Ground deformation analysis using InSAR and backpropagation prediction with influencing factors in Erhai Region, China

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Abstract

The long continuity of Interferometric Synthetic Aperture Radar (InSAR) can provide high space and resolution data for ground deformation investigations. The ground deformation in this paper appeared in the city's development, although it is close to the Erhai region, which is different from a water-deficient city. Therefore, the analysis and prediction of ground deformation using a new method is required. In this study, Sentinel-1 Synthetic Aperture Radar (SAR) images from 2015 to 2018 were used to study the characteristics of ground deformation in the Erhai region using the Small Baseline Subset Interferometric SAR (SBAS-InSAR) technique. The results were cross-validated using ascending and descending direction images to ensure the accuracy. In addition, the results showed that there was little ground deformation in the northern part of the Erhai region, while there was obvious ground deformation in the southern part. Four influencing factors-including the building area, water level, cumulative precipitation, and cumulative temperature of the southern Erhai region-were used together to predict the cumulative ground deformation using back-propagation (BP). The R of all the involved data was 0.966, and the root mean square errors (RMSEs) between the simulated values using BP and the true measured values were 3.063, 1.003, and 1.119, respectively. The results showed that BP has great potential in predicting the change tendency of ground deformation with high precision. The main reason for ground deformation is the continuous increase of building area; the water level followed. The cumulative precipitation and cumulative temperature are the reasons for the seasonal ground deformation. Some countermeasures and suggestions are given to face the challenge of serious ground deformation.

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Wang, Y., Guo, Y., Hu, S., Li, Y., Wang, J., Liu, X., & Wang, L. (2019). Ground deformation analysis using InSAR and backpropagation prediction with influencing factors in Erhai Region, China. Sustainability (Switzerland), 11(10). https://doi.org/10.3390/su11102853

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