Multi-Temporal Insar and Target Detection with COSMO-SkyMed SAR Big Data to Monitor Urban Dynamics in Wuhan (China)
- Resource Type
- Conference
- Authors
- Tapete, Deodato; Cigna, Francesca; Balz, Timo; Tanveer, Hashir; Wang, Jinghui; Jiang, Haonan
- Source
- 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS Geoscience and Remote Sensing Symposium IGARSS , 2021 IEEE International. :3793-3796 Jul, 2021
- Subject
- Aerospace
Geoscience
Photonics and Electrooptics
Signal Processing and Analysis
Deformable models
Bridges
Urban areas
Time series analysis
Dynamics
Traffic control
Market research
InSAR
moving target detection
subsidence
traffic patterns
Wuhan
- Language
- ISSN
- 2153-7003
An unprecedented time series of 293 COSMO-SkyMed StripMap SAR images acquired in 2011–2020 is exploited to investigate land subsidence and vehicle traffic in Wuhan, China. Persistent Scatterer Interferometry using linear and non-linear deformation models suggests that the spatial and temporal evolution of subsidence relates with the dynamic urban development across the main city districts. Traffic patterns along bridges were captured by detecting vehicles based on their azimuth shift caused by their across-track motion, and identified by type based on their radar cross section and speed. The results of vehicle counting confirm an increasing number of vehicles over the last years, which is currently an urban challenge for Wuhan.