A Method for Risk Assessment of Highway Slopes Based on Combined D-INSAR and TS-InSAR Technologies

Abstract

This invention discloses a method for risk assessment of highway slopes based on combined D-INSAR and TS-InSAR technologies, relating to the application of spaceborne SAR data. The method includes: S1 acquiring SAR monitoring image data of the target highway; S2 acquiring digital elevation model (DEM) data of the target highway; S3 performing D-InSAR processing on the SAR monitoring image data to obtain a deformation map; S4 analyzing the deformation map to delineate potential hazard areas; S5 acquiring SAR image data and DEM data of the hazard areas; S6 analyzing changes in the hazard areas; and S7 plotting a time-series cumulative deformation change map to analyze potential causes. This method for risk assessment of highway slopes based on combined D-INSAR and TS-InSAR technologies constructs a deformation model, starting from a large area and gradually refining the model to quickly locate potential hazard areas, determine the target area, and reflect the deformation trend over a long time series, without requiring on-site ground measurements. It fully leverages the advantages of remote sensing data, such as fast information acquisition speed, short cycle, and wide-area observation capability.

Description

Technical Field

[0001] This invention relates to the field of spaceborne SAR data application, and in particular to a method for risk assessment of highway slopes based on the combined technology of D-INSAR and TS-InSAR. Background Technology

[0002] In recent years, with the continuous progress of the national social economy, my country's highway transportation industry has developed rapidly. As of 2021, the total length of expressways in my country reached 169,000 kilometers, covering approximately 92% of prefecture-level cities. The expressway network is gradually extending from the plains of central and eastern China to the mountainous areas of southwest China. In the construction of numerous mountain expressways, slope engineering, as an indispensable and crucial engineering area, has long been a focus of attention for engineering technicians, particularly regarding ensuring the safety of the slope protection work.

[0003] Currently, conventional methods for slope risk assessment often rely on manual methods, primarily using visual inspection, listening, and tapping to determine the current and future condition of the slope—a qualitative approach. This method is highly subjective and involves significant human intervention, especially when assessing long-distance highway slopes. Manual methods incur high labor and material costs and are inefficient. In addition, BeiDou and GPS are also commonly used for slope risk assessment, offering relatively high accuracy compared to manual methods. However, they still have some limitations in practical application, such as high hardware costs, limited monitoring accuracy in complex environments, and the limited number of visible GPS satellites and scattered monitoring targets, resulting in sparse data points and difficulty in comprehensively covering large areas.

[0004] Compared to ground-based manual risk assessment methods and those using BeiDou and GPS, highway slope risk assessment techniques based on satellite remote sensing imagery offer advantages such as speed, timeliness, objectivity, accuracy, and labor and time savings. Synthetic Aperture Radar (SAR) remote sensing satellites actively transmit electromagnetic waves to acquire surface information, unaffected by clouds or fog, enabling all-weather, 24 / 7 observation. Differential Synthetic Aperture Radar Interferometry (D-InSAR) utilizes the phase difference of complex radar images. Based on the geometric relationships of sensor altitude, radar satellite wavelength, antenna distance, and beam line of sight, and through a series of data processing steps, it extracts minute deformation information of the observed target from one or more interferometric fringe patterns containing information on deformation and topography of the study area. Time Series Synthetic Aperture Radar Interferometry (TS-InSAR) is an extension of D-InSAR. It effectively reduces spatiotemporal decoherence errors, phase unwrapping errors, DEM errors, and orbit errors during the processing by combining multiple interferometric image pairs.

[0005] Deformation information acquired through InSAR technology can quantitatively reflect the risk status of highway slopes, theoretically achieving sub-centimeter or even millimeter-level accuracy in deformation monitoring. D-InSAR uses a surface data acquisition method to obtain deformation information, offering a significant advantage over traditional measurement methods that only provide sparse point data. TS-InSAR technology can reflect the temporal deformation characteristics of the target area and predict the future stability of the slope through deformation trends, thereby achieving the purpose of risk assessment.

[0006] While the D-InSAR-based method for assessing highway slope risks can quickly identify long-distance, large-area slope deformation information, rapidly locate potential hazard areas, and determine target areas, it fails to reflect long-term deformation trends and cannot effectively determine future changes within the target area. TS-InSAR technology, on the other hand, can reflect changes over multiple periods, determining the level of risk through these trends. However, TS-InSAR requires a large amount of image data and places high demands on hardware and software performance. In conclusion, both methods can play a role in assessing highway slope risks, but limitations in detail representation and processing efficiency make it difficult to quickly and efficiently assess highway slope risks. Summary of the Invention

[0007] The purpose of this invention is to design a method for risk assessment of highway slopes based on the combined technology of D-INSAR and TS-InSAR in order to solve the above problems.

[0008] The present invention achieves the above objectives through the following technical solutions:

[0009] The method for assessing highway slope risks based on the combined D-INSAR and TS-InSAR technologies includes:

[0010] S1. Acquire two synthetic aperture radar (SAR) monitoring image data corresponding to the target highway;

[0011] S2. Obtain the digital elevation model (DEM) data of the area corresponding to the target highway;

[0012] S3. Perform D-InSAR processing on the SAR monitoring image data of the target highway to obtain a deformation map of the SAR coverage area at the macro level.

[0013] S4. Analyze the deformation diagram, delineate the deformation area that exceeds the preset deformation amount, and expand the deformation area as the potential danger area.

[0014] S5. Acquire SAR image data and digital elevation model (DEM) data of the potential hazard area;

[0015] S6. Perform TS-InSAR deformation secondary inversion on the SAR image data of the potential hazard area to obtain the changes of the potential hazard area at various times;

[0016] S7. Draw a time-series cumulative deformation change diagram, analyze the potential causes of highway slope risk, and obtain qualitative and quantitative analysis results of highway slope risk.

[0017] The beneficial effects of this invention are as follows: The highway slope risk assessment method based on the combined D-INSAR and TS-InSAR technologies constructs a deformation model, starting from a large area and gradually refining the model to quickly locate potential hazardous areas, determine target areas, and reflect the deformation trend over a long period of time, without requiring on-site ground measurements. This overcomes the limitations of traditional ground-based manual monitoring techniques that rely on manpower, fully leveraging the advantages of remote sensing data—fast information acquisition, short cycle, and wide-area observation capability. The highway slope risk assessment method based on the combined D-INSAR and TS-InSAR technologies can quickly achieve risk assessment of long-distance highway slopes, comprehensively understand the disaster risk situation along highways, and ascertain the baseline of highway slope risks and hazards, which is of great significance for road safety and navigation safety in various regions. Attached Figure Description

[0018] Figure 1This is a flowchart illustrating the method for identifying highway slope risks based on the combined D-INSAR and TS-InSAR technologies of this invention.

[0019] Figure 2 This is a schematic diagram of the terrain and landforms of an embodiment of the present invention;

[0020] Figure 3 This is a diagram showing the results of further risk analysis and investigation of the Ya'an-Xichang Expressway, where the method was used to screen out potential slopes and then the slopes were further analyzed and investigated.

[0021] Figure 4 The results of data processing and analysis after the implementation of this invention. Figure 1 ;

[0022] Figure 5 The results of data processing and analysis after the implementation of this invention. Figure 2 . Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0024] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0025] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0026] In the description of this invention, it should be understood that the terms "upper," "lower," "inner," "outer," "left," "right," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product of this invention is in use, or the orientation or positional relationship commonly understood by those skilled in the art. They are only used to facilitate the description of this invention and to simplify the description, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0027] Furthermore, the terms "first," "second," etc., are used only to distinguish descriptions and should not be interpreted as indicating or implying relative importance.

[0028] In the description of this invention, it should also be noted that, unless otherwise explicitly specified and limited, terms such as "set" and "connection" should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium; it can be a connection within two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0029] The specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0030] The method for assessing highway slope risks based on the combined D-INSAR and TS-InSAR technologies includes:

[0031] S1. Acquire two synthetic aperture radar (SAR) monitoring image data corresponding to the target highway; specifically including:

[0032] S11. Use synthetic aperture radar remote sensing satellites to monitor the target highway and acquire a pair of monitoring image data, the main image Mst and the auxiliary image Sla. Based on the characteristics of current remote sensing satellite data and data acquisition time, combined with monitoring requirements and remote sensing data costs, rationally select remote sensing data sources, requiring that the data from a single satellite imaging can fully cover the monitored highway area.

[0033] S12. Based on the acquired synthetic aperture radar data product level, perform orthorectification processing on the main image Mst and the auxiliary image Sla to obtain SAR monitoring image data.

[0034] S2. Based on the latitude and longitude of the target highway, acquire the digital elevation model (DEM) data within the corresponding area to ensure that the DEM data completely covers the monitoring area. When acquiring the DEM data, the newer WorldDEM™ elevation data product is used. Based on two identical synthetic aperture radar satellites, TerraSAR-X and TanDEM-X, they fly in formation to acquire homogeneous data worldwide, ensuring that the elevation information is uninterrupted and of consistent quality globally.

[0035] S3. Use InSAR processing software to perform D-InSAR processing on the SAR monitoring image data of the target highway to obtain the deformation map Disp of the SAR coverage area at the macro level. D-InSAR processing includes image registration, interferogram generation, interferogram filtering, phase unwrapping, orbit refinement and re-flattening, phase transformation deformation and geocoding.

[0036] S4. Analyze the deformation map Disp, delineate the deformation area exceeding the preset deformation amount, and expand the deformation area as the potential danger area; specifically: import the deformation map Disp into GIS software, perform histogram equalization on the deformation map Disp; delineate the deformation area exceeding the preset deformation amount, and automatically identify and expand the deformation area as the potential danger area based on the neighborhood constraint clustering algorithm, then establish the corresponding vector range shp, and manually verify the vector range shp.

[0037] S5. Obtain SAR image data and digital elevation model (DEM) data of the potential hazard area based on the vector range (shp). In the remote sensing processing software, crop the SAR data according to the vector range (shp) to obtain the SAR image data. The DEM data of the potential hazard area can use the DEM data of the target highway in S2, but the DEM data in S2 needs to be cropped a second time according to the vector range (shp) to ensure low data computation and that the data processing results can cover the entire potential hazard area.

[0038] S6. Perform TS-InSAR deformation secondary inversion on the SAR image data of the potential hazard area to obtain the changes in the potential hazard area at various times; specifically: combine TS-InSAR technology and use an amplitude dispersion index E A A permanent scattering point PS is selected, a TS-InSAR time series model is constructed, and the deformation phase is calculated. Represented as Calculate linear phase Nonlinear deformation phase And combined with satellite orbital parameters (λ, (etc.) inverting the shape variables of different periods (defo) non-linear and annual deformation rate Δv p Amplitude dispersion index E A The standard deviation of the amplitude of the time series image is δ A With average amplitude The ratio of is expressed as

[0039] S7. Calculate the absolute value Δ of the deformation rate difference between all PS points at the top and bottom of the slope within the hazard area using GIS and Matlab software. v When the region Δ vWhen the value exceeds the pre-set threshold γ, it is identified as a high-risk area. Based on the existing PS points in the potential hazard area, the specific location is extracted, and a time-series cumulative deformation change diagram is drawn according to the time change. The potential causes of the target highway slope risk are analyzed, and the qualitative and quantitative analysis results of the target highway slope risk are obtained.

[0040] Detailed Analysis of Examples

[0041] The following example is taken from a section of the Ya'an-Xichang Expressway in Sichuan Province, my country, which experienced a high-altitude landslide on September 20, 2020. Figure 2 As shown, the method for investigating highway slope risks based on the combined D-INSAR and TS-InSAR technologies provided by this invention is verified and explained.

[0042] During the processing, two SAR images covering the target area of ​​the Ya'an-Xichang Highway, taken on September 17 and 29, 2020, were selected for D-InSAR processing to obtain a surface deformation map (Disp), as shown below. Figure 3 As shown in (a); through statistical analysis using GIS software, the vector range (shp) of the more obvious hidden danger areas within the target area is drawn, as shown in (a). Figure 3 As shown, the area selected by the solid line is based on the vector range shapefile (shp). Multiple SAR images are obtained using the newly created vector range shapefile of the potential hazard area; this embodiment uses 21 images. Permanent scattering points are selected based on the amplitude dispersion index, and their distribution is as follows: Figure 3 As shown in (b), a phase-deformation model is constructed, and the trend of cumulative deformation over time at typical points is plotted, as follows. Figure 4 As shown, the potential causes of highway slope risk are analyzed, and the qualitative and quantitative analysis results of highway slope risk are obtained, such as... Figure 5 The data shows the detection results of the PS points at the top and bottom of the slope from January 9th to September 17th, 2020 (a period of more than nine months). Statistical analysis of the annual settlement rate at the PS point on the right slope bottom shows an average annual uplift rate of 12.5 mm / y; analysis of the annual settlement rate at the PS point at the top shows an average annual settlement rate of -8.9 mm / y. During the monitoring period, the slope top showed a subsidence trend, while the slope bottom showed uplift, indicating a potential for landslides and slope instability. The absolute value of the difference in deformation rate Δ... v =21.4>15, where 15 is the pre-set threshold γ, so this area is a high-risk area.

[0043] The results of the above examples demonstrate that the method proposed in this invention can accurately reflect the actual risk situation of highway slope risk points, and there is a good correlation between theory and practice. This method overcomes the problems of time-consuming and labor-intensive manual risk assessment of highway slopes, and the shortcomings of both DInSAR and TS-InSAR. It establishes a highway slope risk assessment method based on the combined technology of D-INSAR and TS-InSAR, providing effective technical support for long-distance, large-area slope risk assessment on highways, and has good practical value.

[0044] The technical solutions of the present invention are not limited to the specific embodiments described above. Any technical modifications made in accordance with the technical solutions of the present invention fall within the protection scope of the present invention.

Claims

1. A method for risk assessment of highway slopes based on combined D-INSAR and TS-InSAR technologies, characterized in that, include: S1. Acquire two synthetic aperture radar (SAR) monitoring image data corresponding to the target highway; S2. Obtain the digital elevation model (DEM) data of the area corresponding to the target highway; S3. Perform D-InSAR processing on the SAR monitoring image data of the target highway to obtain 2-3 macroscopic deformation maps of the SAR coverage area. S4. Analyze the deformation diagram, delineate the deformation area that exceeds the preset deformation amount, and expand the deformation area as the potential danger area. S5. Obtain digital elevation model (DEM) data and at least 20 SAR image views of the potential hazard area; S6. Perform TS-InSAR deformation secondary inversion on the SAR image data of the potential hazard area to obtain the changes of the potential hazard area at various times; S7. Draw a time-series cumulative deformation change diagram, analyze the potential causes of highway slope risk, and obtain qualitative and quantitative analysis results of highway slope risk.

2. The method for assessing highway slope risks based on D-INSAR and TS-InSAR combined technologies according to claim 1, characterized in that, S1 includes: S11. Use synthetic aperture radar remote sensing satellites to monitor the target highway and acquire a pair of monitoring image data, the main image Mst and the auxiliary image Sla; S12. Perform orthorectification on the main image Mst and the auxiliary image Sla to obtain SAR monitoring image data.

3. The method for assessing highway slope risks based on the combined D-INSAR and TS-InSAR technologies according to claim 1, characterized in that, In S3, InSAR processing software is used to perform D-InSAR processing on the SAR monitoring image data of the target highway. D-InSAR processing includes image registration, interferogram generation, interferogram filtering, phase unwrapping, orbit refinement and re-flattening, phase transformation and geocoding.

4. The method for assessing highway slope risks based on the combined D-INSAR and TS-InSAR technologies according to claim 1, characterized in that, In S4, the deformation map is imported into the GIS software, and histogram equalization is performed on the deformation map; the deformation area exceeding the preset deformation amount is delineated, and the expanded deformation area is automatically identified as the potential danger area based on the neighborhood constraint clustering algorithm, and then the corresponding vector range is established.

5. The method for highway slope risk assessment based on D-INSAR and TS-InSAR combined technology according to claim 4, characterized in that, In S5, SAR data and digital elevation model (DEM) data are acquired based on the vector range. In the remote sensing processing software, the SAR data is cropped based on the vector range to obtain SAR image data.

6. The method for assessing highway slope risks based on the combined D-INSAR and TS-InSAR technologies according to claim 4, characterized in that, In S6, for SAR image data of the potential hazard area, TS-InSAR technology is used in conjunction with an amplitude dispersion index E. A A permanent scattering point PS is selected, a TS-InSAR time series model is constructed, and the deformation phase is calculated. Represented as Calculate linear phase Nonlinear deformation phase And by combining orbital parameters, the deformation values ​​at different times were inverted (defo). non-linear and annual deformation rate Δv p Orbital parameters include λ, 7. The method for assessing highway slope risks based on the combined D-INSAR and TS-InSAR technologies according to claim 6, characterized in that, In S7, the absolute value Δ of the deformation rate difference between all PS points at the top and bottom of the slope within the hazard area is calculated using GIS and Matlab software. v When the region Δ v When the value exceeds the pre-set threshold γ, it is identified as a high-risk area. Based on the existing PS points in the potential hazard area, the specific location is extracted, and a time-series cumulative deformation change diagram is drawn according to the time change. The potential causes of the target highway slope risk are analyzed, and the qualitative and quantitative analysis results of the target highway slope risk are obtained.

Images