An automatic site selection method, system, device and medium for a natural gas pressure regulating station

Abstract

The present application relates to the technical field of automatic site selection for natural gas pressure regulating stations, and provides a method, system, device and medium for automatic site selection of natural gas pressure regulating stations, including accurately extracting the contour boundary of the water system by using an edge detection algorithm to generate a water system distribution map, and establishing topographic constraints in combination with a slope grading mask; dynamically adjusting the gradient attenuation range of the water system safety buffer zone based on the river bend curvature feature and the confluence density of tributaries to effectively balance water body protection and land use requirements; identifying the boundaries of the building area and the forest protection area through the color and shape features of remote sensing images, and superimposing to generate a composite safety constraint layer; screening low-slope contiguous effective candidate blocks after excluding the protected areas, simulating feasible paths through a depth-first search algorithm, and selecting an area with high connectivity to the main road and small terrain undulation as the final site selection. It reduces the risk of ecological environment damage, ensures the feasibility of project implementation, and achieves the optimal balance of ecological protection, safety protection and construction cost.

Description

Technical Field

[0001] This application relates to the field of automatic site selection for natural gas pressure regulating stations. Specifically, it relates to a method, system, device, and medium for automatic site selection of natural gas pressure regulating stations. Background Art

[0002] The content of this part only provides background information related to this application, and it may not constitute prior art.

[0003] In the early stage, the site selection of natural gas pressure regulating stations mainly relied on manual experience and industry norms, and on-site surveys needed to be carried out in combination with basic parameters such as topography, gas supply radius, and safety distance. Although this method can ensure basic safety requirements, it has defects such as low efficiency, poor dynamic adaptability, and inability to quantitatively evaluate environmental risks. Moreover, there is no technical solution for the automatic site selection of natural gas pressure regulating stations in the prior art.

[0004] The closest Chinese patent with the publication number CN108053060B in the prior art discloses a step-up substation site selection system and site selection method for automatic route selection of roads within a wind farm. It comprehensively considers factors such as distance, slope, and earthwork volume that affect the construction cost of wind power projects, automatically realizes the optimal design of roads for wind farm construction projects, and uses the average shortest distance algorithm to perform intelligent site selection of step-up substations. It improves the accuracy of wind power project design, avoids the increase in project cost caused by the lack of experience of designers, reduces the human and material costs and time consumption of step-up substation design in the wind power industry, improves the construction efficiency of wind power projects, improves the design efficiency of wind power step-up substation projects, and makes the integrated design of wind power projects more flexible, intelligent, and reasonable.

[0005] Although both are for the automatic site selection of buildings, this patent cannot be applied to the site selection of natural gas pressure regulating stations. Specifically, it ignores the accuracy of water system safety protection, which is likely to lead to the selected location being too close to the water body, increasing the flood risk and possibly having an adverse impact on the local water ecosystem. Secondly, it does not effectively reduce the risk of ecological environment damage.

[0006] Therefore, there is an urgent need for a more scientific, comprehensive, and feasible site selection method to meet the actual needs of natural gas pressure regulating stations. Summary of the Invention

[0007] In order to solve the above technical problems, the purpose of this application is to provide a method, system, device, and medium for automatic site selection of natural gas pressure regulating stations. By dynamically adjusting the gradient buffer zone, it improves the accuracy of water system safety protection, uses multi-dimensional space superposition exclusion to reduce the risk of ecological environment damage, combines terrain and road network analysis to ensure the feasibility of project implementation, realizes the optimal balance of ecological protection, safety protection, and construction cost, and significantly improves the site selection efficiency and scientificity.

[0008] The object of the present application is achieved by the following technical solutions:

[0009] In a first aspect, the present invention provides a method for automatically selecting a location for a natural gas pressure regulating station, including:

[0010] Obtain the water system data, road network data, remote sensing image, and digital elevation model data of the target area, and obtain the elevation value data and slope value data from the elevation model data; based on the water system data, use the edge detection algorithm to identify the contour boundary of the water system network on the remote sensing image according to the water body characteristics, and generate a water system distribution map; divide multiple slope regions according to different slope value ranges to form a slope grading mask;

[0011] Based on the water system distribution map, taking the contour boundary of the water system network as the reference line, calculate the buffer distance extending outward from the reference line to the water system network according to the curvature radius of the river bend section and the confluence density of tributaries; generate a water system safety buffer with a gradient attenuation characteristic according to the gradient change among the curvature radius, confluence density, and buffer distance;

[0012] Identify the building area and forest protection area from the remote sensing image based on color and shape characteristics; mark the contours of the forest protection area and the building area as protection red lines, and superimpose the spatial positions of the protection red lines and the water system safety buffer to generate a composite safety constraint layer;

[0013] Perform spatial exclusion on the area included in the protection red line in the composite safety constraint layer, and extract the initial candidate areas with a slope lower than the preset value in the remaining area according to the slope grading mask; select the continuously connected initial candidate areas among the multiple initial candidate areas, and retain the continuously connected initial candidate areas with an area greater than the first preset threshold as effective candidate blocks;

[0014] Based on the road network data and the digital elevation model data, with the height difference between two consecutive points less than or equal to the preset height as the feasible path and the height difference between two consecutive points greater than the preset height as the obstacle as the constraint condition, calculate the number of paths from the geometric center of each effective candidate block to the nearest main road through the depth-first search algorithm, and select the effective candidate block corresponding to the number of paths greater than the preset number and the path length less than the preset distance as the target area, and output the position of the target area and the position of its corresponding path.

[0015] Further, the step of using the edge detection algorithm to identify the contour boundary of the water system network on the remote sensing image according to the water body characteristics specifically includes:

[0016] Calculate the gradient magnitude of each pixel in the remote sensing image through an edge detection operator to generate a gradient map. Based on the spectral characteristics of the sudden drop in the reflectance in the visible light band and the near-infrared band of water bodies, set the gradient threshold range. Synchronously perform gradient magnitude threshold determination and spectral reflectance characteristic verification on each pixel in the gradient map, and extract double-feature pixels that simultaneously meet the gradient jump condition and the water body spectral response law as candidate edge points;

[0017] Perform morphological closing operation on the candidate edge pixel points, connect the broken areas and fill the internal holes through dilation and erosion operations, and generate the contour boundary of a continuous and closed water system network.

[0018] Further, the steps of calculating the buffer distance extending outward from the water system network along the reference line specifically include:

[0019] Calculate the average curvature of the local river section according to the curvature radius of the river bend section, and at the same time count the density of tributary confluence nodes within the unit river length;

[0020] For the curved river channels with a curvature radius less than the second preset threshold, increase the buffer extension distance according to a preset ratio, and adopt a decreasing method to reduce the extension distance for the areas with a tributary confluence density greater than the preset density, and generate a water system safety buffer with a gradient decay characteristic.

[0021] Further, the steps of identifying the built-up area and the forest protection area from the remote sensing image based on color and shape features specifically include:

[0022] Extract the sub-regions with the greenness index meeting the preset index range from the remote sensing image, use the edge detection algorithm to extract the closed contour of the sub-regions, and calculate the shape complexity index of the closed contour; determine the sub-regions with the shape complexity index greater than the preset index threshold as the forest protection areas;

[0023] Perform edge detection and polygon fitting on the remote sensing image, screen out the closed polygon regions with an area within the preset range and a shape compactness higher than the third preset threshold, and determine them as the built-up areas.

[0024] Further, after outputting the position of the target area and the position of its corresponding path, it also includes:

[0025] For the path corresponding to each target area, calculate the path comprehensive cost value based on a preset formula, and screen out the target area with the minimum cost value as the optimal site selection.

[0026] Further, the preset formula is:

[0027]

[0028] Among them, represents the path comprehensive cost value, represents the total path length, is the absolute value of the elevation difference of the th segment of the path, represents the standard deviation of the path curvature radius, represents the average curvature radius of the path, is the length weight coefficient, is the elevation change penalty coefficient, is the path curvature penalty coefficient, is the curvature radius of the th bending segment in the path, is the path segmentation index variable, is the bending segment index variable.

[0029] Furthermore, after outputting the position of the target area and the position of its corresponding path, it further includes:

[0030] Mark the position of the target area and the position of its corresponding path on the remote sensing image to obtain a result reference map, and send the result reference map to a preset terminal;

[0031] After receiving the confirmation from the preset terminal that the result is correct, save the position of the target area and the position of its corresponding path to the final result document.

[0032] In a second aspect, the present invention provides a natural gas pressure regulating station automatic site selection system, including:

[0033] A slope grading mask generation module, which is used to obtain the water system data, road network data, remote sensing image and digital elevation model data of the target area, and obtain the elevation value data and slope value data from the elevation model data; based on the water system data, use the edge detection algorithm to identify the contour boundary of the water system network on the remote sensing image according to the water body characteristics, and generate a water system distribution map; divide multiple slope areas according to different slope value ranges to form a slope grading mask;

[0034] A water system safety buffer generation module, based on the water system distribution map, uses the contour boundary of the water system network as the reference line, and calculates the buffer distance extending outward from the water system network along the reference line according to the curvature radius of the river bend segment and the confluence density of tributaries; generates a water system safety buffer with a gradient attenuation characteristic according to the gradient change among the curvature radius, confluence density and buffer distance;

[0035] A composite safety constraint layer generation module, which identifies the building area and forest protection area from the remote sensing image based on color and shape characteristics; marks the contours of the forest protection area and the building area as protection red lines, and superimposes the spatial positions of the protection red lines and the water system safety buffer to generate a composite safety constraint layer;

[0036] The effective candidate block acquisition module is used to perform spatial exclusion on the area included in the protection red line in the composite security constraint layer, and extract the initial candidate area with a slope lower than the preset value in the remaining area according to the slope grading mask; select the continuously connected initial candidate areas from multiple initial candidate areas, and retain the continuously connected initial candidate areas with an area greater than the first preset threshold as the effective candidate blocks;

[0037] The target area acquisition module, based on the road network data and the digital elevation model data, takes the height difference between two consecutive points less than or equal to the preset height as the feasible path, and the height difference between two consecutive points greater than the preset height as the obstacle as the constraint condition, calculates the number of paths from the geometric center of each effective candidate block to the nearest main road through the depth-first search algorithm, and selects the effective candidate block corresponding to the number of paths greater than the preset number and the path length less than the preset distance as the target area, and outputs the position of the target area and the position of its corresponding path.

[0038] In a third aspect, the present invention provides an electronic device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the computer program, the steps corresponding to the method in the first aspect are implemented.

[0039] In a fourth aspect, the present invention provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps corresponding to the method in the first aspect are implemented.

[0040] In summary, the technical solutions of the embodiments of the present application at least have the following advantages and beneficial effects:

[0041] By integrating water systems, roads, remote sensing images, and terrain data, the present invention uses an edge detection algorithm to accurately extract the contour boundary of the water system to generate a water system distribution map, and establishes terrain constraint conditions in combination with a slope grading mask; then, based on the characteristics of the river channel bending curvature and the density of tributary intersections, the gradient attenuation range of the water system safety buffer zone is dynamically adjusted to effectively balance water body protection and land use requirements; the boundaries of the built-up area and the forest protection area are identified through the color and shape characteristics of the remote sensing image, and the composite security constraint layer is superimposed to achieve double protection of ecology and artificial facilities; after excluding the protected areas, low-slope contiguous effective candidate blocks are screened, and finally, combined with the road accessibility analysis, the depth-first search algorithm is used to simulate the feasible path in the digital elevation model, and the area with high connectivity to the main road and small terrain undulation is preferentially selected as the final site selection. By dynamically adjusting the gradient buffer zone, the accuracy of water system safety protection is improved, the risk of ecological environment damage is reduced by using multi-dimensional space superposition and exclusion, and the feasibility of project implementation is ensured by combining terrain and road network analysis, achieving the optimal balance of ecological protection, safety protection, and construction cost, and significantly improving the site selection efficiency and scientificity. Description of the Drawings

[0042] Figure 1 Flow chart of an automatic site selection method for a natural gas pressure regulating station provided by the present invention;

[0043] Figure 2 Structural schematic diagram of an automatic site selection system for a natural gas pressure regulating station provided by the present invention;

[0044] Figure 3 Structural schematic diagram of an electronic device provided by the present invention. Detailed implementation manners

[0045] To make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. Usually, the components of the embodiments of the present application described and illustrated in the accompanying drawings here can be arranged and designed in various different configurations.

[0046] As Figure 1 shown, an automatic site selection method for a natural gas pressure regulating station proposed in the embodiments of the present application includes:

[0047] S101, obtaining water system data, road network data, remote sensing images and digital elevation model data of a target area, and obtaining elevation value data and slope value data from the elevation model data; based on the water system data, using an edge detection algorithm to identify the contour boundary of the water system network on the remote sensing image according to water body characteristics, generating a water system distribution map; dividing multiple slope areas according to different slope value ranges to form a slope classification mask.

[0048] Specifically, first obtain the water system vector data, road network topology data, high-resolution remote sensing images and digital elevation model (DEM) data of the target area. For example, in a certain planned area, call a 1:10,000 scale water system map through a geographic information system, and at the same time load a 0.5-meter resolution WorldView-3 remote sensing image and DEM data with a 5-meter grid interval to form a multi-dimensional space analysis basic data set. Among them, the DEM data is processed by spatial interpolation to generate an accurate elevation surface, and the elevation value is converted into slope percentage data through a slope calculation module. For example, after calculating a certain hilly area, the slope is divided into three grades: a gentle slope area of 0-5 degrees, a gentle slope area of 5-15 degrees, and a steep slope area of 15-90 degrees, forming a slope classification mask layer that can be partitioned and identified.

[0049] Further, the steps of using an edge detection algorithm to identify the contour boundary of the water system network on the remote sensing image according to water body characteristics specifically include:

[0050] Calculate the gradient magnitude of each pixel in the remote sensing image through an edge detection operator to generate a gradient map. Based on the spectral characteristics of the sudden drop in the reflectance of water bodies in the visible light band and the near-infrared band, set the gradient threshold range. Synchronously perform gradient magnitude threshold determination and spectral reflectance characteristic verification on each pixel in the gradient map, and extract dual-feature pixels that simultaneously meet the gradient jump condition and the water body spectral response law as candidate edge points;

[0051] Perform morphological closing operation on the candidate edge pixel points. Connect the broken areas and fill the internal holes through dilation and erosion operations to generate the contour boundary of a continuous and closed water system network.

[0052] Specifically, for the precise extraction of the water system network, an edge detection algorithm that combines spectral features and morphological features is adopted. During specific implementation, first use the Sobel operator to calculate the gradient magnitude of the remote sensing image. For example, when processing the Landsat8 image of the Taihu Lake Basin, jointly analyze the visible light band (blue, green, red) and the near-infrared band. When it is detected that the reflectance of a certain pixel in the green light band is lower than 25% and the reflectance in the near-infrared band suddenly drops to less than 5%, the water body spectral response condition is triggered. At the same time, calculate the gradient magnitude of this point. When it reaches the preset threshold (such as gradient magnitude > 120), it is determined that this pixel meets both the spectral jump and edge gradient dual conditions and is marked as a candidate edge point. Through this dual verification mechanism, interference areas with similar spectral characteristics such as shadows and asphalt roads can be effectively excluded.

[0053] When performing morphological optimization processing on the candidate edge points, a closing operation combination with a custom structural element is adopted. For example, in the image processing of a certain bay area, for the phenomenon of river boundary breakage caused by cloud cover, a 7×7 circular structural element is selected for dilation operation to connect edge line segments with a broken interval of less than 30 meters; then a 5×5 square structural element is used for erosion operation to eliminate false protrusions and smooth the serrated edges. After this processing, the boundary of the tributaries in this bay area forms a complete closed polygon, and the internal holes caused by ship navigation are effectively filled, and finally a water system distribution vector map that meets the GIS topology requirements is generated. Compared with the traditional single-edge detection method, the recognition accuracy of the water system boundary of this technical solution is improved by about 35%, and the false connection rate is reduced to less than 3%.

[0054] S102. Based on the water system distribution map, taking the contour boundary of the water system network as the reference line, calculate the buffer distance extending outward from the reference line to the water system network according to the curvature radius of the curved section of the river channel and the confluence density of the tributaries; generate a water system safety buffer with a gradient attenuation characteristic according to the gradient change among the curvature radius, the confluence density of the tributaries, and the buffer distance;

[0055] Specifically, first, taking the centerline of the river channel in the water system distribution map generated in step S1 as the reference line, a buffer calculation model with multi-parameter coupling is adopted. For example, when processing a certain section of the river channel, by calculating the distribution of the radius of curvature of the river section through GIS tools, it is found that the average radius of curvature of a certain continuous bend is only 280 meters, significantly lower than the preset threshold of 500 meters. At this time, the system automatically triggers the buffer extension mechanism, and according to the rule of increasing the buffer distance by 15 meters for every 100-meter reduction in the radius of curvature, the buffer distance of this river section is increased from the basic value of 100 meters to 145 meters. This design fully considers the problem of the increased risk of flood scouring caused by the increase in the river channel curvature, ensuring a safe distance between the pressure regulating station and the unstable river bank.

[0056] Furthermore, the step of calculating the buffer distance extending outward from the reference line to the water system network specifically includes:

[0057] Calculate the average curvature of the local river section according to the radius of curvature of the curved river section, and at the same time count the density of tributary confluence nodes within the unit river channel length; for the curved river channel with a radius of curvature less than the second preset threshold, increase the buffer extension distance according to the preset ratio, and adopt a decreasing method to reduce the extension distance for the area where the tributary confluence density is greater than the preset density, generating a water system safety buffer with a gradient attenuation characteristic.

[0058] Specifically, in response to the influence of tributary hydrological characteristics, the system determines the buffer distance correction coefficient through spatial density analysis. For example, in a certain tributary confluence area, it is calculated that there are 3 tributary confluence points per kilometer of the river channel, exceeding the preset density threshold of 2 points / km. At this time, the system starts the decreasing algorithm, and according to the rule of reducing the buffer distance by 8 meters for every additional confluence point, the original basic buffer distance of 120 meters is adjusted to 104 meters. This processing mechanism effectively balances the contradiction between the complexity of the hydrological conditions in the tributary dense area and the land resource utilization efficiency, avoiding insufficient site selection space caused by overly conservative buffer settings.

[0059] When comprehensively dealing with the synergistic effect of the radius of curvature and tributary density, the system adopts a gradient attenuation model to achieve a smooth transition of the buffer distance. For example, in a certain river section, the radius of curvature of a certain curved section is 400 meters, triggering an increase in the buffer distance to 112 meters, while the tributary confluence density in this area is 2.5 points / km, triggering a reduction in the buffer distance by 10 meters. After superposition calculation, the final buffer distance in this area is determined to be 102 meters. This dynamic adjustment mechanism makes the buffer zone boundary form a natural gradient effect, maintaining both the hydrological safety requirements and optimizing the continuity and usability of the site selection area.

[0060] S103, Identify the built-up area and forest protection area from the remote sensing image based on color and shape features; mark the outlines of the forest protection area and the built-up area as protection red lines, and superimpose the spatial positions of the protection red lines and the water system safety buffer to generate a composite safety constraint layer;

[0061] Specifically, sub-regions with greenness indices satisfying a preset index range are extracted from the remote sensing image. The edge detection algorithm is used to extract the closed contour of the sub-region, and the shape complexity index of the closed contour is calculated. Sub-regions with a shape complexity index greater than the preset index threshold are determined as forest protection areas. That is, forest protection areas are first extracted based on vegetation spectral characteristics and morphological analysis. The system calculates the Normalized Difference Vegetation Index (NDVI) from the remote sensing image and filters out vegetation-covered areas with greenness values between 0.3 and 0.8. For example, in the identification of nature reserves, the NDVI is calculated for the red band (B4) and the near-infrared band (B8) of Sentinel-2 imagery (Sentinel-2 Satellite Imagery). The original forest area with NDVI > 0.65 in the core area is successfully extracted. Subsequently, the Canny edge detection algorithm is used to outline the vegetation patch contours, and the shape complexity index (SC = perimeter² / (4π × area)) is calculated. When the SC value exceeds 1.5, it is determined as the morphological feature of the natural forest area. Taking a certain area as an example, the SC value of the natural forest patch reaches 2.3, which is significantly higher than 1.1 of the artificial nursery, thus accurately distinguishing the boundary of the original forest to be protected.

[0062] For the identification of building areas, edge detection and polygon fitting are performed on the remote sensing image, and closed polygon areas with an area within a preset range and a shape compactness higher than the third preset threshold are selected and determined as building areas. That is, the system uses dual criteria of morphological compactness and edge regularity. First, edge detection is performed on the image to generate candidate polygons, and the compactness index (Compactness Index, CI) of each polygon is calculated. For example, in the processing of urban areas, the CI values of the financial district building complexes therein are generally higher than 0.7, while the CI values of natural bare lands are lower than 0.3. After setting the CI threshold to 0.6, the high-rise building agglomeration areas can be effectively filtered out. At the same time, an area filtering mechanism is combined to exclude scattered structures with an area less than 5000 square meters. For example, in the analysis of a certain industrial park, the system accurately identifies the business building complex with an area of 12 hectares and a CI value of 0.78 on the west side of a certain lake, while excluding the temporary shed with an area of only 800 square meters from the protection red line. After the identification of the two types of areas is completed, the system automatically marks the forest protection boundary and the building area contour as the protection red line layer.

[0063] S104, perform spatial exclusion on the areas included in the protection red line in the composite safety constraint layer, and extract the initial candidate areas with slopes lower than the preset value according to the slope grading mask in the remaining areas; select continuously connected initial candidate areas from multiple initial candidate areas, and retain the continuously connected initial candidate areas with an area greater than the first preset threshold as valid candidate blocks.

[0064] Specifically, the system performs an "erasure" operation on the area covered by the protection red line, excluding all areas that have a spatial intersection with the protection red line from the full set of target areas. After completing the spatial exclusion, the system loads the slope classification mask layer generated in step S1 and extracts the initial candidate areas where the slope value is lower than the preset threshold. The slope threshold is set according to the construction specifications of the pressure regulating station. Generally, it is required that the ground slope of the station yard does not exceed 8%. During implementation, the system combines the areas marked as "gentle slope area" (0 - 5 degrees) and "moderate slope area" (5 - 15 degrees) in the slope classification mask, and then filters out the sub - areas with a slope ≤ 8% through re - classification operations.

[0065] Next, the system performs a connectivity analysis on the initial candidate areas. The morphological closing operation algorithm is used to connect the discrete candidate areas spatially. Specifically, it includes: using a circular structuring element to dilate the area edges to bridge adjacent areas, and then using a structuring element of the same size for erosion operation to restore the original geometric features. This process can merge independent areas with a distance less than the radius of the structuring element into a continuous connected body.

[0066] After completing the connectivity processing, the system calculates the geometric area of each connected area and performs area threshold screening. The first preset threshold is determined according to the minimum land use requirement of the pressure regulating station, usually set to 1 hectare. During implementation, the system automatically excludes scattered areas with an area smaller than the threshold and retains the effective candidate blocks that have the conditions for large - scale development. This mechanism effectively avoids the problem of fragmented selected sites caused by terrain fragmentation and ensures the practical engineering feasibility of the candidate blocks.

[0067] S105, based on the road network data and digital elevation model data, with the condition that the height difference between two consecutive points is less than or equal to the preset height as the feasible path and the height difference between two consecutive points being greater than the preset height as the obstacle, calculate the number of paths from the geometric center of each effective candidate block to the nearest main road through the depth - first search algorithm. Select the effective candidate blocks corresponding to the number of paths greater than the preset number and the path length less than the preset distance as the target areas, and output the positions of the target areas and the positions of their corresponding paths.

[0068] Specifically, the system first establishes a path accessibility model under terrain undulation constraints, using the height difference between consecutive path nodes as the criterion for passage feasibility. For adjacent grid points in the digital elevation model, if the absolute value of the height difference between the two points does not exceed the preset threshold (for example, 3 meters), it is determined as a passable path segment; otherwise, it is regarded as a terrain obstacle and path crossing is prohibited. This constraint condition effectively simulates the actual limitations of engineering vehicles and pipeline laying on the ground slope and avoids selecting areas with difficult construction due to steep terrain.

[0069] Subsequently, the system uses the depth-first search algorithm to traverse all potential paths from each valid candidate block to the nearest main road. The algorithm starts from the geometric center of the candidate block, radiates and expands the search in eight directions, recursively visits adjacent grid points, and accumulates the path length. When reaching the edge of any main road, the path is recorded as a valid connection route. Through the exhaustive search strategy, the algorithm can comprehensively detect the terrain features around the block to ensure that no potential passage is missed.

[0070] After completing the path search, the system performs a comprehensive screening of multiple indicators: First, count the number of valid paths in each block, requiring it to reach the preset minimum number of connected paths (e.g., ≥2), to ensure redundancy for project access; Second, screen the path length not exceeding the preset maximum distance threshold (e.g., 5 kilometers) to control the pipeline construction cost. For example, in the evaluation of a certain candidate block, the system detects that there are three independent paths in this block: two 4.3-kilometer paths connecting to Provincial Road S306 and one 3.1-kilometer path connecting to Rural Road Y045. Since the number of paths (3) exceeds the preset threshold (2) and the maximum path length (4.3 kilometers) is less than the 5-kilometer limit, this block is retained as a qualified target area. On the contrary, in another block, although two paths are detected, their lengths reach 5.8 kilometers and 6.2 kilometers respectively, and it is automatically excluded by the system due to exceeding the length threshold.

[0071] Furthermore, after outputting the location of the target area and the location of its corresponding path, it also includes:

[0072] For the path corresponding to each target area, calculate the comprehensive cost value of the path based on a preset formula, and screen out the target area with the minimum cost value as the optimal site selection.

[0073] Among them, the preset formula is:

[0074]

[0075] Among them, represents the comprehensive cost value of the path, represents the total length of the path, is the absolute value of the elevation difference of the th segment of the path, represents the standard deviation of the radius of curvature of the path, represents the average radius of curvature of the path, is the length weight coefficient, is the elevation change penalty coefficient, is the path curvature penalty coefficient, is the radius of curvature of the th bending segment in the path, is the path segment index variable, is the bending segment index variable.

[0076] Further, after outputting the location of the target area and the location of its corresponding path, it further includes:

[0077] Mark the location of the target area and the location of its corresponding path on the remote sensing image to obtain a result reference map, and send the result reference map to a preset terminal.

[0078] Specifically, after completing the path reachability screening of the effective candidate blocks, the system performs spatial visualization integration on the site selection result of the target area and the corresponding connection path. That is, it calls the spatial overlay function of the geographic information system, and overlays the geometric center coordinates of the target area determined in step S5 and the spatial trajectory of its connected path on the original high-resolution remote sensing image base map in the form of a vector layer. Through a preset legend symbol library, the target area is filled with a red semi-transparent polygon, and the path is marked with a yellow dotted line to form an intuitive result reference map.

[0079] After receiving the confirmation from the preset terminal that the result is correct, save the location of the target area and the location of its corresponding path to the final result document.

[0080] Specifically, after the preset terminal receives the result, the engineer conducts multi-dimensional verification through the human-computer interaction interface: First, verify whether the target block completely avoids the water system buffer zone and the protection red line. Second, confirm whether the path direction reasonably avoids steep slope obstacles. When detecting the need for manual correction, the engineer can adjust the boundary of the target area or re-plan the path by means of circle selection, and the modified data is transmitted back to the system through an encryption protocol for secondary calculation. When the terminal confirms that the result is correct, the system persistently stores the target area coordinates and its path topology data to the final result document. The storage format uses the GeoPackage binary file standard of the Open Geospatial Consortium (OGC).

[0081] Based on the same inventive concept, the present invention provides a natural gas pressure regulating station automatic site selection system, including:

[0082] A slope grading mask generation module 201, configured to obtain water system data, road network data, remote sensing images, and digital elevation model data of the target area, and obtain elevation value data and slope value data from the elevation model data; based on the water system data, use an edge detection algorithm to identify the contour boundary of the water system network on the remote sensing image according to the water body characteristics, and generate a water system distribution map; divide multiple slope regions according to different slope value ranges to form a slope grading mask;

[0083] The water system safety buffer generation module 202, based on the water system distribution map, uses the contour boundary of the water system network as the reference line, and calculates the buffer distance extending outward from the reference line to the water system network according to the curvature radius of the river bend section and the confluence density of tributaries; according to the gradient change among the curvature radius, the confluence density of tributaries and the buffer distance, a water system safety buffer with a gradient attenuation feature is generated.

[0084] The composite safety constraint layer generation module 203 identifies the built-up area and the forest protection area from the remote sensing image based on color and shape features; marks the contours of the forest protection area and the built-up area as protection red lines, and superimposes the spatial positions of the protection red lines and the water system safety buffer to generate a composite safety constraint layer.

[0085] The effective candidate block acquisition module 204 is used to perform spatial exclusion on the areas included in the protection red lines in the composite safety constraint layer, and extract the initial candidate areas with a slope lower than a preset value from the remaining areas according to the slope grading mask; select the continuously connected initial candidate areas from multiple initial candidate areas, and retain the continuously connected initial candidate areas with an area greater than the first preset threshold as effective candidate blocks.

[0086] The target area acquisition module 205, based on the road network data and the digital elevation model data, uses the condition that the height difference between two consecutive points is less than or equal to the preset height as the feasible path and the condition that the height difference between two consecutive points is greater than the preset height as the obstacle, and calculates the number of paths from the geometric center of each effective candidate block to the nearest main road through the depth-first search algorithm, and selects the effective candidate blocks corresponding to the number of paths greater than the preset number and the path length less than the preset distance as the target area, and outputs the position of the target area and the position of its corresponding path.

[0087] Based on the same inventive concept, the present invention provides an electronic device, including: a memory 302, a processor 301, and a computer program stored on the memory 302 and executable on the processor 301. When the processor 301 executes the computer program, a method for automatically selecting a location for a natural gas pressure regulating station is implemented.

[0088] Based on the same inventive concept, the present invention provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, a method for automatically selecting a location for a natural gas pressure regulating station is implemented.

[0089] The above are only the preferred embodiments of the present application, and are not used to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. An automatic site selection method for a natural gas pressure regulating station, characterized in that Including: Obtain the water system data, road network data, remote sensing image, and digital elevation model data of the target area, and obtain the elevation value data and slope value data from the elevation model data; Based on the water system data, use the edge detection algorithm to identify the contour boundary of the water system network on the remote sensing image according to the water body characteristics, and generate a water system distribution map; Divide multiple slope regions according to different slope value ranges to form a slope grading mask; Based on the water system distribution map, taking the contour boundary of the water system network as the reference line, calculate the buffer distance extending outward from the water system network along the reference line according to the curvature radius of the river bend section and the confluence density of tributaries; Generate a water system safety buffer with a gradient attenuation feature according to the gradient change between the curvature radius, confluence density, and buffer distance; Identify the built-up area and forest protection area from the remote sensing image based on color and shape features; Mark the contours of the forest protection area and the built-up area as protection red lines, and superimpose the spatial positions of the protection red lines and the water system safety buffer to generate a composite safety constraint layer; Perform spatial exclusion on the area included in the protection red line in the composite safety constraint layer, and extract the initial candidate area with a slope lower than the preset value in the remaining area according to the slope grading mask; Select the continuously connected initial candidate areas among the multiple initial candidate areas, and retain the continuously connected initial candidate areas with an area greater than the first preset threshold as valid candidate blocks; Based on the road network data and digital elevation model data, with the height difference between two consecutive points less than or equal to the preset height as the feasible path and the height difference between two consecutive points greater than the preset height as the obstacle as the constraint condition, calculate the number of paths from the geometric center of each valid candidate block to the nearest main road through the depth-first search algorithm, select the valid candidate block corresponding to the number of paths greater than the preset number and the path length less than the preset distance as the target area, and output the position of the target area and the position of its corresponding path; For the path corresponding to each target area, calculate the comprehensive cost value of the path based on the preset formula, and screen out the target area with the minimum cost value as the optimal site selection; The preset formula is: Among them, represents the path comprehensive cost value, represents the total path length, is the absolute value of the elevation difference of the th segment of the path, represents the standard deviation of the path curvature radius, represents the average curvature radius of the path, is the length weight coefficient, is the elevation change penalty coefficient, is the path curvature penalty coefficient, is the curvature radius of the th bending segment in the path, is the path segmentation index variable, is the bending segment index variable; Mark the position of the target area and the position of its corresponding path on the remote sensing image to obtain a result reference map, and send the result reference map to the preset terminal; After receiving the confirmation from the preset terminal that the result is correct, save the position of the target area and the position of its corresponding path to the final result document.

2. The automatic site selection method for a natural gas pressure regulating station according to claim 1, wherein, The step of using the edge detection algorithm to identify the contour boundary of the water system network on the remote sensing image according to the water body characteristics specifically includes: Calculate the gradient amplitude of each pixel point of the remote sensing image through the edge detection operator to generate a gradient map, set the gradient threshold range based on the spectral characteristics of the sudden drop in the reflectivity of the water body in the visible light band and the near-infrared band reflectivity, perform gradient amplitude threshold determination and spectral reflection characteristic verification on each pixel point in the gradient map simultaneously, and extract the dual-characteristic pixels that simultaneously meet the gradient jump condition and the water body spectral response law as candidate edge points; Perform morphological closing operation on the candidate edge pixels, connect the broken areas and fill the internal holes through dilation and erosion operations, and generate the contour boundary of the continuous and closed water system network.

3. The automatic site selection method for a natural gas pressure regulating station according to claim 1, wherein, The step of calculating the buffer distance extending outward from the water system network along the reference line specifically includes: Calculate the average curvature of the local river section according to the curvature radius of the river bend section, and at the same time count the density of tributary confluence nodes per unit river length; For the curved river with a curvature radius less than the second preset threshold, increase the buffer extension distance according to a preset ratio, and adopt a decreasing method to reduce the extension distance for the area where the tributary confluence density is greater than the preset density, and generate a water system safety buffer with gradient attenuation characteristics.

4. The automatic site selection method for a natural gas pressure regulating station according to claim 1, wherein The step of identifying the building area and the forest protection area from the remote sensing image based on color and shape features specifically includes: Extract the sub-region with the greenness index meeting the preset index range from the remote sensing image, use the edge detection algorithm to extract the closed contour of the sub-region, and calculate the shape complexity index of the closed contour; determine the sub-region with the shape complexity index greater than the preset index threshold as the forest protection area; Perform edge detection and polygon fitting on the remote sensing image, screen out the closed polygon areas with an area within the preset range and a shape compactness higher than the third preset threshold, and determine them as the building area.

5. An automatic site selection system for a natural gas pressure regulating station, characterized in that, Include: A slope grading mask generation module, used to obtain the water system data, road network data, remote sensing image and digital elevation model data of the target area, and obtain the elevation value data and slope value data from the elevation model data; based on the water system data, use the edge detection algorithm to identify the contour boundary of the water system network on the remote sensing image according to the water body characteristics, and generate a water system distribution map; divide multiple slope areas according to different slope value ranges to form a slope grading mask; A water system safety buffer generation module, based on the water system distribution map, using the contour boundary of the water system network as the reference line, calculate the buffer distance extending outward from the water system network along the reference line according to the curvature radius of the river bend section and the tributary confluence density; generate a water system safety buffer with gradient attenuation characteristics according to the gradient change among the curvature radius, tributary confluence density and buffer distance; A composite safety constraint layer generation module, identify the building area and the forest protection area from the remote sensing image based on color and shape features; mark the contours of the forest protection area and the building area as the protection red line, and superimpose the spatial positions of the protection red line and the water system safety buffer to generate a composite safety constraint layer; An effective candidate block acquisition module, used to perform spatial exclusion on the area included in the protection red line in the composite safety constraint layer, and extract the initial candidate area with a slope lower than the preset value from the remaining area according to the slope grading mask; Select the continuously connected initial candidate areas from the multiple initial candidate areas, and retain the continuously connected initial candidate areas with an area greater than the first preset threshold as the effective candidate blocks; The target area acquisition module, based on road network data and digital elevation model data, uses the condition that the height difference between two consecutive points is less than or equal to a preset height as a feasible path and the height difference between two consecutive points is greater than the preset height as an obstacle. Through the depth-first search algorithm, it calculates the number of paths from the geometric center of each valid candidate block to the nearest main road, selects the valid candidate block corresponding to the number of paths greater than the preset number and the path length less than the preset distance as the target area, and outputs the position of the target area and the position of its corresponding path; for the path corresponding to each target area, it calculates the comprehensive cost value of the path based on a preset formula, and screens out the target area with the minimum cost value as the optimal site selection; The preset formula is: Among them, represents the path comprehensive cost value, represents the total path length, is the absolute value of the elevation difference of the th segment of the path, represents the standard deviation of the path curvature radius, represents the average curvature radius of the path, is the length weight coefficient, is the elevation change penalty coefficient, is the path curvature penalty coefficient, is the curvature radius of the th bending segment in the path, is the path segmentation index variable, is the bending segment index variable; Mark the position of the target area and the position of its corresponding path on the remote sensing image to obtain a result reference map, and send the result reference map to a preset terminal; After receiving the confirmation from the preset terminal that the result is correct, save the position of the target area and the position of its corresponding path to the final result document.

6. An electronic device, characterized in that, The electronic device includes: a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, it implements the steps corresponding to the method according to any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps corresponding to the method according to any one of claims 1 to 4.

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