Time series analysis of L-band PALSAR-2 images in Istanbul and Kocaeli, Turkey

DOI DOI DOI Web Site 参考文献47件 オープンアクセス
  • Sadra Karimzadeh
    Department of Remote Sensing and GIS, University of Tabriz, Tabriz, Iran
  • Abdullah Can Zulfikar
    Disaster Management Institute, Istanbul Technical University, Maslak, Istanbul, Turkey
  • Masashi Matsuoka
    Department of Architecture and Building Engineering, Tokyo Institute of Technology, Yokohama, Japan

書誌事項

公開日
2024-02-29
資源種別
journal article
権利情報
  • http://creativecommons.org/licenses/by/4.0/
DOI
  • 10.1080/20964471.2024.2320466
  • 10.6084/m9.figshare.25314996.v1
  • 10.6084/m9.figshare.25314996
公開者
Informa UK Limited

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説明

Conducting long measurements of infrastructure deformation is a critical engineering task. Conventional methods are both time-consuming and expensive, limiting their use for large-scale applications. The synergy of synthetic aperture radar (SAR) and geographic information systems (GIS) offers a complementary approach. This study focuses on the feasibility of using time series analysis of L-band PALSAR-2 images to discover land displacements in Istanbul and Kocaeli, significant industrial and residential areas in Turkey. PALSAR-2 phase and intensity information were analyzed. For phase analysis, 14 L-band images from 2014 to 2021 were taken into account. Small baseline subset (SBAS) analysis was performed using 44 pairs, and results of the velocity, coherence and backscattering values are presented. Coherence of all pairs and their correlations were calculated. Principal Component Analysis (PCA) reduced the dimension of coherence pairs, enhancing feature extraction and the final geocoded velocity map revealed a fastest subsidence rate of −58 mm/yr and a mean subsidence of −20 mm/yr. These findings were confirmed through mean vertical velocity from Sentinel-1 datasets and field observations. The results showed that immature land subsidence in the mentioned areas are growing slowly, which can be taken as a serious risk in future.

収録刊行物

  • Big Earth Data

    Big Earth Data 8 (3), 467-493, 2024-02-29

    Informa UK Limited

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