A coal mining boundary updating and out-of-boundary early warning method based on time-series InSAR deformation

Abstract

The present application relates to the technical field of mining area monitoring, and discloses a coal mining boundary updating and out-of-bound early warning method based on time-series InSAR deformation, which comprises the following steps: performing deformation inversion and space-time feature analysis on time-series synthetic aperture radar image data of a target mining area to obtain a cumulative deformation area and a deformation rate gradient zone; performing spatial correlation verification on the cumulative deformation area and the deformation rate gradient zone and mining activity polygons of the target mining area to obtain a feature interlocking result; performing contour evolution on the initial mining boundary of the target mining area based on a mining disturbance front identified based on the feature interlocking result to obtain an updated mining boundary; performing risk front demarcation on the updated mining boundary according to the deformation rate gradient zone to obtain a risk progressive area, and performing situation quantification indexing on the risk progressive area to obtain a risk situation label; and deriving an early warning instruction from the risk situation label to obtain an early warning instruction; the present application can improve the efficiency of coal mining boundary updating and out-of-bound early warning.

Description

Technical Field

[0001] This invention relates to the field of mining area monitoring technology, and in particular to a method for updating coal mining boundaries and providing early warning of boundary crossings based on temporal InSAR deformation. Background Technology

[0002] Traditional coal mine boundary updates rely heavily on manual surveys or conventional monitoring methods. These methods are not only cumbersome and time-consuming, but also have limited coverage and make it difficult to capture subtle topographical deformations and dynamic boundary changes caused by mining activities in real time. This results in discrepancies between the updated mining boundaries and the actual mining area, failing to provide accurate data for supervision.

[0003] Existing boundary crossing early warning methods often rely on fixed threshold judgments or single monitoring indicator analysis, lacking in-depth analysis and comprehensive consideration of the spatiotemporal characteristics of deformation. The targeting and accuracy of risk identification are insufficient, and false alarms and missed alarms are prone to occur. It is difficult to predict the risks of cross-border mining in advance and issue effective early warnings in a timely manner, which poses a potential threat to the safe production and ecological protection of mining areas. Therefore, how to improve the efficiency of coal mine mining boundary updates and boundary crossing early warning has become an urgent problem to be solved. Summary of the Invention

[0004] This invention provides a method for updating coal mine mining boundaries and providing early warning of boundary crossings based on temporal InSAR deformation, in order to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, this invention provides a method for updating coal mine mining boundaries and providing early warning of boundary violations based on temporal InSAR deformation, comprising: S1. Perform deformation inversion on the time-series synthetic aperture radar image data of the target mining area to obtain the time-series deformation data of the target mining area; S2. Perform spatiotemporal feature analysis on the time-series deformation dataset to obtain the cumulative deformation zone and deformation rate gradient zone of the target mining area; S3. Spatial correlation verification is performed between the cumulative deformation zone and the deformation rate gradient zone and the mining activity patches of the target mining area to obtain the characteristic interlocking results of the target mining area. S4. Based on the mining disturbance front identified by the feature interlocking results, the initial mining boundary of the target mining area is profiled and evolved to obtain the updated mining boundary of the target mining area. S5. Based on the deformation rate gradient zone, the risk frontier of the updated mining boundary is delineated to obtain the risk progression zone of the target mining area, and the risk progression zone is quantitatively indexed to obtain the risk status label of the target mining area. S6. Derivation of alarm instructions from risk status labels to obtain early warning instructions for the target mining area.

[0006] In a preferred embodiment, the deformation inversion of the temporal synthetic aperture radar image data of the target mining area to obtain the temporal deformation data of the target mining area includes: Acquire temporal synthetic aperture radar (SAR) image data of the target mining area and perform geometric fine correction on the temporal SAR image data to obtain a standardized temporal image of the target mining area. Terrain phase removal is performed on standardized time-series images to obtain differential interferograms of the target mining area; Nonlinear deformation separation is performed on the differential interferogram to obtain the deformation phase information of the target mining area; The deformation phase information is converted by wavelength ratio to obtain the time-series deformation data of the target mining area.

[0007] In a preferred embodiment, the step of performing spatiotemporal feature analysis on the time-series deformation dataset to obtain the cumulative deformation zone and deformation rate gradient band of the target mining area includes: In the time domain, trend component decomposition is performed on the time-series deformation data to construct the cumulative deformation trend field of the target mining area; Based on the preset deformation influence judgment rules, the cumulative deformation trend field is spatially filtered to obtain the significant deformation area of ​​the target mining area; Spatial connectivity analysis was performed on the areas of significant deformation to obtain the cumulative deformation area of ​​the target mining area. In the spatial dimension, anisotropy detection is performed on the temporal deformation data to construct the spatial variation intensity field of the target mining area; Boundary identification is performed on the spatially varying intensity field to obtain the transition zone of the spatially varying intensity field, and the continuous spatial contour of the transition zone is extracted to generate the initial gradient zone of the target mining area. The spatial relationship between the initial gradient zone and the cumulative deformation zone is verified to obtain the deformation rate gradient zone of the target mining area.

[0008] In a preferred embodiment, the step of spatially correlating the cumulative deformation zone and deformation rate gradient band with the mining activity patches of the target mining area to obtain the feature interlocking results of the target mining area includes: Under a unified geospatial reference framework, the cumulative deformation zone, deformation rate gradient zone and mining activity patches of the target mining area are overlaid to obtain a spatial composite layer of the target mining area. Based on the spatial composite layer and cumulative deformation zone, the spatial coverage of the core area in the mining activity patch is determined to determine the spatial ownership, and a spatial coverage analysis report of the target mining area is obtained. Based on the spatial composite layer, the adjacency relationship between the spatial topological relationship between the deformation rate gradient zone and the boundary of the mining activity patch is identified, and the topological relationship identification conclusion of the target mining area is obtained. By logically integrating the spatial coverage analysis report and the topological relationship identification conclusions, a preliminary interlocking determination result for the target mining area is obtained. Based on the geological background data of the target mining area, spatial consistency analysis was conducted on the preliminary interlocking determination to obtain the characteristic interlocking results of the target mining area.

[0009] In a preferred embodiment, the step of logically synthesizing the spatial coverage analysis report and the topological relationship identification conclusion to obtain the preliminary interlocking determination result of the target mining area includes: The comprehensive correlation index of the target mining area is obtained by weighting and comprehensively evaluating the core area coverage rate index in the spatial coverage analysis report and the adjacency strength index in the topological relationship identification conclusion. Based on the spatial composite layer, the spatial relationship between the deformation center point of the cumulative deformation zone and the geometric center of the mining activity patch is vectorized to obtain the offset vector of the target mining area. By integrating the comprehensive correlation index with the spatial consistency of the offset vector, a preliminary interlocking determination result for the target mining area is obtained.

[0010] In a preferred embodiment, the step of performing contour evolution on the initial mining boundary of the target mining area based on the mining disturbance front identified by the feature interlocking results to obtain the updated mining boundary of the target mining area includes: Extract spatial geometric information of the mining disturbance leading edge from the feature interlocking results; By spatially overlaying spatial geometric information with the initial mining boundary, the section to be expanded in the target mining area is obtained; Using spatial geometric information as the evolution benchmark, spatial extrapolation is performed on the section to be expanded to obtain the evolved boundary segment of the target mining area; After the evolution of the boundary segment, gaps are filled to obtain the transition boundary of the target mining area. The unchanged portions of the transition boundary and the initial mining boundary are topologically reconstructed to obtain the updated mining boundary of the target mining area.

[0011] In a preferred embodiment, the step of performing spatial overlay analysis between spatial geometric information and the initial mining boundary to obtain the target mining area to be expanded includes: Based on spatial geometric information, determine the boundary evolution analysis range of the target mining area; Within the scope of boundary evolution analysis, the initial mining boundary is topologically superimposed based on spatial geometric information to obtain the original area to be expanded in the target mining area; The original area to be expanded is broken up and the purified section of the target mining area is obtained by removing the broken sections. The purified sections will be integrated into the expansion sections of the target mining area.

[0012] In a preferred embodiment, the step of delineating the risk frontier of the updated mining boundary based on the deformation rate gradient zone to obtain the risk progression zone of the target mining area includes: By extracting the adjacent area between the deformation rate gradient zone and the updated mining boundary, the candidate front zone of the target mining area is obtained. Using the centerline of the candidate front zone as the baseline, the outer direction of the updated mining boundary is geometrically extended to obtain the initial risk front zone of the target mining area; By determining the boundary contact between the initial risk front zone and the cumulative deformation zone, the risk connectivity zone of the target mining area is obtained. By merging the risk connectivity zone with the updated mining boundary, a risk progression zone for the target mining area is obtained.

[0013] In a preferred embodiment, the step of performing situational quantification indexing on the risk progression zone to obtain a risk situation label for the target mining area includes: Extract statistical characteristics of deformation rate within the risk progression zone; By normalizing and aggregating the statistical characteristics of deformation rate, the risk progression zone and the average distance of the updated mining boundary, a comprehensive risk quantification index for the target mining area is obtained. Based on a predefined industry standard risk classification framework, the comprehensive risk quantification index is mapped to the risk status label of the target mining area.

[0014] In a preferred embodiment, the step of deriving an alarm instruction from the risk status label to obtain an early warning instruction for the target mining area includes: By deconstructing the risk status label, we can obtain the risk level and risk spatial range information of the risk status label. Based on a preset risk alert mapping table, risk levels are matched and retrieved to obtain the standard alert level for the target mining area; By recombining the standard alarm level with the risk spatial range information, an early warning instruction for the target mining area is obtained.

[0015] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention performs deformation inversion on time-series synthetic aperture radar (SAR) image data of the target mining area, combines spatiotemporal feature analysis to obtain the cumulative deformation zone and deformation rate gradient band, and accurately identifies the mining disturbance front through spatial correlation verification, thereby completing the contour evolution of the initial mining boundary. This process enables dynamic updating of the mining boundary, significantly improving the consistency between boundary information and the actual mining area, providing reliable basic data for mining area supervision, while simplifying the update process and improving the timeliness and accuracy of boundary updates.

[0016] 2. This invention delineates risk progression zones through deformation rate gradient bands, quantifies and indexes risks based on multi-dimensional deformation rate statistical characteristics and spatial distance parameters, generates precise risk status labels, and derives early warning instructions. This quantitative analysis and targeted calibration method makes risk identification more scientific, and the early warning instructions more closely match actual risk scenarios. It can promptly capture potential boundary-crossing risks, build a solid defense for safe production and ecological protection in mining areas, and significantly improve the pertinence and effectiveness of risk prevention and control. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating a method for updating and warning of coal mine mining boundaries based on temporal InSAR deformation, provided as an embodiment of the present invention.

[0018] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0019] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0020] This application provides a method for updating and warning of coal mine mining boundaries based on temporal InSAR deformation. The executing entity of this method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the method for updating and warning of coal mine mining boundaries based on temporal InSAR deformation can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster. The server can be an independent server or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0021] Reference Figure 1 The diagram shown is a flowchart illustrating a method for updating and issuing early warnings of coal mine mining boundaries based on temporal InSAR deformation, according to an embodiment of the present invention. In this embodiment, the method includes: S1. Perform deformation inversion on the time-series synthetic aperture radar image data of the target mining area to obtain the time-series deformation data of the target mining area; In this embodiment of the invention, the deformation inversion of the temporal synthetic aperture radar image data of the target mining area to obtain the temporal deformation data of the target mining area includes: Acquire temporal synthetic aperture radar (SAR) image data of the target mining area and perform geometric fine correction on the temporal SAR image data to obtain a standardized temporal image of the target mining area. Terrain phase removal is performed on standardized time-series images to obtain differential interferograms of the target mining area; Nonlinear deformation separation is performed on the differential interferogram to obtain the deformation phase information of the target mining area; The deformation phase information is converted by wavelength ratio to obtain the time-series deformation data of the target mining area.

[0022] Acquire time-series synthetic aperture radar (SAR) imagery data of the target mining area for at least six consecutive months. The spatial coverage of the images must completely cover an area extending 5 kilometers beyond the boundary of the target mining area, and the time interval between images must not exceed 15 days to ensure data continuity and integrity. Using a high-precision geographic coordinate dataset of the target mining area certified by an authoritative department as a benchmark, this dataset contains at least 100 evenly distributed ground control points with a coordinate error not exceeding 0.5 meters. By identifying prominent ground feature points such as road intersections and building corners corresponding to the ground control points on the images, a correspondence between image pixels and ground control point coordinates is established. The spatial position, scaling ratio, and rotation angle of the images are adjusted to eliminate spatial distortions caused by sensor attitude changes, Earth curvature, and atmospheric refraction. The result is a standardized time-series imagery with accurate spatial positioning and uniform geometric shape.

[0023] A digital elevation model (DEM) with a resolution of at least 10 meters and an elevation error of no more than 1 meter is acquired for the target mining area. Based on this DEM, the geometric path length between the terrain elevation corresponding to each pixel in the standardized time-series image and the radar sensor is calculated, and then the terrain phase component of each pixel is obtained. The original phase value in the standardized time-series image is subtracted from the corresponding pixel's terrain phase component to completely eliminate the influence of terrain undulation on the phase, resulting in a differential interferogram that only contains information such as surface deformation and atmospheric disturbance.

[0024] A pixel-by-pixel phase change analysis was performed on the differential interferogram. Based on the spatial continuity of the phase change, regions with linear phase changes and regions with irregular phase changes were identified. The linear trend regions correspond to linear surface deformation, while the irregular regions correspond to nonlinear deformations such as phase disturbances caused by atmospheric turbulence. A spatial domain neighborhood analysis method was used to isolate and extract the phase from the nonlinear deformation regions, separating this phase from the overall phase of the differential interferogram. Only the phase components related to the actual surface deformation were retained, resulting in undisturbed deformation phase information.

[0025] The C-band radar wavelength is fixed at 5.6 cm. The fixed wavelength of the synthetic aperture radar used is clearly defined. Based on the physical relationship between phase and distance—a 360-degree change in phase corresponds to a distance change of one wavelength—the phase value of each pixel in the deformation phase information is converted according to this wavelength ratio, converting the phase unit to the distance unit of centimeters. Simultaneously, each converted distance change value is associated with the corresponding time point of the time-series image, forming time-series deformation data containing the surface deformation distance data of each pixel in the target mining area at different time points.

[0026] The beneficial effects are that by using standardized image acquisition criteria, precise geometric correction benchmarks, clear terrain phase removal basis, and rigorous wavelength ratio conversion logic, various interference factors are eliminated layer by layer. The resulting time-series deformation data has spatial accuracy, information purity, and temporal continuity, which can truly reflect the actual situation of surface deformation in the target mining area. This provides a high-quality and reliable data foundation for subsequent spatiotemporal feature analysis, mining boundary updates, and boundary crossing early warning, ensuring the implementation effect and application reliability of the entire technical solution.

[0027] S2. Perform spatiotemporal feature analysis on the time-series deformation dataset to obtain the cumulative deformation zone and deformation rate gradient zone of the target mining area; In this embodiment of the invention, the step of performing spatiotemporal feature analysis on the time-series deformation dataset to obtain the cumulative deformation zone and deformation rate gradient band of the target mining area includes: In the time domain, trend component decomposition is performed on the time-series deformation data to construct the cumulative deformation trend field of the target mining area; Based on the preset deformation influence judgment rules, the cumulative deformation trend field is spatially filtered to obtain the significant deformation area of ​​the target mining area; Spatial connectivity analysis was performed on the areas of significant deformation to obtain the cumulative deformation area of ​​the target mining area. In the spatial dimension, anisotropy detection is performed on the temporal deformation data to construct the spatial variation intensity field of the target mining area; Boundary identification is performed on the spatially varying intensity field to obtain the transition zone of the spatially varying intensity field, and the continuous spatial contour of the transition zone is extracted to generate the initial gradient zone of the target mining area. The spatial relationship between the initial gradient zone and the cumulative deformation zone is verified to obtain the deformation rate gradient zone of the target mining area.

[0028] For the surface deformation distance data at different time points corresponding to each pixel in the time-series deformation data, all deformation distance data of each pixel are arranged in chronological order according to the timestamp, forming a deformation time series for each pixel. The part in the deformation time series that maintains a consistent direction of change and has a stable change amplitude at multiple consecutive time points is defined as the long-term stable change part of each pixel over time. At the same time, the values ​​that appear at a few time points in the deformation time series that are opposite to the overall change direction or have a sudden change amplitude are identified and the change parts corresponding to these values ​​are removed. Finally, the long-term stable deformation change trends of all pixels are integrated according to their spatial location in the target mining area to form a cumulative deformation trend field covering the entire target mining area.

[0029] A cumulative deformation threshold of 1 cm is defined. This threshold is set based on the minimum identifiable impact range of surface deformation caused by coal mining activities. The cumulative deformation trend value corresponding to each pixel in the cumulative deformation trend field is extracted one by one. This value is directly compared with 1 cm. When the cumulative deformation trend value of a pixel reaches 1 cm or equals 1 cm, the surface area corresponding to that pixel is directly determined to be an effective deformation area associated with mining activities. Then, all pixels that meet this determination condition are completely collected according to their spatial location to form continuous or scattered areas. This area is the significant deformation area.

[0030] Using a single pixel as an independent analysis unit, for each pixel within the deformation saliency region, its eight adjacent pixels in the top-bottom, left-right, top-left, top-right, bottom-left, and bottom-right directions are examined sequentially to confirm whether each adjacent pixel is marked as a deformation saliency region. If any of the adjacent pixels belongs to the deformation saliency region, it is determined that the current pixel and that adjacent pixel have a connectivity relationship. Then, all pixels within the deformation saliency region are continuously traversed in the order from left to right and from top to bottom. All pixels that have a connectivity relationship with each other are completely integrated to form one or more unbroken continuous spatial regions. This continuous spatial region is the cumulative deformation region.

[0031] For each pixel in the target mining area, the deformation rate difference between the current pixel and its directly adjacent pixels in each of the four fixed spatial directions (east-west, north-south, northeast-southwest, and northwest-southeast) is calculated. The deformation rate differences obtained in these four directions are summed to obtain the spatial change intensity value corresponding to the pixel. After calculating the spatial change intensity value of all pixels, the corresponding spatial change intensity values ​​are arranged one by one according to the actual spatial position of each pixel in the target mining area to form a spatial change intensity field covering the entire target mining area.

[0032] Following a row-by-row and column-by-column order, each pixel in the spatial variation intensity field is traversed sequentially. The spatial variation intensity value of the current pixel is compared with the spatial variation intensity values ​​of its four adjacent pixels (up, down, left, and right). When the spatial variation intensity value of the current pixel is found to be unequal to that of any adjacent pixel, and this inequality continues to occur among five or more consecutive pixels, the spatial range occupied by these pixels with consecutive intensity value changes is defined as the transition zone of the spatial variation intensity field. Then, along the outermost pixels of the transition zone, they are connected sequentially according to their spatial positions, ensuring that there are no breaks or intersections in the connection process, forming a closed or continuous spatial contour. The area enclosed by this spatial contour is the initial gradient band.

[0033] Extract the edge pixel set of the initial gradient zone and the edge pixel set of the cumulative deformation zone respectively. Check each pixel on the edge of the initial gradient zone to confirm whether it also belongs to the edge pixel of the cumulative deformation zone. Count the number of pixels that belong to both the edge of the initial gradient zone and the edge of the cumulative deformation zone. Calculate the ratio of this number to the total number of edge pixels in the initial gradient zone. When the ratio reaches 80% or more, it is determined that the spatial relationship between the initial gradient zone and the cumulative deformation zone meets the matching requirements. The initial gradient zone that passes the matching verification is directly determined as the deformation rate gradient zone of the target mining area.

[0034] The beneficial effects are that by clarifying the deformation time series sorting method, quantifying the deformation judgment threshold, refining the connectivity verification logic, standardizing the spatial change intensity calculation process, and clarifying the judgment criteria for transition zones and the spatial relationship matching ratio, each step of the extraction process of cumulative deformation zone and deformation rate gradient zone has a clear operational basis, ensuring that the results are reproducible and highly accurate, and fully preserving the spatiotemporal core characteristics of the target mining area deformation. This provides clear and reliable basic data for subsequent spatial correlation verification with mining activity patches, further ensuring the accuracy of subsequent mining boundary updates and risk warnings.

[0035] S3. Spatial correlation verification is performed between the cumulative deformation zone and the deformation rate gradient zone and the mining activity patches of the target mining area to obtain the characteristic interlocking results of the target mining area. In this embodiment of the invention, the step of spatially correlating and verifying the cumulative deformation zone and deformation rate gradient zone with the mining activity patches of the target mining area to obtain the feature interlocking results of the target mining area includes: Under a unified geospatial reference framework, the cumulative deformation zone, deformation rate gradient zone and mining activity patches of the target mining area are overlaid to obtain a spatial composite layer of the target mining area. Based on the spatial composite layer and cumulative deformation zone, the spatial coverage of the core area in the mining activity patch is determined to determine the spatial ownership, and a spatial coverage analysis report of the target mining area is obtained. Based on the spatial composite layer, the adjacency relationship between the spatial topological relationship between the deformation rate gradient zone and the boundary of the mining activity patch is identified, and the topological relationship identification conclusion of the target mining area is obtained. By logically integrating the spatial coverage analysis report and the topological relationship identification conclusions, a preliminary interlocking determination result for the target mining area is obtained. Based on the geological background data of the target mining area, spatial consistency analysis was conducted on the preliminary interlocking determination to obtain the characteristic interlocking results of the target mining area.

[0036] The process of logically synthesizing the spatial coverage analysis report and the topological relationship identification conclusions to obtain the preliminary interlocking determination results of the target mining area includes: The comprehensive correlation index of the target mining area is obtained by weighting and comprehensively evaluating the core area coverage rate index in the spatial coverage analysis report and the adjacency strength index in the topological relationship identification conclusion. Based on the spatial composite layer, the spatial relationship between the deformation center point of the cumulative deformation zone and the geometric center of the mining activity patch is vectorized to obtain the offset vector of the target mining area. By integrating the comprehensive correlation index with the spatial consistency of the offset vector, a preliminary interlocking determination result for the target mining area is obtained.

[0037] The National Geodetic Coordinate System 2000 is adopted as a unified geospatial reference framework. This coordinate system is my country's legally mandated geospatial benchmark, which ensures that the coordinate systems of the cumulative deformation zone, deformation rate gradient zone, and mining activity plot are completely consistent. Then, the spatial data of the three are matched one by one according to latitude and longitude coordinates, so that the three types of information corresponding to each coordinate point—the deformation attribute of the cumulative deformation zone, the intensity attribute of the deformation rate gradient zone, and the mining attribute of the mining activity plot—are mutually bound and fully integrated to form a single layer containing all spatial location information and attribute description information. This layer is the spatial composite layer.

[0038] The core area of ​​the mining activity patch is determined as the region uniformly contracted towards the center, based on the geometric center of the patch, until the area reaches 50% of the total area of ​​the original mining activity patch. In the spatial composite layer, all pixels within the core area are precisely extracted according to the latitude and longitude coordinates. At the same time, the coordinate information of all pixels in the cumulative deformation area is extracted. The number of pixels whose coordinates in the core area coincide with those in the cumulative deformation area is checked and counted row by row and column by column. The number of overlapping pixels is divided by the total number of pixels in the core area to obtain the coverage ratio of the core area, which is retained to two decimal places. The start and end values ​​of the latitude and longitude of the core area, the specific distribution grid number of the cumulative deformation area in the core area after grid division, and the above coverage ratio are recorded in detail. This information is systematically organized to form a spatial coverage analysis report.

[0039] The adjacency criterion is set as follows: the straight-line distance between the boundary pixels of the deformation rate gradient zone and the mining activity patch does not exceed 50 meters. In the spatial composite layer, the latitude and longitude coordinates of all boundary pixels of the deformation rate gradient zone and the mining activity patch are extracted respectively. After converting the latitude and longitude coordinates into planar coordinates, the straight-line distance between each boundary pixel of the deformation rate gradient zone and each boundary pixel of the mining activity patch is calculated one by one. The number of pixel pairs with a distance value less than or equal to 50 meters is counted. Adjacent pixels that meet the adjacency criterion are connected in coordinate order to form continuous line segments. The length of each continuous line segment is calculated by the difference between the coordinates at the two ends of the line segment and accumulated. The proportion of the accumulated length to the total length of the deformation rate gradient zone boundary and the proportion to the total length of the mining activity patch boundary are calculated respectively. The number of pixel pairs, the two proportion values, and the latitude and longitude start and end coordinates of the adjacent area, as well as the coordinates of the start and end pixels, are organized to form the topological relationship identification conclusion.

[0040] The weighting of the core area coverage rate is set at 0.6, and the weighting of the adjacency strength is set at 0.4. This weighting is based on the principle that the core area coverage rate directly reflects the internal relationship between mining activities and deformation, and has a higher priority, while the adjacency strength reflects the external relationship between the two, and has a lower priority. The core area coverage rate is the ratio recorded in the spatial coverage analysis report and retained to two decimal places. The adjacency strength is the average ratio obtained by adding the cumulative length of continuous line segments that meet the adjacency criteria to the total length of the deformation rate gradient zone boundary and the ratio to the total length of the mining activity patch boundary, and then dividing by 2. The core area coverage rate is multiplied by 0.6, and then the adjacency strength is multiplied by 0.4. All values ​​in the calculation process are retained to three decimal places. The value obtained through this calculation is the comprehensive correlation index, which is strictly between 0 and 1.

[0041] In the spatial composite layer, the sum of the x-coordinate values ​​of all pixels in the cumulative deformation zone is calculated and divided by the total number of pixels in the cumulative deformation zone to obtain the average x-coordinate. Similarly, the average y-coordinate is calculated. The coordinate point corresponding to the average x-coordinate is determined as the deformation center point of the cumulative deformation zone. The coordinate values ​​are retained to six decimal places. Similarly, the sum of the x-coordinate values ​​of all pixels in the mining activity patch is calculated and divided by the total number of pixels in the patch, and the sum of the y-coordinate values ​​is divided by the total number of pixels in the patch to obtain the geometric center coordinates of the patch, and retained to six decimal places. Taking the geometric center as the starting point and the deformation center point as the ending point, the latitude and longitude coordinates of the two points are converted into plane rectangular coordinates. The straight-line distance is calculated by adding the square of the difference between the x-coordinate and the square of the difference between the y-coordinate and taking the square root. The direction is determined by calculating the azimuth angle from the starting point to the ending point. The azimuth angle is marked from 0 to 360 degrees and retained to one decimal place, forming an offset vector that simultaneously records distance and azimuth information and has both length and direction attributes.

[0042] The spatial consistency determination rule is set as follows: if the azimuth angle of the offset vector is within the azimuth range of the unmined area marked on the target mining area mining plan map, and the distance value of the offset vector is less than or equal to 100.00 meters, the spatial consistency degree is recorded as 1; otherwise, it is recorded as 0. Simultaneously, the comprehensive correlation index threshold is set to 0.7. When the comprehensive correlation index value is greater than or equal to 0.7 and the spatial consistency degree is 1, the preliminary interlocking determination result is strong correlation; when the comprehensive correlation index value is between 0.4 and 0.7 and the spatial consistency degree is 1, or when the comprehensive correlation index value is greater than or equal to 0.7 but the spatial consistency degree is 0, the preliminary interlocking determination result is medium correlation; when the comprehensive correlation index value is less than 0.4, or when the spatial consistency degree is 0 and the comprehensive correlation index value is less than 0.7, the preliminary interlocking determination result is weak correlation.

[0043] Collect geological background data such as stratigraphic lithology distribution maps and geological structure survey reports of the target mining area, verified by authoritative departments. Identify areas prone to deformation as soft rock strata distribution areas, and areas with well-developed geological structures as fault and fold distribution areas. The spatial consistency analysis standard is that the overlap area between the associated areas in the preliminary interlocking determination results and the soft rock strata distribution areas, fault and fold distribution areas, accounts for no less than 60.00% of the total area of ​​the associated areas. Accurately overlay the associated areas from the preliminary interlocking determination with the soft rock strata distribution areas, fault and fold distribution areas in the geological background data according to coordinates. Statistically count areas that simultaneously belong to the associated areas and the aforementioned easily deformable areas... The number of pixels in the constructed development region is multiplied by the actual ground area corresponding to a single pixel to obtain the overlapping area. The total area of ​​the associated region is obtained by multiplying the total number of pixels in the associated region by the actual ground area of ​​a single pixel. The ratio of the overlapping area to the total area of ​​the associated region is calculated and rounded to two decimal places. If the ratio is greater than or equal to 60.00%, the preliminary interlocking determination result is directly used as the feature interlocking result. If the ratio is less than 60.00%, the association strength of the preliminary interlocking determination result is reduced by one level, i.e., strong association is reduced to medium association, medium association is reduced to weak association, and weak association remains unchanged, thus obtaining the final feature interlocking result.

[0044] The beneficial effects include: ensuring coordinate uniformity by adopting a statutory geospatial benchmark; clarifying the shrinkage method and coverage calculation logic of the core area; refining the adjacency determination and intensity calculation process; reasonably setting the basis for weight allocation; accurately standardizing the calculation of center points and the construction method of offset vectors; clarifying the criteria for spatial consistency determination; and conducting correlation verification in conjunction with authoritative geological data. Each step of the operation has a specific and executable process and clear judgment basis, ensuring the accuracy and reproducibility of the feature interlocking results. It clearly and reliably establishes the internal and external correlation between mining activities and surface deformation, providing comprehensive and solid data support for the accurate identification of the mining disturbance front in the future, and further ensuring the accuracy and effectiveness of subsequent mining boundary update work.

[0045] S4. Based on the mining disturbance front identified by the feature interlocking results, the initial mining boundary of the target mining area is profiled and evolved to obtain the updated mining boundary of the target mining area. In this embodiment of the invention, the step of performing contour evolution on the initial mining boundary of the target mining area based on the mining disturbance front identified by the feature interlocking result to obtain the updated mining boundary of the target mining area includes: Extract spatial geometric information of the mining disturbance leading edge from the feature interlocking results; By spatially overlaying spatial geometric information with the initial mining boundary, the section to be expanded in the target mining area is obtained; Using spatial geometric information as the evolution benchmark, spatial extrapolation is performed on the section to be expanded to obtain the evolved boundary segment of the target mining area; After the evolution of the boundary segment, gaps are filled to obtain the transition boundary of the target mining area. The unchanged portions of the transition boundary and the initial mining boundary are topologically reconstructed to obtain the updated mining boundary of the target mining area.

[0046] The process of spatially overlaying spatial geometric information with the initial mining boundary to obtain the target mining area's expansion section includes: Based on spatial geometric information, determine the boundary evolution analysis range of the target mining area; Within the scope of boundary evolution analysis, the initial mining boundary is topologically superimposed based on spatial geometric information to obtain the original area to be expanded in the target mining area; The original area to be expanded is broken up and the purified section of the target mining area is obtained by removing the broken sections. The purified sections will be integrated into the expansion sections of the target mining area.

[0047] The mining disturbance front region, marked with strong or moderate correlation in the feature interlocking results, is identified. This marking is determined based on the previous comprehensive correlation index and spatial consistency analysis results. The region is scanned row by row and column by column in a left-to-right, top-to-bottom order. The latitude and longitude coordinates of all boundary pixels are recorded and six decimal places are retained. The direction of the line segments of adjacent boundary pixels is compared. When the azimuth angle of adjacent line segments changes by more than 30 degrees, the turning point is identified as the boundary inflection point. The latitude and longitude coordinates of all inflection points are recorded, and the azimuth angle of the line segments between adjacent inflection points is determined. At the same time, the actual ground length of the line segments between each inflection point is measured and accumulated to obtain the total boundary length. The outline shape of the region and the specific extension direction of each boundary segment are described. All coordinate data, shape description, direction azimuth angle and length values ​​are systematically integrated to form the spatial geometric information of the mining disturbance front.

[0048] Based on the latitude and longitude coordinates of the outermost boundary pixel of the mining disturbance front, the latitude and longitude difference corresponding to 1 meter is calculated according to the latitude of the target mining area. This difference is accumulated in the direction away from the initial mining boundary to expand the latitude and longitude increment corresponding to 200 meters. This distance is determined with reference to the conventional influence range of coal mining activities extending outward. The coordinates of the easternmost, westernmost, northernmost, and southernmost sides after expansion are used as boundaries to clarify the start and end values ​​of longitude in the east-west direction and the start and end values ​​of latitude in the north-south direction, forming a closed rectangular area. This rectangular area is the boundary evolution analysis range of the target mining area.

[0049] Obtain the latitude and longitude coordinates of the initial mining boundary of the target mining area, which have been filed with the natural resources department. The coordinate accuracy is consistent with the spatial geometric information. Within the determined boundary evolution analysis range, the coordinates of each pixel point of the initial mining boundary are topologically superimposed and compared with the coordinates of each pixel point in the spatial geometric information of the mining disturbance front. When the pixel point coordinates are outside the latitude and longitude range of the initial mining boundary, within the boundary evolution analysis range, and completely coincide with the pixel point coordinates of the mining disturbance front, the pixel point is assigned to the corresponding region. Integrate all pixels that meet the conditions, and clearly record the latitude and longitude coordinates of all pixels in the region and the range outline marked in the order of inflection points. This region is the original area to be expanded in the target mining area.

[0050] The criteria for determining a broken section are: the number of consecutive pixels is less than 50, and the actual ground area corresponding to a single pixel is 1 square meter. That is, 50 consecutive pixels correspond to a ground area of ​​50 square meters. Each consecutive section in the original area to be expanded is inspected one by one from left to right and from top to bottom. A consecutive section is defined as a set of pixels whose horizontal or vertical coordinates are adjacent and all belong to the original area to be expanded. The total number of pixels contained in each consecutive section is counted. When the total number of pixels is less than 50, the section is identified as a broken section. All pixel coordinates corresponding to these broken sections are deleted from the coordinate set of the original area to be expanded. Continuous sections with a total number of pixels of not less than 50 are retained. These retained sections are the purified sections of the target mining area.

[0051] All purified sections are spatially distributed and sorted in ascending order of east longitude and north latitude. Adjacent purified sections are analyzed one by one, extracting the latitude and longitude coordinates of edge pixels and converting them to Cartesian coordinates. The straight-line distance between edge pixels is calculated. When the distance is less than 1 meter, the edge pixels of adjacent sections are directly connected according to coordinate order, making the sections a unified whole. When the distance is greater than 1 meter, the coordinates of supplementary pixels are calculated evenly at 1-meter intervals along the straight line connecting the two edge pixels. The number of supplementary pixels is the integer part of the distance difference. The coordinates of the supplementary pixels are then assigned to the adjacent sections, connecting the two sections through these supplementary pixels. Ultimately, this integrates to form one or more complete and continuous regions, which are the expansion sections of the target mining area.

[0052] Using the extension direction of each boundary segment of the mining disturbance front as the evolution benchmark of spatial geometric information, the azimuth angle and extension trend corresponding to the boundary of each segment to be expanded are clearly defined. Along this trend direction, starting from the outermost boundary pixel of the segment to be expanded, the extension continues outward at the same azimuth angle as the boundary corresponding to the mining disturbance front. The coordinates of each extension point are calculated by adding the latitude and longitude increments corresponding to the azimuth angle to the coordinates of the previous boundary point. The length of the extension matches the depth of the segment to be expanded, ensuring that the extended boundary is consistent with the shape of the mining disturbance front, forming an evolved boundary segment that is spatially perfectly matched with the segment to be expanded.

[0053] The pixel distribution of the evolved boundary segment is checked segment by segment. The Cartesian coordinates of two adjacent boundary points on each segment are extracted, and the actual ground distance between the two points is calculated. When the distance is greater than 1 meter, it is determined that there is a gap. On the straight line connecting the two boundary points, the coordinates of the intermediate supplementary pixels are calculated evenly at 1-meter intervals. The number of supplementary pixels is the integer difference between the distance between the two points and 1 meter. The coordinates of these supplementary pixels are inserted between the two boundary points in sequence so that the actual ground distance between each adjacent pixel is equal to 1 meter, ensuring that the boundary segment has no gaps or breaks, and forming a continuous and complete transition boundary.

[0054] Extract the coordinates of all pixels in the initial mining boundary and compare them one by one with the coordinates of pixels in the section to be expanded. When the coordinates of pixels in the initial mining boundary do not overlap with the coordinates of pixels in the section to be expanded, the boundary formed by these pixels is the unchanged part of the initial mining boundary. Align the latitude and longitude coordinates of the starting endpoint of the transition boundary with the latitude and longitude coordinates of the ending endpoint of the unchanged part of the initial mining boundary. Align the ending endpoint of the transition boundary with the other starting endpoint of the unchanged part of the initial mining boundary. Reconnect all the boundary points of the transition boundary and the unchanged part of the initial mining boundary in sequence according to the order of east longitude coordinates from small to large and north latitude coordinates from small to large. During the connection process, ensure that the line segments do not cross or overlap, and finally form the updated mining boundary of the closed target mining area.

[0055] The beneficial effects are as follows: by clarifying the criteria for correlation strength screening, coordinate accuracy standards, inflection point determination conditions, and length calculation methods, the spatial geometric information extraction is ensured to be accurate; by converting the extension distance to actual latitude, the boundary evolution analysis range is set scientifically; by comparing coordinates point by point, the accuracy of topological superposition is achieved; by using quantitative standards to eliminate broken sections and standardizing the integration process, the integrity of the section to be expanded is ensured; by using azimuth as a reference for spatial extrapolation and filling gaps at fixed distances, the transition boundary is ensured to be continuous and smooth; and by completing topological reconstruction through precise coordinate alignment and orderly connection, each step of the operation has a clear and executable basis. The final updated mining boundary coordinates are accurate and the shape is continuous and complete, which can accurately match the extension of actual mining activities, providing accurate and reliable basic boundary data for subsequent risk front delineation and boundary crossing early warning.

[0056] S5. Based on the deformation rate gradient zone, the risk frontier of the updated mining boundary is delineated to obtain the risk progression zone of the target mining area, and the risk progression zone is quantitatively indexed to obtain the risk status label of the target mining area. In this embodiment of the invention, the step of delineating the risk frontier of the updated mining boundary based on the deformation rate gradient band to obtain the risk progression zone of the target mining area includes: By extracting the adjacent area between the deformation rate gradient zone and the updated mining boundary, the candidate front zone of the target mining area is obtained. Using the centerline of the candidate front zone as the baseline, the outer direction of the updated mining boundary is geometrically extended to obtain the initial risk front zone of the target mining area; By determining the boundary contact between the initial risk front zone and the cumulative deformation zone, the risk connectivity zone of the target mining area is obtained. By merging the risk connectivity zone with the updated mining boundary, a risk progression zone for the target mining area is obtained.

[0057] The process of quantifying and indexing the risk progression zone to obtain the risk status label of the target mining area includes: Extract statistical characteristics of deformation rate within the risk progression zone; By normalizing and aggregating the statistical characteristics of deformation rate, the risk progression zone and the average distance of the updated mining boundary, a comprehensive risk quantification index for the target mining area is obtained. Based on a predefined industry standard risk classification framework, the comprehensive risk quantification index is mapped to the risk status label of the target mining area.

[0058] Extract the latitude and longitude coordinates of all boundary pixels of the deformation rate gradient zone and the updated mining boundary. Set the proximity criterion as the actual straight-line distance between two boundary pixels on the ground does not exceed 100 meters. This distance is based on the conventional early warning range of coal mine boundary risk. Calculate the straight-line distance between each boundary pixel of the deformation rate gradient zone and each boundary pixel of the updated mining boundary. Select all deformation rate gradient zone pixels that meet the proximity criterion. Integrate these pixels according to their spatial distribution to form a continuous region, which is the candidate front zone of the target mining area. At the same time, record the boundary coordinates and contour range of the candidate front zone.

[0059] Within the candidate front zone, several sampling lines are uniformly selected along its width. Each sampling line intersects with the two edges of the candidate front zone. The coordinates of the midpoint between the intersection of each sampling line and the two edges are calculated. All midpoint coordinates are connected sequentially along the extension direction of the candidate front zone to form a continuous straight line or curve. This line is the centerline of the candidate front zone. Using this centerline as the baseline, the zone is extended 50 meters parallel to the outer perimeter away from the updated mining boundary. During the extension process, the parallel relationship and distance with the centerline are maintained. The closed area formed after the extension is the initial risk front zone of the target mining area.

[0060] Extract the coordinates of all boundary pixels in the initial risk front zone and the cumulative deformation zone. Set the boundary contact judgment criteria as the actual ground straight-line distance between two boundary pixels being less than 1 meter or their coordinates completely coinciding. Compare the positional relationship between the boundary pixels in the initial risk front zone and the boundary pixels in the cumulative deformation zone one by one, count the number of pixels that meet the contact criteria and the length of the line segments in continuous contact, and completely extract the parts in the initial risk front zone that have contact with the cumulative deformation zone. These extracted areas are the risk connectivity zones of the target mining area, and clearly record the boundary coordinates and range of the risk connectivity zones.

[0061] Extract the coordinates of all pixels in the risk connectivity zone and the updated mining boundary. Find the edge pixels adjacent to the risk connectivity zone and the updated mining boundary. Precisely connect the edge pixels of the risk connectivity zone and the corresponding edge pixels of the updated mining boundary in coordinate order. During the connection process, ensure that the line segments do not intersect, overlap, or have gaps. Integrate the area enclosed by the connected risk connectivity zone and the updated mining boundary to form a continuous closed area, which is the risk progression zone of the target mining area.

[0062] The algorithm iterates through all pixels within the risk progression zone, extracts the deformation rate data for each pixel, calculates the sum of all pixel deformation rate data, and divides this sum by the total number of pixels within the risk progression zone to obtain the average deformation rate within the risk progression zone. This data is one of the core parameters of the comprehensive risk quantification index. The algorithm then calculates the difference between the deformation rate of each pixel and the average deformation rate, squares each difference, sums the squares, divides the sum by the total number of pixels, and then calculates the standard deviation of the deformation rate within the risk progression zone through the inverse operation of the squares. This standard deviation reflects the fluctuation of the deformation rate. Finally, the algorithm selects the pixel corresponding to the geometric center point of the risk progression zone, calculates the absolute value of the difference between the deformation rate of each pixel and the deformation rate of the center point, sums all the absolute values ​​of the differences, and divides the sum by the total number of pixels to obtain the spatial distribution dispersion of the deformation rate within the risk progression zone. This reflects the spatial uniformity of the deformation rate distribution. The average deformation rate, standard deviation, and spatial distribution dispersion together constitute the statistical characteristics of the deformation rate.

[0063] The coordinates of the boundary pixels of the risk progression zone and the updated mining boundary are extracted. The straight-line distance between each boundary pixel in the risk progression zone and the nearest boundary pixel in the updated mining boundary is calculated. All distance values ​​are summed and divided by the total number of boundary pixels in the risk progression zone to obtain the average distance between them. The average deformation rate of the time-series deformation data is obtained from the time-series synthetic aperture radar image data of the target mining area after geometric correction, terrain phase removal, nonlinear deformation separation, and wavelength scaling conversion. The deformation rate of all pixels is summed and divided by the total number of pixels. The standard deviation of the deformation rate of the time-series deformation data is obtained by first calculating the average deformation rate of the time-series deformation data, then calculating the difference between the deformation rate of each pixel and the average value, squaring and summing the results, dividing by the total number of pixels, and then squaring the result. The deformation spatial distribution dispersion of the target mining area is obtained through inverse operations. It is calculated by first determining the geometric center point of the target mining area, extracting the deformation rate at that point, calculating the absolute value of the difference between the deformation rate of each pixel and the deformation rate of the center point, summing these values, and dividing by the total number of pixels. The characteristic distance of the target mining area is determined based on the mining area's mining planning documents, historical mining boundary expansion records, and the size of the mining area's geographical scope. It is obtained by acquiring multiple distance data from the mining boundary to the outer geographical boundary of the mining area and calculating the average value. The average deformation rate of the risk progression zone is divided by the average deformation rate of the time-series deformation data, the standard deviation is divided by the standard deviation of the deformation rate of the time-series deformation data, the spatial distribution dispersion is divided by the deformation spatial distribution dispersion of the target mining area, and the average distance is divided by the characteristic distance of the target mining area, resulting in four normalized values. The calculation formula for the comprehensive risk quantification index is as follows: ; In the formula, As a comprehensive indicator for risk quantification, The average deformation rate within the risk progression zone. The average deformation rate of the time-series deformation data. The preset deformation intensity weighting coefficient, The standard deviation of the deformation rate within the risk progression zone. The standard deviation of the deformation rate for time-series deformation data. The pre-defined deformation fluctuation weighting coefficient. This represents the spatial dispersion of deformation rate within the risk progression zone. The spatial dispersion of deformation in the target mining area. This represents the average spatial distance between the risk progression zone and the updated mining boundary. The characteristic distance of the target mining area. It is an exponential function. The system employs a pre-defined risk calibration normalization coefficient. The pre-defined deformation intensity weighting coefficient is determined based on historical statistical data from numerous cross-boundary mining cases in the coal mining industry. The correlation between deformation intensity and cross-boundary risk level is analyzed to clarify the priority of influence. The pre-defined deformation fluctuation weighting coefficient is determined by referring to industry standards and combining the correspondence between deformation fluctuation and risk occurrence probability in historical risk events. The weightings are set as follows: deformation intensity 0.4, deformation fluctuation 0.3, and spatial distribution dispersion 0.2. The pre-defined risk calibration normalization coefficient is calibrated based on the numerical range of industry risk assessment standards and actual risk data from multiple mining areas, ensuring the index falls within the 0-1 range. The four normalized values ​​are multiplied by their corresponding weights, summed, and then multiplied by the pre-defined risk calibration normalization coefficient of 1. An exponential function is introduced to reflect the attenuation effect of distance on risk; the greater the distance, the weaker the risk impact. The final value is the comprehensive risk quantification index for the target mining area. This formula integrates deformation rate-related characteristics and spatial distance characteristics, clarifies the priority of each characteristic's influence, eliminates dimensional differences, incorporates the distance attenuation effect, and comprehensively and reasonably quantifies the degree of cross-boundary risk.

[0064] A predefined industry standard risk classification framework is established, clearly defining that a comprehensive risk quantification index of 0.8 or above corresponds to extremely high risk, 0.6 to 0.8 corresponds to high risk, 0.4 to 0.6 corresponds to medium risk, 0.2 to 0.4 corresponds to low risk, and below 0.2 corresponds to extremely low risk. This classification framework is formulated based on industry standards and risk prevention and control requirements for coal mine safety management. The calculated comprehensive risk quantification index is compared with the intervals in the framework to determine its corresponding risk level. Combined with the spatial coordinate range information of the risk progression zone, a risk status label for the target mining area containing the risk level and the location of the risk area is generated.

[0065] The beneficial effects are as follows: by establishing clear proximity criteria, centerline extraction methods, boundary contact rules, and quantitative statistical methods, the delineation of risk progression zones is ensured to be accurate and consistent with actual risk scenarios. The extraction and normalization aggregation process of deformation rate statistical features is standardized. The formula parameters have clear sources and are consistent with actual mining area data. The risk classification framework is formulated based on industry standards, enabling risk status labels to truly reflect the boundary crossing risk status of the mining area. The formula and content are highly consistent, providing a scientific and reliable calculation basis for risk quantification and providing accurate and reliable risk information support for the derivation of subsequent early warning instructions, thereby improving the scientific nature and pertinence of boundary crossing early warnings.

[0066] S6. Derivation of alarm instructions from risk status labels to obtain early warning instructions for the target mining area.

[0067] In this embodiment of the invention, the step of deriving an alarm instruction from the risk status label to obtain an early warning instruction for the target mining area includes: By deconstructing the risk status label, we can obtain the risk level and risk spatial range information of the risk status label. Based on a preset risk alert mapping table, risk levels are matched and retrieved to obtain the standard alert level for the target mining area; By recombining the standard alarm level with the risk spatial range information, an early warning instruction for the target mining area is obtained.

[0068] The risk situation label is deconstructed, containing two core pieces of information: risk level and risk spatial range. The label format is uniformly "risk level - east longitude start and end range - north latitude start and end range". By identifying the explicit expressions "extremely high risk", "high risk", "medium risk", "low risk" and "extremely low risk" in the label, the corresponding risk level is extracted. At the same time, the start and end values ​​of the east longitude and the start and end values ​​of the north latitude in the label are extracted, and the coordinate precision is retained to six decimal places to ensure consistency with the coordinate data of the previous risk progression zone, so as to obtain complete risk spatial range information.

[0069] The preset risk alarm mapping table is formulated based on industry standards for coal mine safety production supervision. The mapping relationship is clearly defined as follows: extremely high risk corresponds to Level 1 alarm, high risk corresponds to Level 2 alarm, medium risk corresponds to Level 3 alarm, low risk corresponds to Level 4 alarm, and extremely low risk corresponds to Level 5 alarm. Each standard alarm level is accompanied by a specific response requirement description. Level 1 alarm is "emergency warning, immediate action required", Level 2 alarm is "high-risk warning, time-limited verification", Level 3 alarm is "moderate warning, enhanced monitoring", Level 4 alarm is "low-risk warning, regular inspection", and Level 5 alarm is "extremely low risk, routine supervision". The risk levels obtained from the deconstruction are precisely compared with the risk levels in the mapping table one by one to find the completely matching entries and extract the corresponding standard alarm level and response requirement description.

[0070] The standard alarm level number, response requirement description, and the longitude and latitude range of the risk area are recombined into a single instruction. The recombined format is fixed as follows: "[Standard Alarm Level]: The target mining area risk zone coordinates are XXX.XXXXXX-XXX.XXXXXX East longitude and XXX.XXXXXX-XXX.XXXXXX North latitude. According to the alarm level requirements, corresponding response measures must be implemented. Relevant responsible units are requested to implement them within the specified time limit." The "corresponding response measures" directly adopt the response requirement description of the corresponding level in the mapping table, ensuring that the instruction contains the three core elements of alarm level, risk location, and execution requirements, forming a complete, clear, and directly executable early warning instruction for the target mining area.

[0071] The beneficial effects are that, through clear label deconstruction rules, standardized risk alert mapping tables, and fixed instruction recombination formats, each step has specific operational standards and judgment criteria to follow, ensuring that the generation process of early warning instructions is reproducible, the results are accurate and unambiguous, and the instructions clearly convey the risk level, the specific location of the risk area, and the corresponding response measures. They can be directly implemented without additional interpretation, greatly improving the execution efficiency and operability of boundary crossing warnings, providing timely and accurate action guidance for mine safety production supervision, and ensuring the pertinence and effectiveness of supervision work.

[0072] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0073] This application embodiment can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0074] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for updating coal mine mining boundaries and providing early warning of boundary violations based on temporal InSAR deformation, characterized in that, The method includes: S1. Perform deformation inversion on the time-series synthetic aperture radar image data of the target mining area to obtain the time-series deformation data of the target mining area; S2. Perform spatiotemporal feature analysis on the time-series deformation dataset to obtain the cumulative deformation zone and deformation rate gradient zone of the target mining area; S3. Spatial correlation verification is performed between the cumulative deformation zone and the deformation rate gradient zone and the mining activity patches of the target mining area to obtain the characteristic interlocking results of the target mining area. S4. Based on the mining disturbance front identified by the feature interlocking results, the initial mining boundary of the target mining area is profiled and evolved to obtain the updated mining boundary of the target mining area. S5. Based on the deformation rate gradient zone, the risk frontier of the updated mining boundary is delineated to obtain the risk progression zone of the target mining area, and the risk progression zone is quantitatively indexed to obtain the risk status label of the target mining area. S6. Derivation of alarm instructions from risk status labels to obtain early warning instructions for the target mining area.

2. The method for updating and warning of coal mine mining boundaries based on temporal InSAR deformation as described in claim 1, characterized in that, The deformation inversion of the time-series synthetic aperture radar image data of the target mining area to obtain the time-series deformation data of the target mining area includes: Acquire temporal synthetic aperture radar (SAR) image data of the target mining area and perform geometric fine correction on the temporal SAR image data to obtain a standardized temporal image of the target mining area. Terrain phase removal is performed on standardized time-series images to obtain differential interferograms of the target mining area; Nonlinear deformation separation is performed on the differential interferogram to obtain the deformation phase information of the target mining area; The deformation phase information is converted by wavelength ratio to obtain the time-series deformation data of the target mining area.

3. The method for updating and warning of coal mine mining boundaries based on temporal InSAR deformation as described in claim 1, characterized in that, The spatiotemporal feature analysis of the time-series deformation dataset yields the cumulative deformation zone and deformation rate gradient band of the target mining area, including: In the time domain, trend component decomposition is performed on the time-series deformation data to construct the cumulative deformation trend field of the target mining area; Based on the preset deformation influence judgment rules, the cumulative deformation trend field is spatially filtered to obtain the significant deformation area of ​​the target mining area; Spatial connectivity analysis was performed on the areas of significant deformation to obtain the cumulative deformation area of ​​the target mining area. In the spatial dimension, anisotropy detection is performed on the temporal deformation data to construct the spatial variation intensity field of the target mining area; Boundary identification is performed on the spatially varying intensity field to obtain the transition zone of the spatially varying intensity field, and the continuous spatial contour of the transition zone is extracted to generate the initial gradient zone of the target mining area. The spatial relationship between the initial gradient zone and the cumulative deformation zone is verified to obtain the deformation rate gradient zone of the target mining area.

4. The method for updating and warning of coal mine mining boundaries based on temporal InSAR deformation as described in claim 1, characterized in that, The step of spatially correlating and verifying the cumulative deformation zone and deformation rate gradient zone with the mining activity patches of the target mining area to obtain the feature interlocking results of the target mining area includes: Under a unified geospatial reference framework, the cumulative deformation zone, deformation rate gradient zone and mining activity patches of the target mining area are overlaid to obtain a spatial composite layer of the target mining area. Based on the spatial composite layer and cumulative deformation zone, the spatial coverage of the core area in the mining activity patch is determined to determine the spatial ownership, and a spatial coverage analysis report of the target mining area is obtained. Based on the spatial composite layer, the adjacency relationship between the spatial topological relationship between the deformation rate gradient zone and the boundary of the mining activity patch is identified, and the topological relationship identification conclusion of the target mining area is obtained. By logically integrating the spatial coverage analysis report and the topological relationship identification conclusions, a preliminary interlocking determination result for the target mining area is obtained. Based on the geological background data of the target mining area, spatial consistency analysis was conducted on the preliminary interlocking determination to obtain the characteristic interlocking results of the target mining area.

5. The method for updating and warning of coal mine mining boundaries based on temporal InSAR deformation as described in claim 4, characterized in that, The process of logically synthesizing the spatial coverage analysis report and the topological relationship identification conclusions to obtain the preliminary interlocking determination results of the target mining area includes: The comprehensive correlation index of the target mining area is obtained by weighting and comprehensively evaluating the core area coverage rate index in the spatial coverage analysis report and the adjacency strength index in the topological relationship identification conclusion. Based on the spatial composite layer, the spatial relationship between the deformation center point of the cumulative deformation zone and the geometric center of the mining activity patch is vectorized to obtain the offset vector of the target mining area. By integrating the comprehensive correlation index with the spatial consistency of the offset vector, a preliminary interlocking determination result for the target mining area is obtained.

6. The method for updating and warning of coal mine mining boundaries based on temporal InSAR deformation as described in claim 1, characterized in that, The mining disturbance front identified based on the feature interlocking results is used to perform contour evolution on the initial mining boundary of the target mining area, resulting in the updated mining boundary of the target mining area. include: Extract spatial geometric information of the mining disturbance leading edge from the feature interlocking results; By spatially overlaying spatial geometric information with the initial mining boundary, the section to be expanded in the target mining area is obtained; Using spatial geometric information as the evolution benchmark, spatial extrapolation is performed on the section to be expanded to obtain the evolved boundary segment of the target mining area; After the evolution of the boundary segment, gaps are filled to obtain the transition boundary of the target mining area. The unchanged portions of the transition boundary and the initial mining boundary are topologically reconstructed to obtain the updated mining boundary of the target mining area.

7. The method for updating and warning of coal mine mining boundaries based on temporal InSAR deformation as described in claim 6, characterized in that, The process of spatially overlaying spatial geometric information with the initial mining boundary to obtain the target mining area's expansion section includes: Based on spatial geometric information, determine the boundary evolution analysis range of the target mining area; Within the scope of boundary evolution analysis, the initial mining boundary is topologically superimposed based on spatial geometric information to obtain the original area to be expanded in the target mining area; The original area to be expanded is broken up and the purified section of the target mining area is obtained by removing the broken sections. The purified sections will be integrated into the expansion sections of the target mining area.

8. The method for updating and warning of coal mine mining boundaries based on temporal InSAR deformation as described in claim 1, characterized in that, The step of delineating the risk frontier of the updated mining boundary based on the deformation rate gradient zone to obtain the risk progression zone of the target mining area includes: By extracting the adjacent area between the deformation rate gradient zone and the updated mining boundary, the candidate front zone of the target mining area is obtained. Using the centerline of the candidate front zone as the baseline, the outer direction of the updated mining boundary is geometrically extended to obtain the initial risk front zone of the target mining area; By determining the boundary contact between the initial risk front zone and the cumulative deformation zone, the risk connectivity zone of the target mining area is obtained. By merging the risk connectivity zone with the updated mining boundary, a risk progression zone for the target mining area is obtained.

9. The method for updating and warning of coal mine mining boundaries based on temporal InSAR deformation as described in claim 1, characterized in that, The process of quantifying and indexing the risk progression zone to obtain the risk status label of the target mining area includes: Extract statistical characteristics of deformation rate within the risk progression zone; By normalizing and aggregating the statistical characteristics of deformation rate, the risk progression zone and the average distance of the updated mining boundary, a comprehensive risk quantification index for the target mining area is obtained. Based on a predefined industry standard risk classification framework, the comprehensive risk quantification index is mapped to the risk status label of the target mining area.

10. A method for updating and warning of coal mine mining boundaries based on temporal InSAR deformation as described in claim 1, characterized in that, The process of deriving alarm commands from risk status labels to obtain early warning commands for the target mining area includes: By deconstructing the risk status label, we can obtain the risk level and risk spatial range information of the risk status label. Based on a preset risk alert mapping table, risk levels are matched and retrieved to obtain the standard alert level for the target mining area; By recombining the standard alarm level with the risk spatial range information, an early warning instruction for the target mining area is obtained.

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