new damage assessment index is also introduced to handle the assessment at the level of the block scale. To demonstrate the effectiveness of the proposed approach, the high-resolution airborne PolSAR imagery acquired after the earthquake that hit Yushu County, Qinghai Province of China, is investigated. By comparison with the damage validation map, the results confirm the validity of the proposed method and the advantage of further improving the assessment accuracy without external ancillary optical or SAR data.
引用
收藏
页码:8952 / 8966
页数:15
相关论文
共 50 条
  • [21] Earthquake and post-earthquake vulnerability assessment of urban gas pipelines network
    Saeideh Farahani
    Ahmad Tahershamsi
    Behrouz Behnam
    Natural Hazards, 2020, 101 : 327 - 347
  • [22] Earthquake and post-earthquake vulnerability assessment of urban gas pipelines network
    Farahani, Saeideh
    Tahershamsi, Ahmad
    Behnam, Behrouz
    NATURAL HAZARDS, 2020, 101 (02) : 327 - 347
  • [23] A framework for automated assessment of post-earthquake building damage using geospatial data
    Dong, Pinliang
    Guo, Huadong
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2012, 33 (01) : 81 - 100
  • [24] Single Post-event PolSAR Data Based Earthquake/Tsunami Damage Information Extraction in Urban Areas
    Ji, Y. Q.
    Sumantyo, J. T. Sri
    Chua, M. Y.
    Waqar, M. M.
    2018 PROGRESS IN ELECTROMAGNETICS RESEARCH SYMPOSIUM (PIERS-TOYAMA), 2018, : 899 - 904
  • [25] Image classification on Post-Earthquake damage assessment: A case of the 2023 Kahramanmaras,earthquake
    Ozman, Gizem Ozerol
    Selcuk, Semra Arslan
    Arslan, Abdussamet
    ENGINEERING SCIENCE AND TECHNOLOGY-AN INTERNATIONAL JOURNAL-JESTECH, 2024, 56
  • [26] POST-EARTHQUAKE DAMAGE ASSESSMENT OF MOMENT RESISTING STEEL FRAMES
    Bernuzzi, Claudio
    Rodigari, Davide
    Simoncelli, Marco
    INGEGNERIA SISMICA, 2019, 36 (04): : 34 - 56
  • [27] Post-earthquake damage assessment of moment resisting steel frames
    Bernuzzi, Claudio
    Rodigari, Davide
    Simoncelli, Marco
    Ingegneria Sismica, 2019, 36 (04): : 35 - 55
  • [28] MEMS-based sensors for post-earthquake damage assessment
    Pozzi, M.
    Zonta, D.
    Trapani, D.
    Athanasopoulos, N.
    Amditis, A. J.
    Bimpas, M.
    Garetsos, A.
    Stratakos, Y. E.
    Ulieru, D.
    9TH INTERNATIONAL CONFERENCE ON DAMAGE ASSESSMENT OF STRUCTURES (DAMAS 2011), 2011, 305
  • [29] Few-Shot Learning for Post-Earthquake Urban Damage Detection
    Koukouraki, Eftychia
    Vanneschi, Leonardo
    Painho, Marco
    REMOTE SENSING, 2022, 14 (01)
  • [30] Post-earthquake damage assessment for RC columns using crack image complexity measures
    Sara Jamshidian
    Mohammadjavad Hamidia
    Bulletin of Earthquake Engineering, 2023, 21 : 6029 - 6063