Detecting Land Subsidence in Shanghai by PS-Networking SAR Interferometry

Area of Science:

• Geosciences
• Remote Sensing
• Geophysics

Background:

• Satellite Synthetic Aperture Radar (SAR) interferometry faces challenges like temporal decorrelation and atmospheric contamination for deformation mapping.
• Permanent Scatterer (PS) techniques improve analysis by tracking stable radar reflectivity points in time-series SAR images.

Purpose of the Study:

• To develop and apply a PS-neighborhood networking interferometry approach for precise land subsidence detection in Shanghai, China.
• To analyze the spatial and temporal patterns of land subsidence over a 10-year period.

Main Methods:

• Utilized 26 ERS-1/2 SAR images acquired between 1992 and 2002 over Shanghai.
• Implemented a PS-neighborhood networking strategy, connecting adjacent PS points based on a distance threshold.
• Separated linear and nonlinear subsidence, atmospheric effects, and topographic errors.

Main Results:

• Derived a 10-year subsidence velocity field for Shanghai.
• Identified annual subsidence rates varying between -2.1 and -0.6 cm/yr.
• Calculated an average subsidence rate of -1.1 cm/yr for the study area.

Conclusions:

• PS-neighborhood networking interferometry effectively overcomes limitations of traditional SAR interferometry for deformation mapping.
• The study provides crucial data on land subsidence in Shanghai, essential for urban planning and risk assessment.