Abstract
Being built on the reclamation area, Shanghai Pudong International Airport (SPIA) has been undergoing uneven subsidence since the beginning of its operation in 1999. In order to explore the evolution characteristics of ground deformation in the SPIA reclamation area and further provide assurance for the airport’s safe operation, 141 Sentinel-1A images from October 2016 to September 2021 were selected to acquire time-series ground deformation observations by the StaMPS PSI processing procedure. We subsequently built a ground deformation prediction model using the Long Short Term Memory (LSTM) neural network for the short-term prediction of the SPIA deformation severity area. On this basis, the spatial-temporal evolution trends of SPIA ground deformation in the reclamation area were revealed concerning the influence and mode of action of geological conditions and environmental factors. Finally, we proposed targeted recommendations and strategies for the comprehensive ground deformation prevention and control needs of SPIA. The results indicated that the SPIA exhibits overall subsidence in the eastern part, with the maximum deformation rate reaching −57.29 mm/a. Meanwhile, the central and western part has a local uplift with the maximum deformation rate reaching 32.76 mm/a. The proposed LSTM ground deformation prediction model demonstrated excellent robustness in the region of uneven deformation, and the prediction results were in high agreement with the StaMPS PSI monitoring results. The time-series observations and prediction results are expected to provide references for the expansion project of SPIA and help the research of ground deformation and prevention in related fields.
Highlights
With the rapid socio-economic development, many coastal cities have resorted to reclamation to alleviate the shortage of land for urban construction and transportation [1,2,3]
For revealing the ground deformation evolution characteristics of the Shanghai Pudong International Airport (SPIA) reclamation area in recent years, this paper carried out the prediction of deformation evolution and subsidence pattern analysis of SPIA by the long time-series ground deformation observations acquired with the Stanford Method for Persistent Scatterers (StaMPS) Persistent Scatterer Interferometry (PSI)
The output of the Long Short Term Memory (LSTM) network at the t − 1 layer is represented by ht−1, and xt represents the input vector
Summary
With the rapid socio-economic development, many coastal cities have resorted to reclamation to alleviate the shortage of land for urban construction and transportation [1,2,3]. Used an improved PSI technique to invert the mean deformation rate and SPIA ground deformation; they performed time-series deformation analysis using the high-resolution. With the rapid development of the above-mentioned TS-InSAR technology in reclamation airports’ ground deformation, monitoring data characterized by dense time series are becoming more and more available, making it possible to predict the ground deformation of reclamation airports. For revealing the ground deformation evolution characteristics of the SPIA reclamation area in recent years, this paper carried out the prediction of deformation evolution and subsidence pattern analysis of SPIA by the long time-series ground deformation observations acquired with the StaMPS PSI.
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