Monitoring And Risk Assessment Of Surface Deformation In Mining Cities Based On InSAR

China’s mining cities contributed greatly to the country’s economy during their golden development period.However,a series of geological and environmental issues resulted from excessive mining activities,while earlier expansions of urban buildings and transportation routes were not entirely reasonable,bringing great risks to geological disaster prevention and control and transportation infrastructure maintenance in mining cities.This paper takes Daye City in Hubei Province as a typical representative of mining cities,fully utilizing the advantages of multi-source remote sensing image data such as SAR and multispectral to obtain long-term and large-scale urban surface subsidence and coverage information.It combines historical geological disaster data to analyze the spatial distribution characteristics of surface deformation in mining cities and uses machine learning algorithms to select the main influencing factors to carry out geological disaster risk assessment in mining cities,laying a reliable data foundation for the planning of geological environment and safety engineering in mining cities.This paper uses Sentinel-1 satellite data and a new type of SBAS-In SAR technology with wide swath TOPSAR interferometry measurement to improve the monitoring accuracy of satellite interferometric radar and achieve city-wide,long-term surface deformation monitoring in Daye City every 12 days.Referring to the results of temporal deformation monitoring and combined with field investigations,it identifies key geological deformation areas and analyzes the causes of major deformations.It divides the high subsidence deformation risk areas of the suburban mining clusters in the north and southeast of Daye City,verifying the impact of subsidence caused by underground mining and extraction of groundwater on transportation hubs and residential areas.The monitoring found serious misalignment at the southern end of Changliu Port Bridge in Daye City and obvious subsidence cracks and wall displacement in the residential areas of the Bi Guiyuan community.Comparing with Bei Dou base station monitoring data,the In SAR deformation monitoring accuracy is better than 5mm.Based on surface deformation monitoring data as the main reference and joint local environmental factors such as ground elevation,terrain slope,land use,rainfall,mining,transportation mainlines,and water systems,this paper uses machine learning algorithms to establish a geological hazard susceptibility evaluation model based on environmental factors and calculates the probability of geological hazard risk points under different rainfall levels.The results showed that the risk of high susceptibility increased with the increase of rainfall.The high geological hazard areas are concentrated in the Tieshan district in the north and the copper-green mountain mining area cluster in the southeast of Daye City.Combining Daye City’s land use classification data and using cluster analysis,this paper divides the susceptibility levels of each township and county in Daye City and carries out vulnerability analysis of geological hazard-bearing bodies.The results show that the northern and southeastern street townships of Daye City have relatively high vulnerability.Based on the susceptibility and vulnerability assessment model,a comprehensive geological hazard risk assessment method is constructed to extract the geological hazard risk assessment zones in Daye.The spatial distribution of geological hazard risk in different areas of Daye City under high rainfall conditions is analyzed.The results show that the high geological hazard risk areas in Daye City are concentrated in the northern part of Huandiqiao Town,Luojiqiao Street,Dongyue Road Street,and Daji Pu Town with dense mining areas.The risk assessment level in the area with high geological hazard susceptibility in the south decreases due to the lower density of the built-up area.This article studies the high-precision data acquisition method for monitoring surface deformation in mining cities,and constructs susceptibility,vulnerability,and risk assessment models for geological hazards in mining cities to evaluate the potential risk of geological hazards.The application of these methods and models can comprehensively and scientifically assess the degree of danger and potential impact of geological hazards,and provide a basis for disaster prevention and control decision-making.