Urban building group safety risk multi-scale analysis method fusing InSAR technology and big data

Abstract

The invention provides a building group safety risk multi-scale analysis method fusing an InSAR technology and city big data. The method comprises the following steps: performing city-level wide-area scale deformation monitoring on a city-level wide-area scale level by using a PSI technology, verifying a deformation result based on GNSS monitoring data, identifying a risk area according to an abnormal deformation trend, then obtaining a continuous deformation field in the area, removing PS points with obvious temperature deformation, and finally obtaining a deformation result; according to the method, the interference of building temperature deformation on a deformation field in an area is reduced, vertical deformation and east-west deformation of a PS point are decomposed by utilizing a geometrical relationship, and finally, on a building-level local scale level, the building risk is comprehensively evaluated from the perspective of structural damage risk and rigid body deformation analysis according to four types of longitudinal settlement modes of a building. The method provides an accurate and comprehensive urban building group safety risk multi-scale analysis means, and has important application value for safety monitoring and risk early warning of urban building groups.

Description

Technical Field

[0001] The present invention relates to the field of urban building complex safety risk assessment, and in particular to a multi-scale analysis method for urban building complex safety risk that integrates InSAR technology and big data. Background Art

[0002] When urban buildings face structural aging, changing geological conditions, and underground construction, their safety often deteriorates, leading to serious casualties and economic losses. To improve urban resilience and the safety monitoring and risk warning capabilities of urban buildings, traditional methods such as installing in-situ sensors, leveling, installing GNSS monitoring stations, photogrammetry, and lidar, while highly accurate, are costly and have limited monitoring ranges, making them unsuitable for large-scale deformation monitoring of urban buildings.

[0003] Synthetic Aperture Radar (InSAR) measurement technology is the result of the fusion of synthetic aperture radar imaging and electromagnetic wave interference technologies. It is an active microwave remote sensing measurement method.

[0004] Spaceborne InSAR measurement technology uses a satellite-mounted synthetic aperture radar (SAR) to continuously transmit microwaves to the ground and receive echoes to form a synthetic aperture radar image of the remote sensing area.

[0005] The satellite-mounted SAR performs repeated side-view imaging of the telemetry area along a repeated orbit to obtain a pair of synthetic aperture radar images. Since there is a certain baseline distance between the satellite positions during the two imaging operations and there is a coherent relationship between the image pairs, the interferometric image can be obtained by conjugate multiplication of the image pairs. Based on the interference phase difference at each position in the interferometric image, the distance between the measurement target and the radar at different imaging times can be inverted, thereby extracting the deformation of the measurement target.

[0006] InSAR technology, with its wide observation range, unaffected by day and night conditions, and excellent timeliness, has become an effective means for large-scale urban deformation monitoring. Currently, InSAR deformation observation technology is widely used in monitoring mining settlements, earthquake deformation, landslides, rail transit deformation, and bridge deformation. In particular, Permanent Scatterer Interferometry (PSI) can identify several permanent scatterers (PS) on buildings and obtain their deformation time series, enabling detailed deformation analysis of buildings. Under ideal observation conditions, PSI technology achieves millimeter-level or even submillimeter-level deformation accuracy, and in actual building deformation monitoring, it can achieve sub-centimeter-level deformation accuracy. However, a single macroscopic deformation metric is insufficient to comprehensively assess building risks. Currently, cloud-based urban big data covers an increasingly broad range of areas, including satellite imagery, multi-domain monitoring data, geological and hydrological information, and building information. Fusion of urban big data with spaceborne InSAR technology to deepen the analysis and utilization of deformation results will become a future trend.

[0007] In general, the current spaceborne InSAR technology for urban deformation observation mostly remains at a single scale, lacking multi-scale urban surface deformation observation and building risk assessment integrated with big data.

[0008] PS point: refers to the point where the permanent scatterers of various ground targets with strong backscattering of radar waves and relatively stable in time sequence are located in PSI technology. Summary of the Invention

[0009] The purpose of this invention is to provide a large-scale, low-cost, and sustainable multi-scale safety risk analysis method for urban building complexes that integrates spaceborne InSAR technology, structural theory, and urban big data. This methodology overcomes the limitations of traditional building risk assessment based on a single macroscopic deformation metric, significantly improving the accuracy of identifying high-risk buildings and contributing to the resilience of urban building complexes to potential risks.

[0010] The technical solutions of the present invention are as follows:

[0011] A multi-scale analysis method for urban building complex safety risks that integrates InSAR technology and big data includes:

[0012] S1. City-level, wide-area-scale deformation field analysis: Using PSI technology to monitor deformation at the city level, we obtain deformation results. GNSS monitoring data is then used to verify these results and obtain the deformation field. The deformation field is then analyzed using geological and hydrological information, and abnormal deformation areas are identified as risk areas based on abnormal deformation trends.

[0013] S2. Analysis of mesoscale risk areas at the regional level: By using the IDW interpolation method based on ascending and descending SAR satellite images, the abnormal deformation field of the identified risk areas is analyzed to obtain a continuous deformation field of the risk areas. The vertical deformation and east-west deformation of the PS points within the continuous deformation field of the risk areas are decomposed to obtain the vertical deformation field, and then the settlement values of the PS points within the continuous deformation field of the risk areas are obtained.

[0014] S3. Building-level local-scale deformation and risk assessment: Based on the settlement value of the PS point of the building, the shape of the building's longitudinal settlement curve is obtained. Combined with building information, building deformation pattern and structural theory, building deformation analysis and risk assessment are carried out in the continuous deformation field of the risk area to obtain the building risk assessment results of each building.

[0015] For further improvement, the specific steps of step S1 are as follows:

[0016] S1.1: Urban deformation monitoring using PSI technology: First, short-term baseline processing was performed on the time series SAR images of the study area acquired according to the scope of the study area. The 152 ascending and 35 descending SAR images from the Sentinel-1A satellite were divided into five ascending image subsets and one descending image subset to ensure temporal coherence between the images.

[0017] S1.2: To improve the accuracy of the PSI process, an amplitude stability coefficient of 0.75 is first selected as the threshold for the initial selection of PS points. After removing atmospheric interference, the coefficient is reduced to 0.7 to encrypt the PS points. Finally, the deformation solution reference point for all image subsets is selected at the same location, and the temperature data is used as the temperature parameter to input the interferometric phase model including the temperature phase to obtain more accurate PS point deformation.

[0018] S1.3: Use the monitoring data from the GNSS monitoring station to verify the PSI deformation solution, and obtain the area where the PS point set with the correct verification result is located as the deformation field;

[0019] S1.4: Compare hydrological information with LOS deformation data of nearby PS points and analyze the deformation field in combination with geological information. The cluster of PS points where the deformation trend exceeds the average value is considered an abnormal deformation area. The hydrological information is historical water level data from groundwater level stations, and the geological information is a real-world 3D image.

[0020] As a further improvement, the PSI technology includes: using small time baseline processing and an interferometric phase model including a temperature phase to estimate the deformation of PS points over a large area of the city, so as to accurately obtain the long-period urban deformation field. The specific formula is as follows:

[0021]

[0022] Where Δφ is the interference phase difference between the PS points, λ is the wavelength of the electromagnetic wave, ΔT and B are the time baseline and space baseline between the two images, Δν is the deformation rate difference between the PS points, R is the slant range between the satellite and the observed target, θ is the incident angle of the radar wave, ΔRTE is the elevation residual of the two PS points, ΔTemp is the temperature difference at the time of acquisition of the two images, ΔTh is the temperature deformation coefficient difference between the two PS points, and Δφ is the difference between the two images. res is the interferometric phase residual.

[0023] For further improvement, the specific steps of step S2 are as follows:

[0024] S2.1 removes PS points with obvious temperature deformation, and then uses the IDW interpolation method to calculate the continuous deformation field at the zone level within the abnormal deformation area;

[0025] S2.2: Integrate the SAR satellite ascending and descending orbit images and decompose the vertical deformation and east-west deformation of the PS point in the continuous deformation field at the regional level using the following formula to obtain the regional vertical deformation field;

[0026] D LOS,a =-D e ·cosα a sinθ a +D v cosθ a

[0027] D LOS,d =D e ·cosα d sinθ d +D v cosθ d

[0028] Wherein, the subscripts “a” and “d” represent the satellite orbit ascending and orbit descending observation modes, respectively, and D LOS is the LOS deformation, D e 、D v are the eastward and vertical deformations, respectively, and θ and α are the incident angle of the radar wave and the heading angle of the satellite, respectively;

[0029] S2.3: After obtaining the regional vertical deformation field, extract the settlement values of representative site sections within the regional vertical deformation field, integrate the results of the urban historical real-scene 3D image survey, and analyze the causes of regional abnormal deformation.

[0030] Further improvement, the formula for accurately obtaining the zone-level continuous deformation field within the abnormal deformation area using the IDW interpolation method is as follows:

[0031]

[0032] Where DP is the deformation of the point to be determined, S n is the distance between the nth known deformation point and the point to be determined, D n is the deformation of the nth known deformation point.

[0033] For further improvement, the specific steps of step S3 are as follows:

[0034] S3.1 Obtain the local heel angle to analyze the lateral tilt of the building;

[0035] S3.2: Define four types of longitudinal settlement patterns: S-curve, parabola, horizontal straight line, and inclined line; obtain the settlement pattern of the building to be assessed based on the settlement value at point PS and obtain the corresponding settlement curve deflection ratio ω i and the heel curve deflection ratio ω θ ;

[0036] S3.3 divides the risk assessment of buildings into two categories: structural damage risk and rigid body deformation risk. The risk assessment indicators of structural damage risk include the deflection ratio of the settlement curve ω i and the heel curve deflection ratio ω θ The risk assessment indicators of rigid body deformation risk include the maximum settlement d max , longitudinal inclination angle η, maximum heel angle |θ max | and recent subsidence Set a weight for each risk assessment indicator, multiply each risk assessment indicator by the corresponding weight and add them up to obtain the risk value of the corresponding building, that is, the building risk assessment result.

[0037] As a further improvement, the specific formula for defining the local heel angle is as follows:

[0038]

[0039] Where θ i is the local heel angle, D i With D i ' is the vertical deformation on both sides of the same cross section of the building, and B is the building width.

[0040] A further improvement is that the deflection ratio of the settlement curve is ω i The weight is 30%, the heel curve deflection ratio ω θ The weight is 20%, the maximum settlement d max The weight of the longitudinal inclination angle η is 12.5%, the maximum heel angle |θ is 12.5%. max The weight is 12.5%, with recent settlement The weight is 12.5%.

[0041] Further improvement, the deflection ratio of the settlement curve ωi , heel curve deflection ratio ω θ The maximum settlement d is obtained by geometric calculation from the longitudinal settlement curve and the heel angle curve. max and the maximum heel angle |θ max | Read directly from the settlement curve and heel angle curve, recent settlement Take the average value of the settlement increments at each point of the building in the past six months.

[0042] As a further improvement, the building risk assessment results are presented in the form of a bar graph.

[0043] The beneficial effects of the invention are:

[0044] Improve the accuracy and efficiency of deformation monitoring of urban building complexes: Compared with traditional methods, InSAR technology has higher accuracy and wider coverage, and can realize deformation monitoring at a city-level wide-area scale. By using InSAR technology, the present invention can obtain deformation data of urban building complexes under large-scale and low-cost conditions.

[0045] Achieving multi-scale building risk assessment: This paper proposes a comprehensive building risk assessment method that combines structural damage risk and rigid body deformation risk. This method can more accurately identify high-risk buildings, providing a scientific basis for urban planning, architectural design, and emergency response, significantly improving a city's resilience to potential risks.

[0046] It will help to establish a large-scale, low-cost, sustainable deformation monitoring and risk assessment platform for urban buildings. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 This is a flow chart of a multi-scale analysis method for building complex safety risks that integrates InSAR technology and urban big data, provided according to an embodiment of the present invention.

[0048] Figure 2 This is a schematic diagram of city-level wide-area deformation results provided according to an embodiment of the present invention.

[0049] Figure 3 Schematic diagram of a continuous deformation field in a mid-domain at a slice level according to an embodiment of the present invention.

[0050] Figure 4 Schematic diagram of the longitudinal settlement deformation mode of a building provided according to an embodiment of the present invention.

[0051] Figure 5 A schematic diagram of lateral tilt provided according to an embodiment of the present invention.

[0052] Figure 6 This is a schematic diagram of risk assessment indicators provided according to an embodiment of the present invention.

[0053] Figure 7 This is a diagram of building risk assessment results provided according to an embodiment of the present invention. DETAILED DESCRIPTION

[0054] In order to more clearly and intuitively illustrate the purpose, features and advantages of the present invention, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments of the present invention.

[0055] It should be noted that:

[0056] The following describes some embodiments of the present invention, but not all embodiments. All other embodiments obtained by persons of ordinary skill in the art without creative effort based on the present invention shall fall within the scope of protection of the present invention.

[0057] The embodiments described are not specific limitations of the present invention. Although the present invention has been described in detail with reference to the embodiments, ordinary technicians in this field can still modify the technical solutions described in the aforementioned embodiments, or make equivalent substitutions for some of the technical features therein. These modifications or substitutions do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

[0058] The embodiment of the present invention provides a multi-scale analysis method for the safety risk of urban buildings that integrates InSAR technology and big data. A certain area of a city is selected as the research area. Figure 1 , execute the following steps S1 to S3 to complete the assessment and analysis of the safety risks of the Taipei City building complex:

[0059] S1. City-level wide-area deformation field analysis: Deformation monitoring is performed using PSI technology, and the deformation results are verified using GNSS monitoring data. The deformation field is then analyzed in combination with geological and hydrological information, and risk areas are identified based on abnormal deformation trends.

[0060] The specific steps of step S1 are as follows:

[0061] S1.1: Urban deformation monitoring is performed using PSI technology. First, the time series SAR images of the study area acquired according to the scope of the study area are subjected to short-time baseline processing. The 152 ascending and 35 descending SAR images from the Sentinel-1A satellite are divided into five ascending image subsets and one descending image subset to ensure the temporal coherence between the images.

[0062] S1.2: To improve the accuracy of the PSI process, an amplitude stability coefficient of 0.75 was initially selected as the threshold for the initial selection of PS points. After removing atmospheric interference, the coefficient was reduced to 0.7 for the PS point refinement. Finally, the deformation solution reference point for all image subsets was selected at the same location, and the temperature data was used as the temperature parameter in the interferometric phase model that includes the temperature phase to obtain more accurate PS point deformation.

[0063] S1.3: To further verify the accuracy of the PSI deformation solution, the PSI deformation solution results are verified using the monitoring data from the GNSS monitoring station;

[0064] S1.4: Compare historical groundwater level data from the groundwater level station with LOS deformation data from nearby PS points and analyze the deformation field in combination with geological information.

[0065] S2. Analysis of risk areas at the regional and mid-scale: By using the IDW interpolation method of integrated SAR satellite ascending and descending orbit images, the abnormal deformation field of the identified risk areas is analyzed;

[0066] Through step S1, a Figure 2 The discrete deformation field composed of PS points shown in the figure can preliminarily identify two risk areas with obviously abnormal deformation trends. On this basis, the research scope can be narrowed down and step S2 can be entered to perform a more detailed deformation analysis on the identified risk areas.

[0067] The specific steps of step S2 are as follows:

[0068] S2.1: To reduce the interference of building temperature deformation on the deformation field within the region, PS points with obvious temperature deformation are removed before IDW interpolation. Afterwards, the IDW interpolation method is used to calculate the continuous deformation field within the region.

[0069] S2.2: After obtaining the continuous deformation field at the area level, the vertical deformation and east-west deformation of the PS point are decomposed by integrating the SAR satellite ascending and descending orbit images using the following formula.

[0070] D LOS,a =-D e ·cosα a sinθ a +D v cosθ a

[0071] D LOS,d =D e ·cosα d sinθ d +D v cosθ d

[0072] Wherein, the subscripts “a” and “d” represent the satellite orbit ascending and orbit descending observation modes, respectively, and D LOS is the LOS deformation, D e 、D v are the eastward and vertical deformations, respectively; θ and α are the incident angle of the radar wave and the heading angle of the satellite, respectively.

[0073] S2.3: After obtaining the regional vertical deformation field, extract the settlement values of representative site profiles within the region and integrate them with the results of the urban historical real-scene 3D image survey to conduct an in-depth analysis of the causes of regional abnormal deformation.

[0074] S3. Building-level local-scale deformation and risk assessment: Building deformation analysis and risk assessment are conducted by combining building information, building deformation patterns, and structural theory.

[0075] The deformation field of the risk area is obtained through step S2, and the optical satellite image data is used as the base map for the PS point cloud visualization projection, as shown in the following figure: Figure 3 The continuous deformation field of the risk area is shown, and then step S3 is entered to perform building-level local scale deformation analysis and risk assessment.

[0076] The specific steps of step S3 are as follows:

[0077] S3.1: Utilization Figure 4 The four types of building longitudinal settlement deformation modes summarized from the morphology of the longitudinal settlement curve shown in the figure are used to judge whether the longitudinal settlement will produce adverse additional stress on the building, and the deflection ratio ω of the settlement curve is used to determine whether the longitudinal settlement will produce adverse additional stress on the building. i or ω i 'Measure its level of risk;

[0078] S3.2 uses the local heel angle to analyze the lateral tilt of the building. The definition of the local heel angle is as follows: Figure 5 (a)

[0079] In addition, using Figure 5 (b) The three types of building lateral deformation modes summarized by the lateral inclination angle curve are (g)(x)>0 or <0; g(x)=0; g(x)=θ i ) To determine whether the lateral tilt of a building generates adverse additional stress on the building, (g)(x) is the second-order derivative of g(x), θ = g(x), which is the distribution curve of the lateral tilt angle along the longitudinal direction, and θ is positive when it tilts south or east. The deflection ratio ω of the lateral tilt curve is used. θ Measure the degree of risk.

[0080] S3.3: According to Figure 6 All risk assessment indicators shown are based on the following proportions: settlement curve deflection ratio ω i or ω i '(30%), heel curve deflection ratio ωθ (20%), maximum settlement d max (12.5%), longitudinal inclination angle η(12.5%), maximum heel angle |θ max |(12.5%) and recent subsidence Conduct a comprehensive risk assessment of the target building.

[0081] Through step S3, we can get Figure 7 The risk assessment results for buildings with risks in the indicated risk areas.

[0082] Although the embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the description and the embodiments. They can be fully applied to various fields suitable for the present invention. For those familiar with the art, additional modifications can be easily implemented. Therefore, without departing from the general concept defined by the claims and the scope of equivalents, the present invention is not limited to the specific details and shown here.

Claims

1. A multi-scale analysis method for urban building complex safety risk integrating InSAR technology and big data, characterized by: include: S1. City-level wide-area deformation field analysis: Use PSI technology to monitor deformation at the city level to obtain deformation results, and use GNSS monitoring data to verify the deformation results and obtain the deformation field; Then, the deformation field is analyzed by combining geological information and hydrological information, and abnormal deformation areas are identified as risk areas based on abnormal deformation trends. S2. Analysis of mesoscale risk areas at the regional level: By using the IDW interpolation method based on ascending and descending SAR satellite images, the abnormal deformation field of the identified risk areas is analyzed to obtain a continuous deformation field of the risk areas. The vertical deformation and east-west deformation of the PS points within the continuous deformation field of the risk areas are decomposed to obtain the vertical deformation field, and then the settlement values of the PS points within the continuous deformation field of the risk areas are obtained. S3. Building-level local-scale deformation and risk assessment: Based on the settlement value of the PS point of the building, the shape of the building's longitudinal settlement curve is obtained. Combined with building information, building deformation pattern and structural theory, building deformation analysis and risk assessment are carried out in the continuous deformation field of the risk area to obtain the building risk assessment results of each building.

2. The multi-scale analysis method for urban building complex safety risk integrating InSAR technology and big data as claimed in claim 1 is characterized in that: The specific steps of step S1 are as follows: S1.1: Urban deformation monitoring using PSI technology: First, short-term baseline processing was performed on the time series SAR images of the study area acquired according to the scope of the study area. The 152 ascending and 35 descending SAR images from the Sentinel-1A satellite were divided into five ascending image subsets and one descending image subset to ensure temporal coherence between the images. S1.2: To improve the accuracy of the PSI process, an amplitude stability coefficient of 0.75 is first selected as the threshold for the initial selection of PS points. After removing atmospheric interference, the coefficient is reduced to 0.7 to encrypt the PS points. Finally, the deformation solution reference point for all image subsets is selected at the same location, and the temperature data is used as the temperature parameter to input the interferometric phase model including the temperature phase to obtain more accurate PS point deformation. S1.3: Use the monitoring data from the GNSS monitoring station to verify the PSI deformation solution, and obtain the area where the PS point set with the correct verification result is located as the deformation field; S1.4: Compare hydrological information with LOS deformation data of nearby PS points and analyze the deformation field in combination with geological information. The cluster of PS points where the deformation trend exceeds the average value is considered an abnormal deformation area. The hydrological information is historical water level data from groundwater level stations, and the geological information is a real-world 3D image.

3. The multi-scale analysis method for urban building complex safety risk integrating InSAR technology and big data as claimed in claim 2 is characterized in that: The PSI technology involves using a small time baseline processing and an interferometric phase model including a temperature phase to estimate deformation at PS points over a large area of the city, in order to accurately obtain the long-period urban deformation field. The specific formula is as follows: Where Δφ is the interference phase difference between the PS points, λ is the wavelength of the electromagnetic wave, ΔT and B are the time baseline and space baseline between the two images, Δν is the deformation rate difference between the PS points, R is the slant range between the satellite and the observed target, θ is the incident angle of the radar wave, ΔRTE is the elevation residual of the two PS points, ΔTemp is the temperature difference at the time of acquisition of the two images, ΔTh is the temperature deformation coefficient difference between the two PS points, and Δφ is the difference between the two images. res is the interferometric phase residual.

4. The multi-scale analysis method for urban building complex safety risk integrating InSAR technology and big data as claimed in claim 2 is characterized in that: The specific steps of step S2 are as follows: S2.1 removes PS points with obvious temperature deformation, and then uses the IDW interpolation method to calculate the continuous deformation field at the zone level within the abnormal deformation area; S2.2: Integrate the SAR satellite ascending and descending orbit images and decompose the vertical deformation and east-west deformation of the PS point in the continuous deformation field at the regional level using the following formula to obtain the regional vertical deformation field; D LOS,a =-D e ·cosα a ·sinθ a +D v cosθ a D LOS,d =D e ·cosα d ·sinθ d +D v cosθ d Wherein, the subscripts "a" and "d" represent the satellite orbit ascending and orbit descending observation modes, respectively, and D LOS is the LOS deformation, D e 、D v are the eastward and vertical deformations, respectively, and θ and α are the incident angle of the radar wave and the heading angle of the satellite, respectively; S2.3: After obtaining the regional vertical deformation field, extract the settlement values of representative site sections within the regional vertical deformation field, integrate the results of the urban historical real-scene 3D image survey, and analyze the causes of regional abnormal deformation.

5. The multi-scale analysis method for urban building complex safety risk integrating InSAR technology and big data as claimed in claim 4 is characterized in that: The formula for accurately obtaining the zone-level continuous deformation field within the abnormal deformation area using the IDW interpolation method is as follows: Where D P is the deformation of the point to be determined, S n is the distance between the nth known deformation point and the point to be determined, D n is the deformation of the nth known deformation point.

6. The multi-scale analysis method for urban building complex safety risk integrating InSAR technology and big data as claimed in claim 4, characterized in that: The specific steps of step S3 are as follows: S3.1 Obtain the local heel angle to analyze the lateral tilt of the building; S3.2: Define four types of longitudinal settlement patterns: S-curve, parabola, horizontal line, and inclined line; according to; According to the settlement value of PS point, the settlement mode of the building to be evaluated is obtained, and the corresponding settlement curve deflection ratio ω is obtained. i and the heel curve deflection ratio ω θ ; S3.3 divides the risk assessment of buildings into two categories: structural damage risk and rigid body deformation risk. The risk assessment indicators of structural damage risk include the deflection ratio of the settlement curve ω i and the heel curve deflection ratio ω θ The risk assessment indicators of rigid body deformation risk include the maximum settlement d max , longitudinal inclination angle η, maximum heel angle |θ max | and recent subsidence Set a weight for each risk assessment indicator, multiply each risk assessment indicator by the corresponding weight and add them up to obtain the risk value of the corresponding building, that is, the building risk assessment result.

7. The multi-scale analysis method for urban building complex safety risk integrating InSAR technology and big data as claimed in claim 6, characterized in that: The specific formula for defining the local heel angle is as follows: Where θ i is the local heel angle, D i With D i ' is the vertical deformation on both sides of the same cross section of the building, and B is the building width.

8. The multi-scale analysis method for urban building complex safety risk integrating InSAR technology and big data as claimed in claim 6, characterized in that: The deflection ratio of the settlement curve ω i The weight is 30%, the heel curve deflection ratio ω θ The weight is 20%, the maximum settlement d max The weight of the longitudinal inclination angle η is 12.5%, the maximum heel angle |θ is 12.5%. max The weight is 12.5%, with recent settlement The weight is 12.5%.

9. The multi-scale analysis method for urban building complex safety risk integrating InSAR technology and big data as claimed in claim 6, characterized in that: Deflection ratio of settlement curve ω i , heel curve deflection ratio ω θ The maximum settlement d is obtained by geometric calculation from the longitudinal settlement curve and the heel angle curve. max and the maximum heel angle |θ max | Read directly from the settlement curve and heel angle curve, recent settlement Take the average value of the settlement increments at each point of the building in the past six months.

10. The multi-scale analysis method for urban building complex safety risk integrating InSAR technology and big data according to any one of claims 1 to 9, characterized in that: The building risk assessment results are presented in the form of a bar graph.

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