Railway line landslide identification scale method and system

Abstract

The invention discloses a railway line landslide identification scale method and system, and relates to the technical field of mountain area railway landslide prevention and control, and the method comprises the following steps: collecting optical remote sensing images of a mountain along a railway in different time periods; processing the optical remote sensing image into a surface image by using a permanent scatterer-synthetic aperture radar interferometry technology, performing interference processing on the surface image, and judging a region stable state of a surface deformation region; the regional stable state comprises a stable region and an unstable region; and extracting landslide mass characteristics from the unstable area based on the optical remote sensing image, analyzing the landslide mass characteristics, and comprehensively evaluating the landslide mass according to an analysis result. According to the method, the permanent scatterer-synthetic aperture radar interference measurement technology and the optical remote sensing image are combined, so that accurate identification of the landslide crossing scale of the railway line is realized.

Description

Technical Field

[0001] The invention relates to the technical field of mountain railway landslide prevention and control, and in particular to a railway line landslide scale identification method and system. Background Art

[0002] After the railway is laid in the mountainous area, it faces natural disasters such as landslides. The scale of the landslide directly affects the extent of the loss caused to the railway project. Therefore, accurately identifying the scale of the landslide is of great significance for taking timely prevention and control measures and reducing the impact of the disaster. Traditional methods for identifying the scale of landslides mostly rely on on-site exploration and geological surveys. Although these methods are accurate, they are time-consuming and labor-intensive, and it is difficult to conduct real-time monitoring of large areas of mountains.

[0003] In the existing landslide identification technology system, the drawing of landslide survey maps plays a vital role; this step not only relies on the accurate identification and detailed record of currently known landslides, but also requires investigators to have rich geological knowledge and practical experience to ensure that the drawn landslide survey maps can truly and accurately reflect the geological conditions and landslide distribution of the target area; however, due to the complexity of geological conditions and the diversity of landslide phenomena, the accuracy of landslide survey maps is often restricted by many factors, including the integrity of historical data, the limitations of investigation methods and the subjective judgment of investigators; these factors may have a direct impact on subsequent analysis and prediction, and thus affect the early warning and prevention effects of landslide disasters.

[0004] On the other hand, the establishment of potential landslide identification standards is also a complex and challenging process. When formulating identification standards, it is necessary to comprehensively consider multiple factors such as geological structure, soil type, rainfall conditions, human activities, and the interactions and influences between these factors. Since these factors vary significantly in different regions and time scales, the formulation of identification standards must fully consider regional specificity to ensure their accuracy and effectiveness in practical applications. However, the looseness or strictness of identification standards is often a difficult balance to grasp. Standards that are too loose may lead to a large number of false alarms and increase unnecessary disaster prevention costs. Standards that are too strict may miss real potential landslides and reduce the sensitivity of the early warning system.

[0005] In addition, the empirical relationship between landslide volume and landslide area is also an important link in landslide identification; this relationship is usually based on a large amount of historical data and statistical analysis, and is used to predict and assess the scale and degree of hazard of landslides; however, due to the influence of various factors such as geological structure, soil type, rainfall conditions, etc., this empirical relationship may vary significantly in different regions and between different landslide types; therefore, in practical applications, the universal applicability of the empirical relationship is often limited and needs to be modified and adjusted according to specific circumstances.

[0006] In summary, the existing landslide identification methods still face many challenges and shortcomings in practical applications. In order to further improve the accuracy and reliability of landslide identification, it is necessary to continuously strengthen data collection and processing capabilities and improve the method of drawing landslide survey maps. At the same time, it is also necessary to conduct in-depth research on the principles and methods for formulating potential landslide identification standards to improve the scientificity and applicability of identification standards. In addition, it is also necessary to strengthen the research and verification of the empirical relationship between landslide volume and landslide area, as well as the monitoring and evaluation of the physical properties of landslide bodies.

[0007] Currently, no effective solution has been proposed for the problems in the related technologies. Summary of the invention

[0008] In view of the problems in the related art, the present invention proposes a method and system for identifying the scale of landslides on railway lines to overcome the above-mentioned technical problems existing in the existing related art.

[0009] To this end, the specific technical solution adopted by the present invention is as follows:

[0010] According to one aspect of the present invention, a method for identifying the scale of landslides on a railway line is provided, the method comprising the following steps:

[0011] S1. Collect optical remote sensing images of mountains along the railway in different time periods;

[0012] S2. Processing the optical remote sensing image into a surface image by using a permanent scatterer-synthetic aperture radar interferometry technique, and performing interferometry on the surface image to determine the regional stability state of the surface deformation area; the regional stability state includes a stable area and an unstable area;

[0013] S3. Extract the characteristics of the landslide body in the unstable area based on optical remote sensing images, analyze the characteristics of the landslide body, and comprehensively evaluate the landslide body based on the analysis results.

[0014] Furthermore, the optical remote sensing image is processed into a surface image by using the permanent scatterer-synthetic aperture radar interferometry technology, and the surface image is interferometrically processed to determine the regional stability state of the surface deformation area; the regional stability state includes a stable area and an unstable area, and includes the following steps:

[0015] S21. Use permanent scatterer-synthetic aperture radar interferometry technology to process optical remote sensing images and generate surface maps;

[0016] S22, performing interference processing on the surface map to generate a surface interference map, and extracting surface deformation data based on interference fringes in the surface interference map and using phase unwrapping technology;

[0017] S23. Calculate the surface deformation rate based on the surface deformation data, and determine the regional stability state of the surface deformation area according to the deformation rate result.

[0018] Furthermore, the optical remote sensing image is processed to generate a surface map including radiation correction, geometric correction and phase filtering.

[0019] Furthermore, judging the regional stability state of the surface deformation area based on the deformation rate results includes:

[0020] If the deformation rate range is -20mm / y<ρ<20mm / y, it is a stable region;

[0021] If the deformation rate is in the range of ρ≥20mm / y or ρ≤-20mm / y, it is an unstable region;

[0022] Here, ρ is the deformation rate.

[0023] Furthermore, based on the optical remote sensing image, the landslide features are extracted from the unstable area, and the landslide features are analyzed. According to the analysis results, the landslide is comprehensively evaluated, including the following steps:

[0024] S31. Based on the unstable area and combined with optical remote sensing images, the shape, size, color tone and crack distribution characteristics of the landslide body are extracted;

[0025] S32. Analyze the shape, size, color and crack distribution of the landslide body, and based on the analysis results, evaluate the scale, activity and stability of the landslide body;

[0026] S33. Based on the assessment results, conduct a comprehensive assessment of the landslide body to determine the size, sliding direction and sliding speed of the landslide body, and conduct a secondary assessment of the landslide body based on historical data and the geological background of the area where the landslide body is located.

[0027] Furthermore, the shapes of the landslide body include: dustpan-shaped landslide body, tongue-shaped landslide body and irregular-shaped landslide body;

[0028] A dustpan-shaped landslide is in the shape of a dustpan with a wide landslide wall and a narrow landslide tongue.

[0029] The tongue-shaped landslide is in the shape of a tongue with a narrow front end and a wide rear end.

[0030] Further, the shape of the landslide is analyzed. Based on the analysis results, the scale of the landslide is evaluated, including:

[0031] If the shape of the landslide body is a dustpan-shaped landslide body, the scale of the landslide body is a first-scale landslide body;

[0032] If the shape of the landslide body is a tongue-shaped landslide body, the scale of the landslide body is a second-scale landslide body;

[0033] If the shape of the landslide body is irregular, the scale of the landslide body is the third scale landslide body.

[0034] Furthermore, the size of the landslide body includes: the area of ​​the landslide body and the volume of the landslide body;

[0035] The volume calculation of the landslide body includes: estimating the volume of the landslide body by using the elevation information in the optical remote sensing image and combining the shape and thickness of the landslide body.

[0036] Furthermore, the color tone analysis of the landslide body includes: color tone difference analysis between the landslide body and the surrounding terrain and color tone change analysis of the landslide body.

[0037] According to another aspect of the present invention, a railway line landslide identification scale system is provided, the railway line landslide identification scale system comprising: a remote sensing image acquisition module, a regional stability state determination module and a landslide body assessment module;

[0038] The remote sensing image acquisition module is used to collect optical remote sensing images of mountains along the railway in different time periods;

[0039] The regional stability state determination module is used to process the optical remote sensing image into a surface image by using the permanent scatterer-synthetic aperture radar interferometry technology, and perform interferometry on the surface image to determine the regional stability state of the surface deformation area; the regional stability state includes a stable area and an unstable area;

[0040] The landslide body assessment module is used to extract landslide body features from unstable areas based on optical remote sensing images, analyze the landslide body features, and comprehensively assess the landslide body based on the analysis results.

[0041] The beneficial effects of the present invention are:

[0042] The present invention realizes accurate identification of the scale of landslides across a mountain where a railway line passes by combining permanent scatterer-synthetic aperture radar interferometry technology and optical remote sensing images; wherein the permanent scatterer-synthetic aperture radar interferometry technology provides surface deformation information, making it possible to make a preliminary assessment of the scale of the landslide; and the optical remote sensing images provide detailed characteristic information such as the shape, size, and color of the landslide body, further refining the identification of the scale of the landslide; the combined use of the permanent scatterer-synthetic aperture radar interferometry technology and the optical remote sensing images not only improves the accuracy and reliability of landslide scale identification, but also realizes a rapid assessment of the scale of the landslide, providing a scientific basis for the railway department to take preventive measures in a timely manner; in addition, the method can realize comprehensive monitoring and identification of landslides of different scales, helps to reduce the impact of landslides on railway operations, and improves the economy and reliability of railway safety line patrols. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0044] Figure 1 is a flow chart of a method for identifying the scale of a landslide on a railway line according to an embodiment of the present invention;

[0045] Figure 2 is a principle block diagram of a railway line landslide identification scale system according to an embodiment of the present invention;

[0046] Figure 3 The invention relates to an application process of synthetic aperture radar interferometry technology in a method for identifying the scale of landslides on a railway line according to an embodiment of the present invention;

[0047] Figure 4 is a technical flow chart of landslide scale identification in a method for identifying landslide scale on a railway line according to an embodiment of the present invention;

[0048] Figure 5 It is one of the partial flow charts of landslide characteristic analysis in a method for identifying the scale of a railway line landslide according to an embodiment of the present invention;

[0049] Figure 6 This is a second partial flow chart of landslide characteristic analysis in a method for identifying the scale of a railway landslide according to an embodiment of the present invention;

[0050] Figure 7 This is the third local flow chart of landslide characteristic analysis in a method for identifying the scale of landslides on a railway line according to an embodiment of the present invention.

[0051] In the figure:

[0052] 1. Remote sensing image acquisition module; 2. Regional stability determination module; 3. Landslide assessment module. DETAILED DESCRIPTION

[0053] To further illustrate each embodiment, the present invention provides drawings, which are part of the disclosure of the present invention and are mainly used to illustrate the embodiments. They can be used in conjunction with the relevant descriptions in the specification to explain the operating principles of the embodiments. With reference to these contents, ordinary technicians in this field should be able to understand other possible implementation methods and advantages of the present invention.

[0054] According to an embodiment of the present invention, a method and system for identifying the scale of landslides on a railway line are provided.

[0055] The present invention is further described with reference to the accompanying drawings and specific embodiments. Figure 1 As shown, according to one embodiment of the present invention, a method for identifying the scale of landslides on a railway line is provided, and the method comprises the following steps:

[0056] S1. Collect optical remote sensing images of mountains along the railway in different time periods.

[0057] It should be noted that optical remote sensing images are high-resolution optical remote sensing images, which can be collected through observation equipment such as satellites or airborne radar systems, or obtained through data platforms.

[0058] It should be noted that to obtain optical remote sensing images, it is necessary to conduct multiple observations of the target area (i.e., the mountains along the railway) to obtain image data covering the mountains along the railway; these data usually need to be obtained in different time periods for subsequent interference processing.

[0059] S2. Using permanent scatterer-synthetic aperture radar interferometry technology, the optical remote sensing image is processed into a surface image, and the surface image is interferometrically processed to determine the regional stability state of the surface deformation area; the regional stability state includes a stable area and an unstable area.

[0060] Specifically, the optical remote sensing image is processed into a surface image by using the permanent scatterer-synthetic aperture radar interferometry technology, and the surface image is interferometrically processed to determine the regional stability state of the surface deformation area; the regional stability state includes a stable area and an unstable area, and includes the following steps:

[0061] S21. Use permanent scatterer-synthetic aperture radar interferometry technology to process optical remote sensing images and generate surface maps;

[0062] S22, performing interference processing on the surface map to generate a surface interference map, and extracting surface deformation data based on interference fringes in the surface interference map and using phase unwrapping technology;

[0063] S23. Calculate the surface deformation rate based on the surface deformation data, and determine the regional stability state of the surface deformation area according to the deformation rate result.

[0064] It should be noted that the use of permanent scatterer-synthetic aperture radar interferometry (PS-InSAR) technology to monitor surface deformation is an advanced and efficient means of earth observation, especially suitable for complex mountainous terrains crossed by railway lines. This process not only relies on high-precision satellite or airborne radar systems, but also integrates complex signal processing technology and data analysis methods.

[0065] First of all, the core of PS-InSAR technology lies in synthetic aperture radar interferometry; Synthetic Aperture Radar (SAR) is an active microwave imaging radar that generates high-resolution surface images by emitting microwave pulses to the ground and receiving the reflected signals; unlike traditional optical remote sensing, SAR is not restricted by cloud cover and sunshine conditions and can work under all-weather and all-day conditions. It is particularly suitable for monitoring areas that are difficult to observe by conventional means, such as dense forests, cloudy mountainous areas, etc.

[0066] In PS-InSAR technology, at least two SAR images acquired at different times are used for interferometric processing; the phase information in these images is extracted and the difference between them is calculated to reveal information about surface deformation; this difference appears as interference fringes in the interferogram, each of which corresponds to a small deformation of a point on the surface between the two observations.

[0067] The pre-processed SAR images are interferometrically processed to generate an interferogram. In this process, the phase information in the two images needs to be accurately matched to reveal information about surface deformation.

[0068] Through the interference fringes in the interference pattern, the specific information of the surface deformation can be extracted using technical means such as phase unwrapping. This information is usually expressed in the form of deformation rate, deformation amount, etc., which can intuitively reflect the deformation of the surface in different time periods.

[0069] Specifically, the optical remote sensing image is processed to generate a surface map including: radiation correction, geometric correction and phase filtering.

[0070] It should be noted that the collected images are preprocessed, including radiation correction, geometric correction, phase filtering and other steps, to improve the image quality and the accuracy of the interference processing.

[0071] Specifically, judging the regional stability state of the surface deformation area based on the deformation rate results includes:

[0072] If the deformation rate range is -20mm / y<ρ<20mm / y, it is a stable region;

[0073] If the deformation rate is in the range of ρ≥20mm / y or ρ≤-20mm / y, it is an unstable region;

[0074] Here, ρ is the deformation rate.

[0075] It should be noted that mm / y represents the deformation in millimeters per year.

[0076] It should be noted that the specific steps of using the permanent scatterer-synthetic aperture radar interferometry technique to determine the regional stability of the surface deformation area are as follows: Figure 3 and Figure 4 shown.

[0077] S3. Based on the unstable surface deformation area and combined with high-resolution optical remote sensing images, the characteristics of the landslide body are extracted and analyzed, and the landslide body is comprehensively evaluated based on the analysis results.

[0078] It should be noted that the specific steps for comprehensive assessment of landslide masses in unstable surface deformation areas are as follows: Figure 5 , Figure 6 and Figure 7 As shown, Figure 5 The line at a in Figure 6 Connect the line at a in the figure; Figure 6 The line at point b in Figure 7 Connect the line at point b in the figure.

[0079] Specifically, based on the optical remote sensing image, the landslide body characteristics are extracted from the unstable area, and the landslide body characteristics are analyzed. The comprehensive evaluation of the landslide body according to the analysis results includes the following steps:

[0080] S31. Based on the unstable area and combined with optical remote sensing images, the shape, size, color tone and crack distribution characteristics of the landslide body are extracted;

[0081] S32. Analyze the shape, size, color and crack distribution of the landslide body, and based on the analysis results, evaluate the scale, activity and stability of the landslide body;

[0082] S33. Based on the assessment results, conduct a comprehensive assessment of the landslide body to determine the size, sliding direction and sliding speed of the landslide body, and conduct a secondary assessment of the landslide body based on historical data and the geological background of the area where the landslide body is located.

[0083] It should be noted that in the unstable area, look for areas with armchair-shaped back walls, areas that are relatively flat compared to the surrounding slopes, areas with tongue-shaped or arc-shaped slopes, etc., and then see whether the color is grayish white, khaki, or dark brown. Then see whether the area has two gullies of the same origin, cracks, multiple terraces, and is mostly distributed in valley areas. Finally, see if there are exposed rock and soil and little vegetation. Based on these interpretation signs, you can determine that the area is a potential landslide.

[0084] For unstable areas, high-resolution optical remote sensing images are used to identify the scale of landslides. Through image interpretation, the shape, size, color, crack distribution and other characteristics of the landslide body are analyzed to accurately assess the scale of the landslide.

[0085] Specifically, the shapes of the landslide body include: dustpan-shaped landslide body, tongue-shaped landslide body and irregular-shaped landslide body;

[0086] A dustpan-shaped landslide is in the shape of a dustpan with a wide landslide wall and a narrow landslide tongue.

[0087] The tongue-shaped landslide is in the shape of a tongue with a narrow front end and a wide rear end.

[0088] Specifically, the shape of the landslide is analyzed, and based on the analysis results, the scale of the landslide is assessed, including:

[0089] If the shape of the landslide body is a dustpan-shaped landslide body, the scale of the landslide body is a first-scale landslide body;

[0090] If the shape of the landslide body is a tongue-shaped landslide body, the scale of the landslide body is a second-scale landslide body;

[0091] If the shape of the landslide body is irregular, the scale of the landslide body is the third scale landslide body.

[0092] Specifically, the size of the landslide body includes: the area of ​​the landslide body and the volume of the landslide body;

[0093] The volume calculation of the landslide body includes: estimating the volume of the landslide body by using the elevation information in the optical remote sensing image and combining the shape and thickness of the landslide body.

[0094] Specifically, the color tone analysis of the landslide body includes: color tone difference analysis between the landslide body and the surrounding terrain and color tone change analysis of the landslide body.

[0095] It should be noted that for the determined unstable areas, combined with the interpretation of high-resolution optical remote sensing images, the interpretation signs are as follows: in the high-resolution optical remote sensing images, first look for areas with armchair-shaped back walls, areas that are relatively flat compared to the surrounding slopes, areas with tongue-shaped or arc-shaped slopes, etc. in the unstable areas, then see whether the color is grayish white, khaki, or dark brown, then see whether the area has two gullies of the same origin, cracks, multiple terraces, and is mostly distributed in valley areas, and finally see if there are exposed rock and soil and little vegetation. Based on these interpretation signs, the area can be judged as a potential landslide.

[0096] The shape analysis of landslide is an important clue to assess its scale. Through remote sensing data, the plane and three-dimensional shapes of landslide can be clearly observed. Common landslide shapes include dustpan shape, tongue shape, irregular shape, etc.

[0097] Dustpan-shaped landslide: usually has a wider landslide wall and a narrower landslide tongue, and the overall landslide body is fan-shaped; this type of landslide is often large in scale and has a long sliding distance. It is a first-scale landslide body, that is, a large-scale landslide body.

[0098] Tongue-shaped landslide: The shape of the landslide body is similar to a tongue, which is narrow at the front end and wide at the back end. This type of landslide may be medium to large in scale and slide quickly. It is a second-scale landslide body, that is, a medium-scale landslide body.

[0099] Irregular landslide: The shape is complex and varied, with no obvious rules; the scale of this type of landslide may vary depending on the specific situation, and other characteristics need to be combined to determine it as a third-scale landslide, that is, a large-scale landslide.

[0100] The size of a landslide is mainly assessed through its area, volume and other parameters. Area assessment uses the scale and measurement tools in remote sensing data to estimate the area of ​​a landslide. The area size directly reflects the scale of a landslide. Volume assessment uses the elevation information in remote sensing data combined with the shape and thickness of the landslide to estimate the volume of a landslide. Volume is an important parameter for assessing the scale of a landslide and an important basis for determining the degree of hazard caused by a landslide.

[0101] The color tone analysis of landslide bodies usually shows differences with the color tone of the surrounding terrain. In remote sensing data, the existence and scale of landslide bodies can be judged by color tone comparison. The color tone difference is because the color tone of landslide bodies is often different from that of the surrounding terrain due to the material composition and friction during the sliding process. For example, the landslide body may have a darker color tone, while the surrounding terrain has a lighter color tone. The color tone change is that the color tone may change with the sliding of the landslide body and the passage of time. For example, the vegetation coverage on the surface of the landslide body may decrease, causing the color tone to become lighter. This color tone change can also serve as an important clue to judge the scale and activity of the landslide.

[0102] The analysis of landslide crack distribution is the result of stress release inside the landslide body, and is also an important indicator for judging the scale and activity of the landslide. Among them, crack types include tension cracks and shear cracks. Tension cracks are usually related to the tensile deformation of the landslide body, while shear cracks are related to the shear deformation of the landslide body. Among them, crack distribution can be observed through high-resolution images in remote sensing data. Parameters such as the number, length, width and direction of cracks can be used as important basis for judging the scale and activity of the landslide.

[0103] The relationship between cracks and landslide scale: Generally speaking, the more and denser the cracks are, the worse the stability of the landslide body and the greater the sliding potential; at the same time, the distribution of cracks can also reflect information such as the sliding direction and sliding speed of the landslide body.

[0104] Comprehensive assessment of landslide scale: After analyzing the shape, size, color and crack distribution of the landslide body, it is necessary to integrate this information to assess the scale of the landslide.

[0105] Comprehensive judgment: Comprehensively analyze the shape, size, color and crack distribution of the landslide to determine the scale, sliding direction and sliding speed of the landslide.

[0106] Comparison with historical data: If possible, the current landslide characteristics can be compared with historical landslide events to more accurately assess the size and severity of the landslide.

[0107] Consider the geological background: The occurrence of landslides is closely related to the geological background; therefore, when assessing the scale of a landslide, it is also necessary to consider the impact of factors such as the geological structure, soil type, and rainfall conditions in the area where the landslide is located on the scale and activity of the landslide.

[0108] In summary, by analyzing the shape, size, color and crack distribution of the landslide in remote sensing data, the scale of the landslide can be assessed more accurately; this requires the comprehensive use of remote sensing technology, geological knowledge, data analysis methods and other knowledge and skills; at the same time, it is also necessary to pay attention to comprehensive analysis and judgment based on actual conditions and historical data.

[0109] With the rapid development of remote sensing technology, especially the application of synthetic aperture radar interferometry (InSAR) and high-resolution optical remote sensing images, new means have been provided for the rapid identification of landslide scale. When determining the scale of a landslide, in addition to relying on the accuracy of geological surveys and InSAR data analysis, the physical properties of the landslide body (such as density, water content, etc.) also need to be considered. These properties are of great significance for assessing the stability and degree of hazard of a landslide.

[0110] Only in this way can we establish a more complete and effective landslide identification system to provide more powerful support for the early warning and prevention of landslide disasters. Therefore, in order to further improve the accuracy and reliability of landslide identification, it is necessary to continuously optimize and improve these methods and technical means, including strengthening data collection and processing, improving the accuracy of landslide investigation and identification, establishing more generally applicable empirical relationships, improving methods for determining landslide scale, and enhancing the comprehensiveness and adaptability of methods. Through these efforts, potential landslides can be identified more effectively, providing strong support for disaster assessment, risk management, monitoring and prevention of landslide disasters, and providing guarantees for the safe operation of mountain lines.

[0111] like Figure 2 As shown, according to another embodiment of the present invention, a railway line landslide identification scale system is provided, and the railway line landslide identification scale system includes: a remote sensing image acquisition module, a regional stability state determination module and a landslide body assessment module;

[0112] The remote sensing image acquisition module 1 is used to collect optical remote sensing images of mountains along the railway in different time periods;

[0113] The regional stability state determination module 2 is used to process the optical remote sensing image into a surface image by using the permanent scatterer-synthetic aperture radar interferometry technology, and perform interferometry on the surface image to determine the regional stability state of the surface deformation area; the regional stability state includes a stable area and an unstable area;

[0114] The landslide body assessment module 3 is used to extract landslide body features from unstable areas based on optical remote sensing images, analyze the landslide body features, and comprehensively assess the landslide body based on the analysis results.

[0115] It should be noted that the extracted surface deformation information will be comprehensively analyzed with geological, meteorological and other background data to evaluate the stability of the railway line through the mountain and promptly discover potential geological disaster risks such as landslides and mudslides.

[0116] Based on the analysis results, a surface deformation monitoring report is compiled to provide a scientific basis for the railway department's operational safety, maintenance decisions and disaster warning.

[0117] By using InSAR technology to monitor surface deformation, the railway department can achieve continuous and high-precision monitoring of railway lines passing through mountains, promptly detect and respond to potential geological disaster risks, and ensure the safety and stability of railway operations.

[0118] For example, taking the identification of potential landslides along a railway section as an example, the method of the present invention is used to evaluate the landslide hazard; first, the PS-InSAR (Permanent Scatterer-Synthetic Aperture Radar Interferometry) technology is used to obtain surface deformation information and divide stable areas and unstable areas; then, the landslide characteristics of the unstable areas are analyzed in combination with optical remote sensing images, and it is found that there is a potential landslide in the mountain area next to a railway tunnel entrance; finally, according to factors such as the scale, speed, and potential impact of the landslide, the hazard of the landslide is comprehensively evaluated, providing timely data support for preventing railway disasters.

[0119] In summary, with the help of the above technical scheme of the present invention, the present invention realizes the accurate identification of the scale of landslides passing through the mountain by combining the permanent scatterer-synthetic aperture radar interferometry technology and optical remote sensing images; wherein the permanent scatterer-synthetic aperture radar interferometry technology provides surface deformation information, making it possible to make a preliminary assessment of the scale of the landslide; and the optical remote sensing image provides detailed characteristic information such as the shape, size, and color of the landslide body, further refining the identification of the scale of the landslide; the combined use of the permanent scatterer-synthetic aperture radar interferometry technology and the optical remote sensing image not only improves the accuracy and reliability of the identification of the scale of the landslide, but also realizes the rapid assessment of the scale of the landslide, providing a scientific basis for the railway department to take preventive measures in a timely manner; in addition, the method can realize the comprehensive monitoring and identification of landslides of different scales, which helps to reduce the impact of landslides on railway operations and improve the economy and reliability of railway safety patrols.

[0120] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for identifying the scale of landslides on railway lines, characterized in that: The method comprises the following steps: S1. Collect optical remote sensing images of mountains along the railway in different time periods; S2. Processing the optical remote sensing image into a surface image by using a permanent scatterer-synthetic aperture radar interferometry technique, and performing interferometry on the surface image to determine the regional stability state of the surface deformation area; the regional stability state includes a stable area and an unstable area; S3. Extract the characteristics of the landslide body in the unstable area based on optical remote sensing images, analyze the characteristics of the landslide body, and comprehensively evaluate the landslide body based on the analysis results.

2. A method for identifying the scale of landslides on a railway line according to claim 1, characterized in that: The method uses the permanent scatterer-synthetic aperture radar interferometry technology to process the optical remote sensing image into a surface image, and performs interferometry on the surface image to determine the regional stability state of the surface deformation area; the regional stability state includes a stable area and an unstable area, and includes the following steps: S21. Use permanent scatterer-synthetic aperture radar interferometry technology to process optical remote sensing images and generate surface maps; S22, performing interference processing on the surface map to generate a surface interference map, and extracting surface deformation data based on interference fringes in the surface interference map and using phase unwrapping technology; S23. Calculate the surface deformation rate based on the surface deformation data, and determine the regional stability state of the surface deformation area according to the deformation rate result.

3. A method for identifying the scale of landslides on railway lines according to claim 2, characterized in that: The surface map generated by processing the optical remote sensing image includes: radiation correction, geometric correction and phase filtering.

4. A method for identifying the scale of landslides on a railway line according to claim 2, characterized in that: The determining of the regional stability state of the surface deformation region according to the deformation rate result includes: If the deformation rate is in the range of -20mm / y<ρ<20mm / y, it is a stable region; If the deformation rate is in the range of ρ≥20mm / y or ρ≤-20mm / y, it is an unstable region; Here, ρ is the deformation rate.

5. A method for identifying the scale of landslides on railway lines according to claim 1, characterized in that: The method of extracting landslide features from unstable areas based on optical remote sensing images, analyzing the landslide features, and comprehensively evaluating the landslide according to the analysis results includes the following steps: S31. Based on the unstable area and combined with optical remote sensing images, the shape, size, color tone and crack distribution characteristics of the landslide body are extracted; S32. Analyze the shape, size, color and crack distribution of the landslide body, and based on the analysis results, evaluate the scale, activity and stability of the landslide body; S33. Based on the assessment results, conduct a comprehensive assessment of the landslide body to determine the size, sliding direction and sliding speed of the landslide body, and conduct a secondary assessment of the landslide body based on historical data and the geological background of the area where the landslide body is located.

6. A method for identifying the scale of landslides on railway lines according to claim 5, characterized in that: The shapes of the landslide bodies include: dustpan-shaped landslide bodies, tongue-shaped landslide bodies and irregular-shaped landslide bodies; The dustpan-shaped landslide body is in the shape of a dustpan with a wide landslide wall and a narrow landslide tongue; The tongue-shaped landslide body is in the shape of a tongue with a narrow front end and a wide rear end.

7. A method for identifying the scale of landslides on railway lines according to claim 6, characterized in that: The shape analysis of the landslide body and the assessment of the scale of the landslide body based on the analysis results include: If the shape of the landslide body is a dustpan-shaped landslide body, the scale of the landslide body is a first-scale landslide body; If the shape of the landslide body is a tongue-shaped landslide body, the scale of the landslide body is a second-scale landslide body; If the shape of the landslide body is irregular, the scale of the landslide body is the third scale landslide body.

8. A method for identifying the scale of landslides on a railway line according to claim 5, characterized in that: The size of the landslide body includes: the area of ​​the landslide body and the volume of the landslide body; The volume calculation of the landslide body includes: estimating the volume of the landslide body by using the elevation information in the optical remote sensing image and combining the shape and thickness of the landslide body.

9. A method for identifying the scale of landslides on railway lines according to claim 5, characterized in that: The color tone analysis of the landslide body includes: color tone difference analysis between the landslide body and the surrounding terrain and color tone change analysis of the landslide body.

10. A railway line landslide identification scale system, used to implement the railway line landslide identification scale method according to any one of claims 1 to 9, characterized in that: The railway line landslide identification scale system includes: remote sensing image acquisition module, regional stability state determination module and landslide body assessment module; The remote sensing image acquisition module is used to collect optical remote sensing images of mountains along the railway in different time periods; The regional stability state determination module is used to process the optical remote sensing image into a surface image by using the permanent scatterer-synthetic aperture radar interferometry technology, and perform interferometry on the surface image to determine the regional stability state of the surface deformation area; the regional stability state includes a stable area and an unstable area; The landslide body assessment module is used to extract landslide body features from unstable areas based on optical remote sensing images, analyze the landslide body features, and comprehensively assess the landslide body based on the analysis results.

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