大地测量与地球动力学2024，Vol.44Issue(8)：820-826,7.DOI:10.14075/j.jgg.2023.11.124
基于SBAS-InSAR和PSO-BP模型的鲁南高铁沿线地表沉降监测与预测
Surface Subsidence Monitoring and Prediction along Lunan High Speed Railway Based on SBAS-InSAR and PSO-BP Model
摘要
Abstract
We select 38 views of Sentinel-IA SAR images,and obtain the surface subsidence results within 5 km along the Qufu-Heze section of the Lunan high speed railway using SBAS-InSAR technol-ogy for the period from February 2019 to November 2022.We analyze the distribution characteristics and patterns,and use the PSO-BP model to predict the subsidence of some feature points.The results show that the annual average deformation rate is between-20 and 15 mm/a,the maximum subsid-ence velocity is 25.46 mm/a,and the maximum lifting velocity is 17.43 mm/a within 0.1 km along the high speed railway;the RMSE of the subsidence prediction value obtained by the PSO-BP model ranges from 5.8 to 12.4 mm,which can predict the surface subsidence well.关键词
鲁南高铁/SBAS-InSAR/PSO-BP模型/地表沉降/沉降预测Key words
Lunan high speed railway/SBAS-InSAR/PSO-BP model/surface subsidence/subsidence prediction分类
天文与地球科学引用本文复制引用
何虎振,刘国林,王凤云,陶秋香..基于SBAS-InSAR和PSO-BP模型的鲁南高铁沿线地表沉降监测与预测[J].大地测量与地球动力学,2024,44(8):820-826,7.基金项目
山东省自然科学基金(ZR2020MD043,ZR2020MD044) （ZR2020MD043,ZR2020MD044）
国家自然科学基金(42074009). Natural Science Foundation of Shandong Province,No.ZR2020MD043,ZR2020MD044 （42074009）
National Natural Science Foundation of China,No.42074009. （）
