摘要:
地面沉降是京津冀地区常见的地质灾害之一,地面不均匀沉降对于明长城的保护存在着潜在威胁,从而造成不可逆转的损失。文章采用2016—2018年的53景Sentinel-1数据,基于永久散射体合成孔径雷达干涉测量(persistent scatterer interferometric synthetic aperture Radar,PS-InSAR)和小基线集(small baseline subsets,SBAS)技术获取秦皇岛段明长城地表形变信息。将合成孔径雷达(synthetic aperture Radar,SAR)数据基于不同的处理方法获取的形变结果进行交叉验证检验监测结果的精度,得到两者数据线性相关性R2达到0.81。结合地下水水位变化、地质构造、地层岩性数据、土地利用数据及高速公路铁路分布等辅助数据,对明长城沿线沉降进行成因分析。最后基于广义回归神经网络(generalized regression neural network,GRNN)对明长城沉降进行预测。结果表明: 秦皇岛段明长城沿线表现出不同程度的形变,形变严重的区域主要集中在东部及东北部区域,最大沉降速率超过-12 mm/a; 地面沉降与地下水开采关联不大; 明长城在与断裂带相遇前后沉降速率表现出微小差异; 沉降严重区主要发生在第四系全新统黏土层; 交通道路运营暂时未对明长城沿线沉降造成较大影响。GRNN预测结果表明未来明长城沿线沉降有逐渐增大的趋势,部分区域需要重点关注。研究对位于山地地貌明长城进行系统的监测和整体保护提供技术支持。
Abstract:
Land subsidence is a common geological disaster in the Beijing-Tianjin-Hebei region. The uneven land subsidence poses a potential threat to the protection of the Great Wall of the Ming Dynasty (the Ming Great Wall), thus causing irreversible losses. This study acquired information about the surface deformation of the Qinhuangdao section of the Ming Great Wall from 53 scenes of the Sentinel-1 data during 2016—2018 using the persistent scatterer interferometric synthetic aperture Radar (PS-InSAR) and the small baseline subsets (SBAS). The accuracy of the monitoring results was determined by the cross-validation of the deformation results obtained using different processing methods based on synthetic aperture Radar (SAR) data, yielding linear correlation with a coefficient of determination R2 of 0.81 between the two types of data. Then, this study analyzed the causes of the land subsidence along the Ming Great Wall based on auxiliary data, such as changes in the groundwater level, geological structures, stratigraphic lithology, land use, and the distribution of highways and railways. Finally, the land subsidence of the Ming Great Wall was predicted using the generalized regression neural network (GRNN). The results are as follows: ① The Qinhuangdao section of the Ming Great Wall exhibits varying degrees of deformation, with the severe deformation primarily distributed in the eastern and northeastern regions and a maximum subsidence rate of more than -12 mm/a; ② The land subsidence is slightly related to groundwater exploitation; ③ The land subsidence rate of the Ming Great Wall differ slightly before and after the great wall encounters the fault zone; ④ The areas with severe land subsidence are mainly distributed in the Quaternary Holocene clay layer; ⑤ Traffic road operation has not caused any great impact on the settlement along the Ming Great Wall. The GRNN-based prediction results show that the land subsidence along the Ming Great Wall will gradually increase in the future, and special attention should be paid to some areas. This study will provide technical support for the systematic monitoring and overall protection of the sections of the Ming Great Wall located in mountainous areas.
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