摘要
Abstract
In order to monitor the settlement status of Shanghai Pudong International Airport(SPIA)and improve the prediction accuracy of the long short-term memory(LSTM)model,this paper obtained the time-series settlement information of SPIA from September 2020 to August 2023 based on the small baseline subset-interferometric synthetic aperture radar(SBAS-InSAR)technique and 32-view Sentinel-1A images.The walrus optimization algorithm(WaOA)-LSTM settlement prediction model optimized based on WaOA was constructed,and the prediction results were compared with the InSAR monitoring values.The results show that the maximum settlement rate of SPIA in the past three years is-52.21 mm/a,and the maximum cumulative settlement reaches-159.30 mm.The settlement is mainly concentrated in the reclaimed area of runways No.2,4,and 5,among which the berm area around the northern part of runway No.5 and the coastal embankment area are the most serious.The root-mean-square error(RMSE)of the predicted value by the WaOA-LSTM model and the real monitoring value is 2.63 mm,and the mean absolute error(MAE)is 2.06 mm,which are 52.87%and 53.29%higher than those of the traditional LSTM model,respectively.The results of the study provide a reference for the safe operation of SPIA.关键词
短基线集合成孔径雷达干涉测量(SBAS-InSAR)/沉降监测/上海浦东国际机场(SPIA)/海象优化算法(WaOA)/长短时记忆(LSTM)Key words
small baseline subset-interferometric synthetic aperture radar(SBAS-InSAR)/settlement monitoring/Shanghai Pudong International Airport(SPIA)/walrus optimization algorithm(WaOA)/long short-term memory(LSTM)分类
天文与地球科学
