Detailed hazard identification of urban subsidence in Guangzhou and Foshan by combining InSAR and optical imagery

verfasst von

Yufang He, Mahdi Motagh, Xiaohang Wang, Xiaojie Liu, Hermann Kaufmann, Guochang Xu, Bo Chen

Abstract

Recently Guangzhou and Foshan in China are experiencing significant urbanization and economic development. However, the accelerated urbanization process has contributed significantly to urban land subsidence, causing huge economic losses and endangering safety of infrastructure. This intricate activities on urban surfaces can also lead to pseudo danger in interpreting InSAR-based urban surface deformation, resulting in hazard misidentification in two cities. In order to more accurately identify the hazard of urban surface deformation, we innovatively present a combination of InSAR technology with multi-temporal optical remote sensing data. It can also analyze the specific causes of urban deformation at SAR pixel level in two cities. The SBAS-InSAR method was adopted to obtain an urban subsidence map from 2017 to 2020 based on 110 Sentinel-1 SAR image scenes. To obtain an urban surface change map with a high accuracy, an improved SwiT-UNet++ model was applied based on multi optical Google Earth imagery. By a combined analysis of SAR and optical images, we discovered multiple irregular funnels with subsidence at different scales in both cities, that are mostly relatable to urban surface constructions such as foundation compression, building demolition, and the construction of public facilities. Furthermore, to identify detailed hazard around surface changes, the buffer analysis based on InSAR surface deformation and urban surface change maps was conducted. It revealed the surface deformation signals around certain urban surface change areas are more obvious and pose certain hazard. Finally additional high-risk areas are found in the two cities. By subtracting the optical surface change detection map from the InSAR-based urban subsidence map, the “pseudo danger” caused by urban activities in the interpretation of InSAR-based urban surface deformation is eliminated, enabling precise identification of actual land subsidence hazards. It is realized through a risk assessment experiment in the research area by adding factors of urbanization processes. By combining multiple sources of data and using advanced analytical techniques, we could identify the determining factors contributing to urban subsidence and the detailed hazards and thus, provide valuable information for future urban developments.

Organisationseinheit(en)

Institut für Photogrammetrie und Geoinformation

Externe Organisation(en)

Harbin Institute of Technology
Dongguan University of Technology
Helmholtz-Zentrum Potsdam Deutsches GeoForschungsZentrum (GFZ)
Wuhan University
Lanzhou University of Technology
Shandong University at Weihai
Shenzhen Institute of Advanced Technology
Key Laboratory of Aerospace Remote Sensing Big Data Intelligent Processing and Application of Guang-dong Higher Education

Typ

Artikel

Journal

International Journal of Applied Earth Observation and Geoinformation

Band

135

Anzahl der Seiten

13

ISSN

1569-8432

Publikationsdatum

12.2024

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Globaler Wandel, Erdoberflächenprozesse, Computer in den Geowissenschaften, Management, Monitoring, Politik und Recht

Ziele für nachhaltige Entwicklung

SDG 8 – Anständige Arbeitsbedingungen und wirtschaftliches Wachstum, SDG 11 – Nachhaltige Städte und Gemeinschaften

Elektronische Version(en)

https://doi.org/10.1016/j.jag.2024.104291 (Zugang: Offen)