Fault zone dislocation measurement method, device and electronic equipment

Abstract

The present invention provides a method, device, and electronic device for measuring fault zone dislocation, relating to the field of surveying and mapping technology. The method comprises: obtaining DEM data of a target fault area; extracting contour lines intersecting the fault line from the DEM data and generating vertical profile lines along the fault line to obtain contour line data and profile line data; and using the RANSAC algorithm to calculate horizontal and vertical dislocations on the contour line data and profile line data, respectively, to obtain the horizontal and vertical dislocation distributions of the target fault area. The present invention can realize automated measurement of horizontal and vertical dislocations in fault zones, improving the applicability of complex terrain and the resolution of dislocation measurement.

Description

Technical Field

[0001] The present invention relates to the field of surveying and mapping technology, and in particular to a method, device and electronic equipment for measuring fault zone dislocation. Background Art

[0002] Automatic extraction of fault dislocations is a key area of ​​research in earthquake science and tectonic geomorphology. By combining high-resolution topographic data with automated algorithms, we can efficiently and accurately quantify fault slip characteristics, revealing earthquake history and fault evolution patterns. This not only improves research efficiency but also reduces the subjective errors associated with traditional manual measurements, which is of great significance for earthquake hazard assessment and fault activity monitoring.

[0003] In recent years, with the rapid development of remote sensing technology and geographic information systems, high-resolution topographic data has provided crucial support for the automated extraction and quantitative analysis of fault offsets. Numerous researchers have developed various algorithms and tools to automatically extract fault offsets, such as LaDiCaos, 3D_Fault_Offsets, SPARTA, and AutoThrow. These algorithms have significantly improved the efficiency and accuracy of fault slip and morphological feature extraction. While LaDiCaos and 3D_Fault_Offsets primarily measure horizontal offsets based on geomorphic landmarks of fault offsets, SPARTA and AutoThrow focus on measuring vertical offsets at the fault sill.

[0004] However, existing methods generally have problems such as insufficient applicability to complex terrain and insufficient capture of fine morphological features of faults. Summary of the Invention

[0005] The purpose of the present invention is to provide a method, device and electronic equipment for measuring fault zone dislocation, so as to improve the applicability of complex terrain and the resolution of dislocation measurement.

[0006] In a first aspect, the present invention provides a method for measuring dislocation in a fault zone, comprising:

[0007] Obtain DEM data of the target fault area;

[0008] Extract the contour lines that intersect the fault lines and generate vertical profile lines along the fault lines from the DEM data to obtain contour line data and profile line data;

[0009] The RANSAC algorithm is used to calculate the horizontal and vertical dislocations of the contour data and profile data respectively, and the horizontal and vertical dislocation distributions of the target fault area are obtained.

[0010] In an optional embodiment, the DEM data is subjected to contour extraction that intersects the fault line and vertical profile generation along the fault line to obtain contour line data and profile line data, including:

[0011] Extract the elevation value on the fault line from the DEM data to obtain the target elevation value, and based on the target elevation value, extract the contour data from the DEM data;

[0012] Generate vertical profile lines along the fault lines for the DEM data to obtain profile line data.

[0013] In an optional embodiment, the RANSAC algorithm is used to calculate the horizontal dislocation and vertical dislocation of the contour data and the profile data respectively to obtain the horizontal dislocation distribution and the vertical dislocation distribution of the target fault area, including:

[0014] Based on the contour data and the RANSAC algorithm, the initial horizontal displacement data of the target fault area is determined. The slope of the fault strike and the angle between the contour line and the fault line are used to correct the error caused by the vertical displacement of the initial horizontal displacement data to obtain the intermediate horizontal displacement data.

[0015] Determine the initial vertical displacement data of the target fault area based on the profile data and the RANSAC algorithm;

[0016] The horizontal dislocation distribution and the vertical dislocation distribution are determined based on the intermediate horizontal dislocation data and the initial vertical dislocation data.

[0017] In an optional embodiment, determining initial horizontal dislocation data of a target fault region based on contour data and a RANSAC algorithm includes:

[0018] Determine the confidence region of the target fault area based on the minimum buffer and maximum buffer corresponding to the fault line in the DEM data;

[0019] Filtering the contour line data according to preset filtering conditions to obtain candidate contour line data; wherein the preset filtering conditions include intersecting with the fault line and being at least partially located within the confidence region;

[0020] The RANSAC algorithm is used to perform linear fitting within the confidence region on the first part and the second part of each candidate contour line separated by the fault line in the candidate contour line data, and the first fitting straight line and the second fitting straight line corresponding to each candidate contour line are obtained;

[0021] The horizontal displacement is calculated based on the first fitting straight line and the second fitting straight line corresponding to each candidate contour line to obtain initial horizontal dislocation data.

[0022] In an optional embodiment, the horizontal displacement is calculated based on the first fitting straight line and the second fitting straight line corresponding to each candidate contour line to obtain initial horizontal dislocation data, including:

[0023] Performing a slope difference test on the first fitted straight line and the second fitted straight line corresponding to each candidate contour line to obtain a target contour line that meets a preset slope difference condition; wherein the preset slope difference condition includes that the absolute value of the slope difference between the first fitted straight line and the second fitted straight line is less than a preset slope threshold;

[0024] Calculate the intersection points of the first fitting straight line and the fault line and the intersection points of the second fitting straight line and the fault line corresponding to each target contour line respectively, and obtain the first intersection point and the second intersection point corresponding to each target contour line;

[0025] The distance between the first intersection point and the second intersection point corresponding to each target contour line is determined as the initial horizontal displacement of each target contour line;

[0026] The initial horizontal displacements of all target contour lines are determined as initial horizontal dislocation data.

[0027] In an optional embodiment, the initial horizontal dislocation data is corrected for errors caused by vertical displacement using the slope of the fault strike and the angle between the contour line and the fault line to obtain intermediate horizontal dislocation data, including:

[0028] For each target contour line in the initial horizontal dislocation data, a vertical profile line of the target contour line at the fault line is obtained;

[0029] According to the vertical profile line and RANSAC algorithm, the vertical displacement height of the target contour line and the angle between the target contour line and the fault line are determined;

[0030] The error difference corresponding to the target contour line is calculated based on the vertical dislocation height of the target contour line, the angle between the target contour line and the fault line, and the slope of the target contour line at the fault line;

[0031] The initial horizontal displacement of the target contour line is corrected using the bit error difference corresponding to the target contour line to obtain the intermediate horizontal displacement of the target contour line.

[0032] In an optional embodiment, determining the vertical dislocation height of the target contour line and the angle between the target contour line and the fault line based on the vertical profile line and the RANSAC algorithm includes:

[0033] Extract the elevation values ​​on the vertical section line from the DEM data to obtain the first elevation value sequence;

[0034] The RANSAC algorithm is used to perform linear fitting on the hanging wall data and the footwall data in the first elevation value sequence to obtain the first hanging wall fitting line and the first footwall fitting line;

[0035] The intercept difference between the first hanging wall fitting straight line and the first footwall fitting straight line at the fault line is determined as the vertical dislocation height of the target contour line;

[0036] The average of the angles between the first hanging wall fitting straight line and the fault line and the angles between the first footwall fitting straight line and the fault line is determined as the angle between the target contour line and the fault line.

[0037] In an optional embodiment, determining the horizontal dislocation distribution and the vertical dislocation distribution based on the intermediate horizontal dislocation data and the initial vertical dislocation data includes:

[0038] Using the Monte Carlo method and probability density function, the intermediate horizontal dislocation data and the initial vertical dislocation data are eliminated for outliers to obtain the target horizontal dislocation data and the target vertical dislocation data;

[0039] The target horizontal dislocation data and the target vertical dislocation data are interpolated or smoothed to obtain a continuous horizontal dislocation distribution and a continuous vertical dislocation distribution along the fault line in the target fault area.

[0040] In a second aspect, the present invention provides a fault zone dislocation measurement device, comprising:

[0041] Acquisition module, used to obtain DEM data of target fault area;

[0042] The generation module is used to extract the contour lines intersecting the fault lines and generate vertical profile lines along the fault lines from the DEM data to obtain the contour line data and profile line data;

[0043] The calculation module is used to calculate the horizontal dislocation and vertical dislocation of the contour data and the profile data respectively using the RANSAC algorithm to obtain the horizontal dislocation distribution and vertical dislocation distribution of the target fault area.

[0044] In a third aspect, the present invention provides an electronic device comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the computer program, the fault zone dislocation measurement method of any one of the aforementioned embodiments is implemented.

[0045] The fault zone dislocation measurement method, device, and electronic device provided by the present invention can obtain DEM data of the target fault area; extract contour lines intersecting the fault line and generate vertical profile lines along the fault line from the DEM data to obtain contour line data and profile line data; use the RANSAC algorithm to calculate horizontal and vertical dislocations of the contour line data and profile line data, respectively, to obtain the horizontal and vertical dislocation distributions of the target fault area. In this way, by using the DEM data of the target fault area to generate contour line data and profile line data, and then combining the RANSAC algorithm, the horizontal and vertical dislocation distributions of the fault zone can be automatically measured. This method does not rely on obvious landform landmarks and can fully utilize high-resolution DEM data, so that the resolution of the dislocation measurement is consistent with the DEM data, thereby improving the applicability of complex terrain and the resolution of dislocation measurement. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0047] Figure 1 A schematic flow chart of a method for measuring dislocation in a fault zone provided by an embodiment of the present invention;

[0048] Figure 2 A schematic diagram of a data collection process provided by an embodiment of the present invention;

[0049] Figure 3 A schematic diagram of a flow chart of horizontal dislocation calculation provided by an embodiment of the present invention;

[0050] Figure 4 A schematic diagram of a vertical dislocation calculation process provided by an embodiment of the present invention;

[0051] Figure 5 A schematic diagram of the principle of horizontal dislocation calculation based on contour fitting provided by an embodiment of the present invention;

[0052] Figure 6 A schematic diagram of a vertical bit error difference provided by an embodiment of the present invention;

[0053] Figure 7 A schematic diagram of dense cross-hatching generation provided by an embodiment of the present invention;

[0054] Figure 8 A schematic diagram of the principle of vertical dislocation calculation provided by an embodiment of the present invention;

[0055] Figure 9 A schematic structural diagram of a fault zone dislocation measurement device provided by an embodiment of the present invention;

[0056] Figure 10 A schematic structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0057] The following will clearly and completely describe the technical solutions of the present invention in conjunction with the embodiments. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0058] Currently, existing fault zone dislocation measurement methods generally have problems such as insufficient applicability to complex terrain, insufficient capture of fine morphological features of faults, and insufficient utilization of high-precision DEM (Digital Elevation Model) data. Further improvement is still needed in terms of algorithm innovation and data fusion to solve the applicability problems in complex terrain and promote the development of automated and intelligent fault extraction technology. Based on this, the embodiments of the present invention provide a fault zone dislocation measurement method, device, and electronic device that can utilize high-resolution digital elevation model (DEM) and dense contour data, combined with the RANSAC (Random Sample Consensus) algorithm, to achieve automated measurement of horizontal and vertical displacements of the fault zone, providing important data support and technical guarantees for earthquake activity analysis, fault stability assessment, etc., and helping scientists to deeply understand the mechanism of fault activity.

[0059] To facilitate understanding of this embodiment, a method for measuring dislocation in a fault zone disclosed in an embodiment of the present invention is first introduced in detail.

[0060] The embodiment of the present invention provides a method for measuring dislocation in a fault zone, which can be performed by an electronic device with data processing capabilities. Figure 1 The flowchart of a method for measuring dislocation in a fault zone is shown, and the method mainly includes the following steps S110 to S130:

[0061] Step S110: Acquire DEM data of the target fault area.

[0062] The target fault area is where fault zone displacement measurement is required. High-precision DEM data can be obtained using unmanned aerial vehicles (UAVs, such as UAV lidar or SfM technology) or high-resolution satellite stereo image pairs (such as Gaofen-7 satellite data). The spatial resolution of the DEM data should meet the accuracy requirements for fault identification and displacement measurement (for example, a spatial resolution better than 1 meter).

[0063] Specifically, high-precision DEM data can be obtained using drone lidar, SfM technology, or Gaofen-7 (GF7) satellite data. UAV lidar, also known as airborne laser radar (LiDAR), offers high accuracy. SfM, short for Structure from Motion, uses a drone-mounted camera to capture images covering the target fault area, generating DEM data. GF7 satellite data is also inexpensive and relatively low-cost. Depending on actual needs, one method can be selected to obtain DEM data for the target fault area: drone lidar, SfM, or GF7 satellite data. Specifically, drone photos acquired with SfM technology and GF7's fore- and aft-view imagery can be processed using software such as Agisoft Metashape for DEM data processing, including photo alignment (i.e., image registration), dense point cloud generation (i.e., 3D point cloud reconstruction), and DEM generation. For UAV lidar, TerraSolid software can be used to separate ground points and non-ground points from the airborne LiDAR point cloud data (i.e., point cloud filtering), and then the ground points can be constructed into a DEM through an irregular triangulated network or grid (i.e., DEM generation).

[0064] Step S120 , extracting contour lines intersecting the fault lines and generating vertical profile lines along the fault lines from the DEM data to obtain contour line data and profile line data.

[0065] In some possible embodiments, the above-mentioned step S120 includes: extracting the elevation value on the fault line of the DEM data to obtain the target elevation value, and extracting contour data from the DEM data based on the target elevation value; generating a vertical profile line along the fault line of the DEM data to obtain profile line data.

[0066] The fault lines in the DEM data may be manually drawn or automatically identified. Optionally, the step of extracting the elevation values ​​on the fault lines from the DEM data to obtain the target elevation values ​​may include: identifying the fault lines on the DEM data to obtain the target fault lines; and obtaining the elevation values ​​at the target fault lines from the DEM data to obtain the target elevation values.

[0067] Here, the fault line identified in the DEM data is called the target fault line. The elevation value at the target fault line can be obtained by combining the resolution of the DEM data, so that the resolution of the elevation value at the target fault line is equal to the resolution of the DEM data. For example, if the resolution of the DEM data is 1 meter, the elevation value at the target fault line is also 1 meter apart.

[0068] In one possible implementation, the target fault line can be obtained by calculating the first-order derivative of the DEM data to obtain gradient data; and then performing edge detection on the gradient data using a preset edge detection algorithm to obtain the target fault line. The edge detection algorithm can be selected based on actual needs and is not limited here.

[0069] Furthermore, considering that the coordinate system of the target fault line may be inconsistent with the coordinate system of the DEM data, the coordinate system of the target fault line can be converted so that the coordinate system of the target fault line is consistent with the coordinate system of the DEM data, that is, the two are in the same projection coordinate system, to facilitate subsequent processing.

[0070] Step S130 , using the RANSAC algorithm, calculates the horizontal dislocation and vertical dislocation of the contour line data and the profile line data respectively, and obtains the horizontal dislocation distribution and the vertical dislocation distribution of the target fault area.

[0071] The RANSAC algorithm is an iterative method for estimating the parameters of a mathematical model from a set of data containing outliers. The main advantage of RANSAC is its robustness to outliers.

[0072] In some possible embodiments, the above step S130 may include the following steps S131 to S133:

[0073] In step S131, the initial horizontal dislocation data of the target fault area is determined based on the contour data and the RANSAC algorithm. The error caused by the vertical displacement of the initial horizontal dislocation data is corrected using the slope of the fault direction and the angle between the contour line and the fault line to obtain the intermediate horizontal dislocation data.

[0074] The horizontal dislocation of the fault can be calculated from the contour line dislocation characteristics. Moreover, based on the traditional method that only focuses on the horizontal dislocation, the interference and error caused by the vertical displacement on the horizontal displacement are further considered, and correction is performed through geometric and trigonometric relationships, which greatly improves the accuracy and reliability of the dislocation measurement.

[0075] Optionally, the core idea of ​​a horizontal dislocation calculation is to use a fault line to divide the contour line into two sides, and by linearly fitting the contour line segments, measure the relative horizontal offset of the contour lines on both sides at the fault. Based on this, the step of determining the initial horizontal dislocation data of the target fault area according to the contour line data and the RANSAC algorithm can include: determining the confidence region of the target fault area according to the minimum buffer and maximum buffer corresponding to the fault line in the DEM data; filtering the contour line data according to preset filtering conditions to obtain candidate contour line data; wherein the preset filtering conditions include intersecting with the fault line and being at least partially located within the confidence region; using the RANSAC algorithm to perform linear fitting within the confidence region on the first and second parts of each candidate contour line in the candidate contour line data, which are separated by the fault line, to obtain the first fitted straight line and the second fitted straight line corresponding to each candidate contour line; calculating the horizontal displacement according to the first fitted straight line and the second fitted straight line corresponding to each candidate contour line to obtain the initial horizontal dislocation data. By screening the contour data, it is possible to ensure that the candidate contours intersect the fault lines and are at least partially located within the confidence region, thereby enabling subsequent linear fitting.

[0076] The buffer zone is used to describe the safety distance or impact range associated with the fault line. The minimum buffer zone refers to the shortest distance set to ensure safety. The maximum buffer zone represents a wider safety distance. Furthermore, the above-mentioned step of determining the confidence zone of the target fault area based on the minimum buffer zone and the maximum buffer zone corresponding to the fault line in the DEM data may include: buffering the fault line in the DEM data according to the preset minimum buffer distance and the maximum buffer distance to obtain the minimum buffer zone and the maximum buffer zone; and determining the ring zone area after removing the minimum buffer zone from the maximum buffer zone as the confidence zone of the target fault area. Among them, the minimum buffer distance and the maximum buffer distance can be set according to actual needs and are not limited here. For example, the value range of the minimum buffer distance can be the minimum buffer radius: 10 to 30 m, and the value range of the maximum buffer distance can be the maximum buffer radius: 200 to 300 m.

[0077] Considering that if the difference in slope between the first fitting straight line and the second fitting straight line of a contour line is too large, it means that the shape of the contour line on both sides of the fault line is too inconsistent and is not suitable as a basis for dislocation measurement and can be eliminated. Based on this, the above-mentioned step of calculating the horizontal displacement according to the first fitting straight line and the second fitting straight line corresponding to each candidate contour line to obtain the initial horizontal dislocation data may include: performing a slope difference test on the first fitting straight line and the second fitting straight line corresponding to each candidate contour line to obtain a target contour line that meets a preset slope difference condition; wherein the preset slope difference condition includes that the absolute value of the slope difference between the first fitting straight line and the second fitting straight line is less than a preset slope threshold; respectively calculating the intersection point of the first fitting straight line and the fault line corresponding to each target contour line and the intersection point of the second fitting straight line and the fault line to obtain the first intersection point and the second intersection point corresponding to each target contour line; determining the distance between the first intersection point and the second intersection point corresponding to each target contour line as the initial horizontal displacement of each target contour line; and determining the initial horizontal displacement of all target contour lines as the initial horizontal dislocation data. The preset slope threshold can be set according to actual needs and is not limited here. For example, the preset slope threshold is 5.

[0078] Considering the horizontal position error caused by the terrain slope and the measurement angle, the initial horizontal displacement needs to be corrected. Optionally, the above-mentioned step of using the slope of the fault direction and the angle between the contour line and the fault line to correct the error caused by the vertical displacement of the initial horizontal displacement data to obtain the intermediate horizontal displacement data may include: for each target contour line in the initial horizontal displacement data, obtaining the vertical profile line of the target contour line at the fault line; determining the vertical displacement height of the target contour line and the angle between the target contour line and the fault line based on the vertical profile line and the RANSAC algorithm; calculating the position error corresponding to the target contour line based on the vertical displacement height of the target contour line, the angle between the target contour line and the fault line, and the slope of the target contour line at the fault line; using the position error difference corresponding to the target contour line to correct the initial horizontal displacement of the target contour line to obtain the intermediate horizontal displacement of the target contour line. The vertical section line of the target contour line at the fault line may be a vertical section line at the intersection of the target contour line and the fault line, or a vertical section line at the middle of the first intersection and the second intersection corresponding to the target contour line.

[0079] Further, the steps of determining the vertical dislocation height of the target contour line and the included angle between the target contour line and the fault line according to the vertical profile line and the RANSAC algorithm may include: extracting the elevation values on the vertical profile line from the DEM data to obtain a first elevation value sequence; respectively performing linear fitting on the hanging wall data and the footwall data in the first elevation value sequence by using the RANSAC algorithm to obtain a first hanging wall fitting line and a first footwall fitting line; determining the intercept difference between the first hanging wall fitting line and the first footwall fitting line at the fault line as the vertical dislocation height of the target contour line; and determining the average value of the included angle between the first hanging wall fitting line and the fault line and the included angle between the first footwall fitting line and the fault line as the included angle between the target contour line and the fault line.

[0080] Among them, the hanging wall data and the footwall data are determined in the following manner: by detecting the gradient change of the first elevation value sequence, determining the positions of the first abrupt change point and the second abrupt change point, and determining the hanging wall data and the footwall data in the first elevation value sequence according to the positions of the first abrupt change point and the second abrupt change point. There is one abrupt change point position x1, x2 on each side of the fault. x1, x2 divide the first elevation value sequence into three parts. The middle part is the fault scarp data, and the two parts of data except the middle part are the hanging wall data and the footwall data respectively. Specifically, the slope between adjacent two points in the first elevation value sequence can be calculated point by point, and the position of the sharp change in the slope along the profile (such as a sudden increase or decrease in the slope) is determined as the position of the abrupt change point, and the area between the sudden increase and the sudden decrease corresponds to the fault scarp. Once the positions of the abrupt change points x1, x2 are determined, the hanging wall data and the footwall data can be determined according to the fault occurrence. For example, the data in the area of x < x1 can be regarded as the hanging wall data, and the data in the area of x > x2 can be regarded as the footwall data.

[0081] Step S132, determining the initial vertical dislocation data of the target fault area according to the profile line data and the RANSAC algorithm.

[0082] Optionally, the above step S132 may include: extracting the elevation values on each profile line in the profile line data from the DEM data to obtain a second elevation value sequence; respectively performing linear fitting on the hanging wall data and the footwall data in the second elevation value sequence corresponding to each profile line by using the RANSAC algorithm to obtain a second hanging wall fitting line and a second footwall fitting line; determining the initial vertical displacement at the intersection of each profile line and the fault line according to the second hanging wall fitting line and the second footwall fitting line corresponding to each profile line; and determining the initial vertical displacement at the intersection of each profile line and the fault line as the initial vertical dislocation data.

[0083] Step S133, determining the horizontal dislocation distribution and the vertical dislocation distribution according to the intermediate horizontal dislocation data and the initial vertical dislocation data.

[0084] In a possible implementation, the intermediate horizontal dislocation data and the initial vertical dislocation data may be directly interpolated or smoothed to obtain a continuous horizontal dislocation distribution and a continuous vertical dislocation distribution along the fault line in the target fault region.

[0085] In another possible implementation, the intermediate horizontal dislocation data and the initial vertical dislocation data may be cleaned first to remove outliers, etc., and then interpolated or smoothed. Based on this, the above-mentioned step S133 may include: using the Monte Carlo method and the probability density function to remove outliers from the intermediate horizontal dislocation data and the initial vertical dislocation data to obtain target horizontal dislocation data and target vertical dislocation data; interpolating or smoothing the target horizontal dislocation data and the target vertical dislocation data to obtain a continuous horizontal dislocation distribution and vertical dislocation distribution along the fault line in the target fault area.

[0086] It should be noted that the data cleaning method is not limited to the above-mentioned Monte Carlo method and probability density function. In other embodiments, other data cleaning methods may also be used.

[0087] Furthermore, in order to facilitate user viewing, the horizontal dislocation distribution and the vertical dislocation distribution may be converted into a preset output format, which may include one or more of a chart, a data table, and a GIS (Geographic Information System) vector file.

[0088] The fault zone dislocation measurement method provided by an embodiment of the present invention can obtain DEM data of the target fault area; extract contour lines intersecting the fault line and generate vertical profile lines along the fault line from the DEM data to obtain contour line data and profile line data; use the RANSAC algorithm to calculate horizontal and vertical dislocations of the contour line data and profile line data, respectively, to obtain the horizontal and vertical dislocation distributions of the target fault area. In this way, by using the DEM data of the target fault area to generate contour line data and profile line data, and then combining the RANSAC algorithm, the horizontal and vertical dislocation distributions of the fault zone can be automatically measured. This method does not rely on obvious landform landmarks and can fully utilize high-resolution DEM data, so that the resolution of the dislocation measurement is consistent with the DEM data, thereby improving the applicability of complex terrain and the resolution of dislocation measurement.

[0089] For ease of understanding, the specific implementation process of the above-mentioned fault zone dislocation measurement method is introduced below.

[0090] The fault zone dislocation measurement method provided by the embodiment of the present invention mainly includes three parts: data acquisition, horizontal dislocation calculation and vertical dislocation calculation. Figure 2The data acquisition process diagram shown in the figure is as follows: the drone platform's camera uses SFM technology to take drone photos and GF7's front and back view image data to generate DEM data through image registration and 3D point cloud reconstruction; the drone platform's LiDAR point cloud data is filtered to generate DEM data. Figure 3 The figure shows a flow chart of horizontal displacement calculation. When calculating horizontal displacement, dense contour lines are first generated based on the DEM data obtained from data acquisition and the resolution of the DEM data. Then, contour fitting and initial displacement calculation are performed on the left and right sides of the confidence region. Finally, vertical position error difference is removed to obtain the true horizontal displacement. Figure 4 The figure shows a flow chart of vertical dislocation calculation. When calculating vertical dislocation, dense profile lines are first generated based on the DEM data obtained from data acquisition, and then the hanging wall and footwall of the fault are fitted. Finally, the vertical dislocation is calculated based on the fitting results.

[0091] The efficient fault zone dislocation measurement method based on dense contour lines developed in the embodiments of the present invention can more effectively analyze large amounts of data, realize the automated measurement of horizontal and vertical displacements of the fault zone, provide important data support and technical guarantees for earthquake activity analysis, fault stability assessment, etc., and help scientists deeply understand the mechanism of fault activity.

[0092] The fault zone dislocation measurement method provided by the present invention primarily includes the following steps: First, high-precision DEM data is acquired using drones or high-resolution satellite stereo images. After preprocessing, such as coordinate unification and fault vector repair, dense contour lines intersecting the fault line are extracted based on the DEM data, taking into account the DEM resolution. Subsequently, GIS software is used to generate minimum buffer zones (10-30 meters) and maximum buffer zones (200-300 meters) for the fault line, and a confidence region within the target fault region is determined. Next, in the horizontal dislocation calculation phase, the RANSAC algorithm is used to independently perform linear fits on the left and right sides of each contour line to calculate a preliminary horizontal displacement. The horizontal error caused by vertical displacement is corrected based on the slope of the fault strike and the angle between the fault line and the contour line to obtain the true horizontal displacement. In the vertical dislocation measurement phase, dense profile lines are generated along the fault direction. DEM data on the profile lines is extracted, and the hanging wall and footwall are fitted using the RANSAC algorithm to calculate the vertical displacement. Finally, the Monte Carlo method and probability density function (PDF) are used to remove errors and optimize data for all horizontal and vertical displacement data.

[0093] Specifically, the above-mentioned fault zone dislocation measurement method includes the following steps:

[0094] Step one: data collection and processing.

[0095] 1.1 Data source acquisition: High-resolution DEM data obtained by drone photogrammetry or DEM data constructed from high-resolution satellite stereo images should be used. The spatial resolution of the DEM data should meet the accuracy requirements for fault identification and dislocation measurement (for example, the spatial resolution should be better than 1 m).

[0096] 1.2 Fault data: Fault lines are drawn based on the interpretation of the acquired high-precision DEM data.

[0097] 1.3 Coordinate system 1: DEM data and fault lines are guaranteed to be in the same projection coordinate system.

[0098] Step 2: Dense contour lines and confidence regions are drawn.

[0099] 2.1 Contour extraction: The elevation values ​​along the fault are obtained based on the DEM resolution, and the contour lines intersecting the fault line are generated within the target fault area based on the elevation values.

[0100] 2.2 Determination of Confidence Region: With the known fault trace as input, use it as the centerline and define the minimum and maximum buffer distances based on geological interpretation and engineering experience. For example:

[0101] Minimum buffer radius: 10-30 m;

[0102] Maximum buffer radius: 200-300 m.

[0103] The fault line was buffered using the GIS buffer analysis tool, and the following results were obtained:

[0104] Internal buffer (minimum buffer): Buffer_min;

[0105] External buffer (maximum buffer): Buffer_max.

[0106] The final confidence region is determined as the annular area between Buffer_max and Buffer_min to ensure that the contour lines are only analyzed within a limited range near the fault.

[0107] Step 3: Calculation of horizontal dislocation.

[0108] The goal of this step is to calculate the horizontal offset of the fault from the contour offset characteristics. The core idea is to use the fault line to divide the contour line into two sides and measure the relative horizontal offset of the contour lines on both sides at the fault by linearly fitting the contour line segments.

[0109] 3.1 Contour line fitting processing.

[0110] 3.1.1 Determination of intersection between contour lines and faults: For each contour line C i , determine whether it intersects the fault line and whether it is at least partially within the confidence region. If the contour line does not intersect the fault line or the contour line is not within the confidence region, the contour line is removed.

[0111] 3.1.2 Contour line left and right side splitting and RANSAC fitting: Contour lines that have been confirmed to intersect with fault lines are separated into left parts according to the fault lines. C iL With the right part C iR , use the RANSAC algorithm to C iL and C iR Perform a linear fit on the data within the confidence region and obtain:

[0112] (Linear fit on the left);

[0113] (Linear fit on the right);

[0114] in, a L 、 b L and a R 、 b R are the slope and intercept of the fitted line on the left, and the slope and intercept of the fitted line on the right, respectively.

[0115] 3.1.3 Slope Difference Test: Check the slope difference between the left and right fitting lines Is it within the allowable range (this range can be set based on terrain characteristics or experience, such as less than a certain threshold of 5). If the slope difference is too large, it means that the contour line is too inconsistent on the left and right sides and is not suitable for dislocation measurement and can be eliminated.

[0116] 3.1.4 Preliminary calculation of intersection points and horizontal dislocation: Extend the left and right fitting lines in the direction of the fault line. Calculate the intersection points of the left and right fitting lines with the fault line respectively:

[0117] If the fault line equation is , find the intersection point with the left fitting line The solution process is as follows:

[0118] .

[0119] Similarly, the right intersection for:

[0120] .

[0121] Calculate the distance between the intersection points as the initial horizontal displacement of the contour line:

[0122] .

[0123] The initial horizontal displacement value and contour index information are retained for subsequent correction.

[0124] like Figure 5 As shown ( Figure 5 The 6 in the figure refers to the fault line number). The two black lines are the fitted lines of a certain contour line on the left and right sides of the fault line 6. The extension lines of the two fitted lines ( Figure 5 The distance between the two intersection points of the contour line (the dotted line in the figure) and the fault line 6 is the initial horizontal displacement of the contour line. l initial .

[0125] 3.2 Vertical bit error correction.

[0126] Considering the horizontal position error caused by terrain slope and measurement angle, the initial horizontal displacement needs to be corrected.

[0127] 3.2.1 Midpoint profile line extraction: near the midpoint of the fault intersection (i.e. P L 、 P R midpoint P M ) Construct a vertical profile line along the direction perpendicular to the fault. The length and resolution are determined by the data accuracy and fault characteristics. The length of the vertical profile line is pre-set, and the resolution is the resolution of the DEM data.

[0128] 3.2.2 DEM Extraction and Vertical Displacement Calculation of the Profile Line: Elevation values ​​are extracted from the DEM data along the profile line. The profile line can theoretically be divided into three sections: the hanging wall, the fault scarp, and the footwall. RANSAC is used to perform a linear fit between the hanging wall and footwall data of the profile line:

[0129] (hanging plate fitting);

[0130] (footplate fitting);

[0131] If the slope difference between the upper and lower plates (i.e. ) is within the allowable range, the intercept difference between the upper and lower wall fitting lines at the fault position can be calculated, that is, the vertical dislocation height:

[0132] .

[0133] 3.2.3 Calculation of the angle between the fault line and the contour line: The fault line is approximately regarded as a reference straight line, and the direction of the fault line can be determined by the slope. a f Indicate (or use azimuth θ f The angle between the contour fitting line and the fault line can be calculated by the slope relationship. When the slopes of the two straight lines are known to be m 1 and m 2. Its angle θ satisfy:

[0134] ;

[0135] in, , .

[0136] Calculate the angles between the fitted contour lines and the fault line on the left and right sides respectively, and calculate the average angle for subsequent calculations.

[0137] 3.2.4 Slope and deviation correction calculation: Based on the slope of the DEM data at the midpoint ( slope ) and the angle between the contour line and the fault line ( angle ), calculate the error term in the horizontal displacement l wrong It is known that slope is the surface inclination, that is, the inclination of the terrain surface relative to the horizontal plane (which can be obtained by taking the first-order derivative of the DEM data). angle It is the average value of the angles between the fitting lines on both sides and the fault line (i.e., the average angle).

[0138] like Figure 6 As shown, according to the terrain geometry l wrong , assuming that the error term is equal to the vertical displacement h And the two angles are related, the error formula is given:

[0139] ;

[0140] in, h is the vertical dislocation height; slope is the slope (i.e. Figure 6 The inclination angle θ ), degrees need to be converted to radians for calculation; angle (Right now Figure 6 in α) is the average angle between the contour fitting line and the fault line (also needs to be in radians).

[0141] In the formula sin( slope ) and sin( angle ) is explained as follows:

[0142] When the slope is small, h / sin( slope ) is equivalent to the proportional correction of the projection component mapped from the true vertical displacement to the horizontal direction. sin( angle ) further considers the influence of the angle between the survey line and the fault strike.

[0143] 3.2.5 Final horizontal displacement correction:

[0144] The final true horizontal displacement formula is as follows:

[0145] .

[0146] The corrected horizontal displacement is taken as the horizontal dislocation at the contour line.

[0147] Step 4: Calculation of vertical dislocation.

[0148] Similar to horizontal dislocations, the calculation of vertical dislocations is based on dense vertical profiles arranged along the fault direction.

[0149] 4.1 Dense cross-hatching generation: Figure 7 As shown in the figure, a section line is generated perpendicular to the fault line at regular intervals (e.g., 5 to 10 m) along the fault strike.

[0150] 4.2 DEM data extraction and RANSAC fitting: DEM data is extracted for each profile line, and RANSAC is used to fit the hanging wall and footwall data to obtain:

[0151] (hanging plate fitting);

[0152] (footplate fitting);

[0153] Check the slope difference ( ) is appropriate.

[0154] 4.3 Calculation of vertical displacement: Figure 8 As shown in Figure 2, the vertical displacement is calculated based on the intercept difference between the upper and lower wall fitting lines at the fault position:

[0155] .

[0156] Record the position of the intersection of the section line and the fault line and the corresponding vertical displacement value.

[0157] Step 5: Error reduction and statistical analysis.

[0158] 5.1 Monte Carlo Method and Probability Density Function (PDF) Analysis: Multiple sampling and statistical analysis of all horizontal and vertical dislocation data were performed. Monte Carlo simulations were used to repeatedly sample measurement points and calculate the statistical characteristics of the dislocation distribution (mean, standard deviation). The PDF (Probability Density Function) model was used to fit the distribution characteristics of the dislocation values, detect outliers, and eliminate points with large errors or those that do not conform to the statistical distribution characteristics.

[0159] Specifically, a probability distribution can be defined for the dislocation of each measurement point based on a known or assumed probability distribution. For each measurement point, a large number of random samples are drawn from the probability distribution of its dislocation value. This is equivalent to performing multiple virtual measurements on each measurement point. The mean and standard deviation of each sample set are calculated to obtain a series of mean and standard deviation results. The mean and standard deviation of all simulation results are calculated to estimate the true mean and standard deviation of the dislocation distribution. Use the maximum likelihood estimation method or other suitable methods to fit a suitable PDF model based on the frequency distribution of dislocation values ​​obtained by Monte Carlo simulation. Based on the fitted PDF model, a reasonable threshold is set to define outliers. Values ​​that are several standard deviations away from the mean can be selected as the standard for outliers. Compare the dislocation values ​​in the original data with the threshold, mark those points that exceed the threshold as outliers, and remove the outliers.

[0160] 5.2 Final Result Output: Interpolate or smooth the cleaned dislocation data to obtain continuous horizontal and vertical dislocation distributions along the fault line. Output the results in the form of graphs (e.g., dislocation distribution curves along the fault), data tables (e.g., CSV format), and GIS vector files (e.g., .shp format), providing a reference for earthquake fault activity analysis and surface deformation measurement.

[0161] In summary, the innovations of the embodiments of the present invention mainly include:

[0162] 1. Cross-fault contour measurement, independent of obvious geomorphic landmarks: This method utilizes abundant cross-fault contour data. Even if there are no obvious geomorphic landmarks near the fault, it can identify and measure fault displacement through geometric changes in dense contour lines.

[0163] 2. Fully exploit the value of high-precision DEM: Under conditions of high terrain accuracy, maximize the potential of DEM data and achieve automated, high-resolution detection of fault zone dislocations through intensive contour and profile analysis;

[0164] 3. Vertical misalignment correction: Based on the traditional method that only focuses on horizontal misalignment, this method further considers the interference and error caused by vertical misalignment on horizontal displacement, and corrects it through geometric and trigonometric relationships, greatly improving the accuracy and reliability of misalignment measurement.

[0165] The above-mentioned fault zone dislocation measurement method has broad application prospects in geological fault research and crustal deformation analysis, and can provide important data support and technical guarantees for earthquake activity analysis, fault stability assessment, etc.

[0166] Corresponding to the above-mentioned fault zone dislocation measurement method, an embodiment of the present invention further provides a fault zone dislocation measurement device. Figure 9 The schematic diagram of the structure of a fault zone dislocation measurement device is shown, and the device includes:

[0167] Acquisition module 901, used to acquire DEM data of target fault area;

[0168] A generation module 902 is used to extract contour lines intersecting the fault line and generate vertical profile lines along the fault line from the DEM data to obtain contour line data and profile line data;

[0169] The calculation module 903 is used to calculate the horizontal dislocation and vertical dislocation of the contour data and the profile data using the RANSAC algorithm, and obtain the horizontal dislocation distribution and vertical dislocation distribution of the target fault area.

[0170] The fault zone dislocation measurement device provided in an embodiment of the present invention can obtain DEM data of a target fault area; extract contour lines intersecting the fault line and generate vertical profile lines along the fault line from the DEM data to obtain contour line data and profile line data; and use the RANSAC algorithm to calculate horizontal and vertical dislocations of the contour line data and profile line data, respectively, to obtain the horizontal and vertical dislocation distributions of the target fault area. In this way, by using the DEM data of the target fault area to generate contour line data and profile line data, and then combining it with the RANSAC algorithm, automated measurement of the horizontal and vertical dislocation distributions of the fault zone is achieved. This method does not rely on obvious landform landmarks and can fully utilize high-resolution DEM data, so that the resolution of the dislocation measurement is consistent with the DEM data, thereby improving the applicability of complex terrain and the resolution of dislocation measurement.

[0171] Furthermore, the generating module 902 is specifically configured to:

[0172] Extract the elevation value on the fault line from the DEM data to obtain the target elevation value, and based on the target elevation value, extract the contour data from the DEM data;

[0173] Generate vertical profile lines along the fault lines for the DEM data to obtain profile line data.

[0174] Furthermore, the calculation module 903 is specifically configured to:

[0175] Based on the contour data and the RANSAC algorithm, the initial horizontal displacement data of the target fault area is determined. The slope of the fault strike and the angle between the contour line and the fault line are used to correct the error caused by the vertical displacement of the initial horizontal displacement data to obtain the intermediate horizontal displacement data.

[0176] Determine the initial vertical displacement data of the target fault area based on the profile data and the RANSAC algorithm;

[0177] The horizontal dislocation distribution and the vertical dislocation distribution are determined based on the intermediate horizontal dislocation data and the initial vertical dislocation data.

[0178] Furthermore, the calculation module 903 is further configured to:

[0179] Determine the confidence region of the target fault area based on the minimum buffer and maximum buffer corresponding to the fault line in the DEM data;

[0180] Filtering the contour line data according to preset filtering conditions to obtain candidate contour line data; wherein the preset filtering conditions include intersecting with the fault line and being at least partially located within the confidence region;

[0181] The RANSAC algorithm is used to perform linear fitting within the confidence region on the first part and the second part of each candidate contour line separated by the fault line in the candidate contour line data, and the first fitting straight line and the second fitting straight line corresponding to each candidate contour line are obtained;

[0182] The horizontal displacement is calculated based on the first fitting straight line and the second fitting straight line corresponding to each candidate contour line to obtain initial horizontal dislocation data.

[0183] Furthermore, the calculation module 903 is further configured to:

[0184] Performing a slope difference test on the first fitted straight line and the second fitted straight line corresponding to each candidate contour line to obtain a target contour line that meets a preset slope difference condition; wherein the preset slope difference condition includes that the absolute value of the slope difference between the first fitted straight line and the second fitted straight line is less than a preset slope threshold;

[0185] Calculate the intersection points of the first fitting straight line and the fault line and the intersection points of the second fitting straight line and the fault line corresponding to each target contour line respectively, and obtain the first intersection point and the second intersection point corresponding to each target contour line;

[0186] The distance between the first intersection point and the second intersection point corresponding to each target contour line is determined as the initial horizontal displacement of each target contour line;

[0187] The initial horizontal displacements of all target contour lines are determined as initial horizontal dislocation data.

[0188] Furthermore, the calculation module 903 is further configured to:

[0189] For each target contour line in the initial horizontal dislocation data, a vertical profile line of the target contour line at the fault line is obtained;

[0190] According to the vertical profile line and RANSAC algorithm, the vertical displacement height of the target contour line and the angle between the target contour line and the fault line are determined;

[0191] The error difference corresponding to the target contour line is calculated based on the vertical dislocation height of the target contour line, the angle between the target contour line and the fault line, and the slope of the target contour line at the fault line;

[0192] The initial horizontal displacement of the target contour line is corrected using the bit error difference corresponding to the target contour line to obtain the intermediate horizontal displacement of the target contour line.

[0193] Furthermore, the calculation module 903 is further configured to:

[0194] Extract the elevation values ​​on the vertical section line from the DEM data to obtain the first elevation value sequence;

[0195] The RANSAC algorithm is used to perform linear fitting on the hanging wall data and the footwall data in the first elevation value sequence to obtain the first hanging wall fitting line and the first footwall fitting line;

[0196] The intercept difference between the first hanging wall fitting straight line and the first footwall fitting straight line at the fault line is determined as the vertical dislocation height of the target contour line;

[0197] The average of the angles between the first hanging wall fitting straight line and the fault line and the angles between the first footwall fitting straight line and the fault line is determined as the angle between the target contour line and the fault line.

[0198] Furthermore, the calculation module 903 is further configured to:

[0199] Using the Monte Carlo method and probability density function, the intermediate horizontal dislocation data and the initial vertical dislocation data are eliminated for outliers to obtain the target horizontal dislocation data and the target vertical dislocation data;

[0200] The target horizontal dislocation data and the target vertical dislocation data are interpolated or smoothed to obtain a continuous horizontal dislocation distribution and a continuous vertical dislocation distribution along the fault line in the target fault area.

[0201] The fault zone dislocation measurement device provided in this embodiment has the same implementation principle and technical effects as those of the aforementioned fault zone dislocation measurement method embodiment. For the sake of brief description, for matters not mentioned in the embodiment of the fault zone dislocation measurement device, reference may be made to the corresponding contents in the aforementioned fault zone dislocation measurement method embodiment.

[0202] like Figure 10 As shown, an embodiment of the present invention provides an electronic device 1000, including: a processor 1001, a memory 1002 and a bus, the memory 1002 stores a computer program that can be run on the processor 1001, when the electronic device 1000 is running, the processor 1001 and the memory 1002 communicate through the bus, and the processor 1001 executes the computer program to implement the above-mentioned fault zone dislocation measurement method.

[0203] Specifically, the memory 1002 and processor 1001 can be general-purpose memories and processors, which are not specifically limited here.

[0204] An embodiment of the present invention further provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program executes the fault zone dislocation measurement method described in the preceding method embodiment. The computer-readable storage medium includes various media capable of storing program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), RAM, a magnetic disk, or an optical disk.

[0205] The term "and / or" herein simply describes an association relationship between associated objects, indicating that three relationships can exist. For example, "A and / or B" can represent the existence of three situations: A alone, A and B simultaneously, and B alone. Furthermore, the term "at least one" herein refers to any combination of at least two of any one or more of a plurality of items. For example, "at least one of A, B, and C" can represent any one or more elements selected from the set consisting of A, B, and C.

[0206] In all examples shown and described herein, any specific values ​​should be interpreted as merely exemplary and not limiting, and thus other examples of the exemplary embodiments may have different values.

[0207] The flowcharts and block diagrams in the accompanying drawings show the possible architectures, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, program segment or part of the code, and the module, program segment or part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0208] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of modules is only a logical function division. There may be other division methods in actual implementation. For example, multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interface, the indirect coupling or communication connection of the device or module can be electrical, mechanical or other forms.

[0209] Modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed across multiple network modules. Some or all of these modules may be selected to achieve the purpose of this embodiment based on actual needs.

[0210] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0211] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for measuring fault zone dislocation, characterized in that: include: Obtain DEM data of the target fault area; Extracting contour lines intersecting the fault line and generating vertical profile lines along the fault line from the DEM data to obtain contour line data and profile line data; Utilizing the RANSAC algorithm, the horizontal dislocation and the vertical dislocation of the contour line data and the profile line data are calculated respectively to obtain the horizontal dislocation distribution and the vertical dislocation distribution of the target fault area; The method of using the RANSAC algorithm to calculate the horizontal dislocation and the vertical dislocation of the contour line data and the profile line data respectively to obtain the horizontal dislocation distribution and the vertical dislocation distribution of the target fault area includes: Determine initial horizontal dislocation data of the target fault region based on the contour data and the RANSAC algorithm, and correct the error caused by vertical displacement of the initial horizontal dislocation data using the slope of the fault strike and the angle between the contour line and the fault line to obtain intermediate horizontal dislocation data; Determining initial vertical dislocation data of the target fault region based on the profile data and the RANSAC algorithm; The horizontal dislocation distribution and the vertical dislocation distribution are determined based on the intermediate horizontal dislocation data and the initial vertical dislocation data.

2. The method according to claim 1, characterized in that The extracting of contour lines intersecting the fault line and generating vertical profile lines along the fault line from the DEM data to obtain contour line data and profile line data includes: Extracting the elevation value on the fault line from the DEM data to obtain a target elevation value, and extracting the contour line data from the DEM data based on the target elevation value; A vertical profile line along the fault line is generated for the DEM data to obtain the profile line data.

3. The method according to claim 1, characterized in that Determining the initial horizontal dislocation data of the target fault area according to the contour data and the RANSAC algorithm includes: Determining a confidence region of the target fault region based on a minimum buffer zone and a maximum buffer zone corresponding to the fault line in the DEM data; Filtering the contour line data according to preset filtering conditions to obtain candidate contour line data; wherein the preset filtering conditions include intersecting with the fault line and being at least partially located within the confidence region; Using the RANSAC algorithm, a first part and a second part of each candidate contour line separated by a fault line in the candidate contour line data are linearly fitted within a confidence region to obtain a first fitting straight line and a second fitting straight line corresponding to each candidate contour line; The horizontal displacement is calculated based on the first fitting straight line and the second fitting straight line corresponding to each candidate contour line to obtain the initial horizontal dislocation data.

4. The method according to claim 3, characterized in that The calculating of the horizontal displacement according to the first fitting straight line and the second fitting straight line corresponding to each candidate contour line to obtain the initial horizontal dislocation data includes: Performing a slope difference test on the first fitting straight line and the second fitting straight line corresponding to each candidate contour line to obtain a target contour line that meets a preset slope difference condition; wherein the preset slope difference condition includes that the absolute value of the slope difference between the first fitting straight line and the second fitting straight line is less than a preset slope threshold; Calculating the intersection points of the first fitting straight line and the fault line and the intersection points of the second fitting straight line and the fault line corresponding to each target contour line respectively, to obtain the first intersection point and the second intersection point corresponding to each target contour line; Determine the distance between the first intersection point and the second intersection point corresponding to each target contour line as the initial horizontal displacement of each target contour line; The initial horizontal displacements of all the target contour lines are determined as the initial horizontal dislocation data.

5. The method according to claim 1, wherein The method of correcting the error caused by vertical displacement of the initial horizontal dislocation data by using the slope of the fault direction and the angle between the contour line and the fault line to obtain the intermediate horizontal dislocation data includes: For each target contour line in the initial horizontal dislocation data, obtaining a vertical profile line of the target contour line at the fault line; Determining the vertical dislocation height of the target contour line and the angle between the target contour line and the fault line according to the vertical profile line and the RANSAC algorithm; Calculating the position error difference corresponding to the target contour line according to the vertical dislocation height of the target contour line, the angle between the target contour line and the fault line, and the slope of the target contour line at the fault line; The initial horizontal displacement of the target contour line is corrected using the bit error difference corresponding to the target contour line to obtain an intermediate horizontal displacement of the target contour line.

6. The method according to claim 5, characterized in that Determining the vertical dislocation height of the target contour line and the angle between the target contour line and the fault line according to the vertical profile line and the RANSAC algorithm includes: Extracting elevation values ​​on the vertical profile line from the DEM data to obtain a first elevation value sequence; Using the RANSAC algorithm to perform linear fitting on the hanging wall data and the footwall data in the first elevation value sequence, respectively, to obtain a first hanging wall fitting straight line and a first footwall fitting straight line; Determine the vertical dislocation height of the target contour line as the difference between the intercepts of the first hanging wall fitting straight line and the first footwall fitting straight line at the fault line; The average of the angles between the first hanging wall fitting straight line and the fault line and the angles between the first footwall fitting straight line and the fault line is determined as the angle between the target contour line and the fault line.

7. The method according to claim 1, characterized in that The determining the horizontal dislocation distribution and the vertical dislocation distribution according to the intermediate horizontal dislocation data and the initial vertical dislocation data comprises: Using the Monte Carlo method and the probability density function, outliers are eliminated from the intermediate horizontal dislocation data and the initial vertical dislocation data to obtain target horizontal dislocation data and target vertical dislocation data; The target horizontal dislocation data and the target vertical dislocation data are interpolated or smoothed to obtain the horizontal dislocation distribution and the vertical dislocation distribution that are continuous along the fault line in the target fault region.

8. A fault zone dislocation measurement device, characterized in that: include: Acquisition module, used to obtain DEM data of target fault area; A generation module is used to extract contour lines intersecting the fault line and generate vertical profile lines along the fault line from the DEM data to obtain contour line data and profile line data; a calculation module, configured to calculate horizontal dislocation and vertical dislocation of the contour line data and the profile line data respectively using a RANSAC algorithm, to obtain horizontal dislocation distribution and vertical dislocation distribution of the target fault area; The calculation module is specifically used to: determine the initial horizontal dislocation data of the target fault area based on the contour line data and the RANSAC algorithm, and use the slope of the fault direction and the angle between the contour line and the fault line to correct the error caused by the vertical displacement of the initial horizontal dislocation data to obtain intermediate horizontal dislocation data; determine the initial vertical dislocation data of the target fault area based on the profile line data and the RANSAC algorithm; and determine the horizontal dislocation distribution and the vertical dislocation distribution based on the intermediate horizontal dislocation data and the initial vertical dislocation data.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, wherein: When the processor executes the computer program, the fault zone dislocation measurement method according to any one of claims 1 to 7 is implemented.

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