Automatic site selection method, system, equipment and medium for natural gas pressure regulating station

Abstract

The invention relates to the technical field of natural gas pressure regulating station automatic site selection, and provides a natural gas pressure regulating station automatic site selection method, system, equipment and medium, and the method comprises the steps: precisely extracting a water system contour boundary through employing an edge detection algorithm, generating a water system distribution diagram, and building a terrain constraint condition through combining with a gradient grading mask; the gradient attenuation range of the water system safety buffer area is dynamically adjusted based on the river channel bending curvature characteristic and the branch intersection density, and water body protection and land use requirements are effectively balanced; recognizing boundaries of a building area and a forest protection area through color and shape features of the remote sensing image, and performing superposition to generate a composite security constraint layer; and screening low-gradient contiguous effective candidate blocks after excluding the protected area, simulating a feasible path through a depth-first search algorithm, and selecting an area which is high in connectivity with a main road and small in topographic relief as a final site. The ecological environment damage risk is reduced, the engineering implementation feasibility is ensured, and the optimal balance of ecological protection, safety protection and construction cost is achieved.

Description

Technical Field

[0001] The present application relates to the field of automatic site selection for natural gas pressure regulating stations, and more specifically, to a method, system, equipment and medium for automatic site selection for natural gas pressure regulating stations. Background Art

[0002] The contents of this section merely provide background information related to the present application and may not constitute prior art.

[0003] In the early days, the site selection of natural gas pressure regulating stations mainly relied on manual experience and industry specifications, and required on-site surveys based on basic parameters such as topography, gas supply radius, and safety spacing. Although this method can guarantee basic safety requirements, it has defects such as low efficiency, poor dynamic adaptability, and inability to quantify and assess environmental risks. In addition, there is no technical solution for automatic site selection of natural gas pressure regulating stations in the existing technology.

[0004] The Chinese patent with the closest announcement number CN108053060B in the prior art discloses a booster station site selection system and site selection method based on automatic line selection of roads within a wind farm. It comprehensively considers the distance, slope, and filling and excavation volume factors that affect the construction cost of wind power construction, automatically realizes the optimal design of the wind farm construction project road, and uses the average shortest distance algorithm to perform intelligent site selection of the booster station. It improves the accuracy of wind power project design, avoids the increase in project costs caused by insufficient experience of designers, reduces the manpower and material costs and time consumption of booster station design in the wind power industry, improves the construction efficiency of wind power projects, improves the design efficiency of wind power booster station projects, and makes the integrated design of wind power projects more flexible, intelligent, and reasonable.

[0005] Although both are automatic site selection for buildings, the 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 easily leads to the site selection being too close to the water body, increasing the risk of floods and also potentially causing adverse effects on the local water ecosystem. Secondly, it does not effectively reduce the risk of ecological environmental damage.

[0006] Therefore, a more scientific, comprehensive and feasible site selection method is urgently needed to meet the actual needs of natural gas pressure regulating stations. Summary of the invention

[0007] In order to solve the above-mentioned technical problems, the purpose of this application is to provide a method, system, equipment and medium for automatic site selection of a natural gas pressure regulating station, improve the accuracy of water system safety protection through dynamic adjustment of the gradient buffer zone, use multi-dimensional spatial superposition to eliminate and reduce the risk of ecological environmental damage, combine terrain and road network analysis to ensure the feasibility of project implementation, achieve the optimal balance between ecological protection, safety protection and construction costs, and significantly improve the efficiency and scientificity of site selection.

[0008] The purpose of this application is achieved through the following technical solutions: In a first aspect, the present invention provides a method for automatic site selection of a natural gas pressure regulating station, comprising: Acquire 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 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 classification mask; Based on the water system distribution map, the contour boundary of the water system network is used as the baseline. According to the curvature radius of the river bend and the tributary intersection density, the buffer zone distance extending outside the water system network along the baseline is calculated; according to the gradient change between the curvature radius, tributary intersection density and buffer zone distance, a water system safety buffer zone with gradient attenuation characteristics is generated; Identify built-up areas and forest reserves from remote sensing images based on color and shape features; mark the outlines of forest reserves and built-up areas as protection red lines, and overlay the protection red lines with the spatial positions of water system safety buffer zones to generate a composite safety constraint layer; The area included in the protection red line in the composite safety constraint layer is spatially excluded, and the initial candidate area with a slope lower than a preset value is extracted in the remaining area according to the slope classification mask; the continuously connected initial candidate area is selected from multiple initial candidate areas, and the continuously connected initial candidate area with an area greater than the first preset threshold is retained as a valid candidate block; Based on road network data and digital elevation model data, a feasible path is defined as one with a height difference between two consecutive points less than or equal to a preset height, and an obstacle is defined as a constraint condition when the height difference between two consecutive points is greater than a preset height. The number of paths from the geometric center of each valid candidate block to the nearest main road is calculated through a depth-first search algorithm. The valid candidate blocks corresponding to the blocks with a number of paths greater than a preset number and a path length less than a preset distance are selected as the target area, and the location of the target area and the location of its corresponding path are output.

[0009] Furthermore, the steps of using edge detection algorithm to identify the contour boundary of the water network on the remote sensing image according to the water body characteristics specifically include: The gradient map is generated by calculating the gradient amplitude of each pixel point of the remote sensing image through the edge detection operator. The gradient threshold range is set based on the spectral characteristics of the sudden drop of the reflectivity of the water body in the visible light band and the near-infrared band. The gradient amplitude threshold determination and spectral reflectance characteristic verification are simultaneously implemented for each pixel point in the gradient map, and the dual-feature pixels that meet both the gradient jump condition and the water body spectral response law are extracted as candidate edge points. The candidate edge pixels are processed by morphological closing operations, and the broken areas are connected and the internal holes are filled through dilation and erosion operations to generate the contour boundary of a continuous and closed water network.

[0010] Furthermore, the step of calculating the buffer zone distance extending outside the water network along the baseline specifically includes: The average curvature of the local river section is calculated based on the curvature radius of the river bend, and the density of tributary confluence nodes within the unit river length is counted; For curved rivers with a curvature radius less than the second preset threshold, the buffer zone extension distance is increased according to a preset ratio. For areas where the tributary intersection density is greater than the preset density, the extension distance is reduced in a decreasing manner to generate a water system safety buffer zone with gradient attenuation characteristics.

[0011] Furthermore, the steps of identifying built-up areas and forest reserves from remote sensing images based on color and shape features specifically include: Extract sub-regions whose greenness index meets the preset index range from the remote sensing image, extract the closed contour of the sub-region using the edge detection algorithm, and calculate the shape complexity index of the closed contour; determine the sub-region whose shape complexity index is greater than the preset index threshold as a forest protection area; Edge detection and polygon fitting are performed on the remote sensing image to screen out closed polygonal areas whose areas are within a preset range and whose shape compactness is higher than a third preset threshold and are determined to be building areas.

[0012] Furthermore, after outputting the position of the target area and the position of the corresponding path, the method further includes: For the path corresponding to each target area, the comprehensive cost value of the path is calculated based on the preset formula, and the target area with the smallest cost value is selected as the optimal address.

[0013] Furthermore, the preset formula is:

[0014] in, Represents the comprehensive cost value of the path, represents the total length of the path, To indicate the path The absolute value of the elevation difference of the segment, represents the standard deviation of the path curvature radius, represents the mean curvature radius of the path, is the length weight coefficient, is the penalty coefficient for elevation change, is the path curvature penalty coefficient, For the path The radius of curvature of the curved segment, is the path segment index variable, The index variable of the curved segment.

[0015] Furthermore, after outputting the position of the target area and the position of the corresponding path, the method further includes: Mark the location of the target area and the location of the corresponding path on the remote sensing image, obtain a result reference map, and send the result reference map to a preset terminal; After receiving the confirmation result from the preset terminal, the location of the target area and the location of its corresponding path are saved in the final result document.

[0016] In a second aspect, the present invention provides a natural gas pressure regulating station automatic site selection system, comprising: The slope classification mask generation module is used to obtain the water system data, road network data, remote sensing images 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, the edge detection algorithm is used to identify the contour boundary of the water system network on the remote sensing image according to the water body characteristics, and the water system distribution map is generated; multiple slope areas are divided according to different slope value ranges to form a slope classification mask; The water system safety buffer zone generation module is based on the water system distribution map, takes the contour boundary of the water system network as the baseline, and calculates the buffer zone distance extending outside the water system network along the baseline according to the curvature radius of the river bend and the tributary intersection density; generates a water system safety buffer zone with gradient attenuation characteristics according to the gradient change between the curvature radius, tributary intersection density and buffer zone distance; The composite safety constraint layer generation module identifies the built-up area and forest protection area from the remote sensing image based on color and shape features; marks the outlines of the forest protection area and the built-up area as the protection red line, and superimposes the protection red line with the spatial position of the water system safety buffer zone to generate a composite safety constraint layer; The valid candidate block acquisition module is used to spatially exclude 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 a preset value in the remaining area according to the slope classification mask; select the continuously connected initial candidate area from multiple initial candidate areas, and retain the continuously connected initial candidate area with an area greater than a first preset threshold as a valid candidate block; The target area acquisition module is based on road network data and digital elevation model data. It takes the height difference between two consecutive points less than or equal to the preset height as a feasible path, and the height difference between two consecutive points greater than the preset height as an obstacle constraint. It calculates the number of paths from the geometric center of each valid candidate block to the nearest main road through a depth-first search algorithm, selects the valid 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 location of the target area and the location of its corresponding path.

[0017] In a third aspect, the present invention provides an electronic device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps corresponding to the method in the first aspect when executing the computer program.

[0018] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps corresponding to the method in the first aspect.

[0019] In summary, the technical solution of the embodiment of the present application has at least the following advantages and beneficial effects: The present invention integrates water system, road, remote sensing image and terrain data, uses edge detection algorithm to accurately extract water system contour boundary to generate water system distribution map, and combines slope classification mask to establish terrain constraint condition; then dynamically adjusts the gradient attenuation range of water system safety buffer zone based on river channel curvature characteristics and tributary intersection density, effectively balancing water body protection and land use demand; identifies the boundary between building area and forest protection area through remote sensing image color and shape characteristics, and superimposes and generates composite safety constraint layer to realize dual protection of ecology and artificial facilities; selects low-slope contiguous effective candidate blocks after excluding protection area, and finally combines road accessibility analysis, simulates feasible paths in digital elevation model through depth-first search algorithm, and gives priority to areas with high connectivity with main roads and small terrain undulation as final site selection. The accuracy of water system safety protection is improved through dynamic adjustment of gradient buffer zone, the risk of ecological environment damage is reduced by multi-dimensional space superposition 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 site selection efficiency and scientificity. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 A flow chart of a method for automatic site selection for a natural gas pressure regulating station provided by the present invention; Figure 2 A schematic diagram of the structure of an automatic site selection system for a natural gas pressure regulating station provided by the present invention; Figure 3 The present invention provides a schematic structural diagram of an electronic device. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations.

[0022] like Figure 1As shown, a method for automatic site selection of a natural gas pressure regulating station proposed in an embodiment of the present application includes: S101, obtaining water system data, road network data, remote sensing images and digital elevation model data of the target area, 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, and generating a water system distribution map; dividing multiple slope areas according to different slope value ranges to form a slope classification mask.

[0023] 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 planning area, the 1:10000 scale water system map is called through the geographic information system, and the 0.5-meter resolution WorldView-3 remote sensing image and 5-meter grid spacing DEM data are loaded at the same time to form a multi-dimensional spatial 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 the slope calculation module. For example, after calculation of a certain hilly area, the slope is divided into three levels: 0-5 degree gentle area, 5-15 degree gentle slope area, and 15-90 degree steep slope area, forming a slope classification mask layer that can be partitioned and identified.

[0024] Furthermore, the steps of using edge detection algorithm to identify the contour boundary of the water network on the remote sensing image according to the water body characteristics specifically include: The gradient map is generated by calculating the gradient amplitude of each pixel point of the remote sensing image through the edge detection operator. The gradient threshold range is set based on the spectral characteristics of the sudden drop of the reflectivity of the water body in the visible light band and the near-infrared band. The gradient amplitude threshold determination and spectral reflectance characteristic verification are simultaneously implemented for each pixel point in the gradient map, and the dual-feature pixels that meet both the gradient jump condition and the water body spectral response law are extracted as candidate edge points. The candidate edge pixels are processed by morphological closing operations, and the broken areas are connected and the internal holes are filled through dilation and erosion operations to generate the contour boundary of a continuous and closed water network.

[0025] Specifically, for the precise extraction of water network, an edge detection algorithm that combines spectral features with morphological features is used. In the specific implementation, the Sobel operator is first used to calculate the gradient amplitude of the remote sensing image. For example, when processing the Landsat8 image of the Taihu Lake Basin, the visible light band (blue, green, and red) and the near-infrared band are jointly analyzed. When it is detected that the reflectivity of a certain pixel point in the green light band is less than 25% and the reflectivity of the near-infrared band drops sharply to less than 5%, the water body spectral response condition is triggered. At the same time, the gradient amplitude of the point is calculated. When the preset threshold is reached (such as the gradient amplitude>120), it is determined that the pixel satisfies both the spectral transition and edge gradient conditions and is marked as a candidate edge point. Through this double verification mechanism, interference areas with similar spectral characteristics such as shadows and asphalt pavement can be effectively excluded.

[0026] When performing morphological optimization on candidate edge points, a combination of closed operations of custom structural elements is used. For example, in the image processing of a certain bay area, in order to address the river boundary breaks caused by cloud cover, a 7×7 circular structural element is used for expansion operations to connect edge segments with a break interval of less than 30 meters; then a 5×5 square structural element is used for corrosion operations to eliminate false protrusions and smooth jagged edges. After this processing, the tributary boundaries of the bay area form complete closed polygons, and the 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, this technical solution improves the accuracy of water system boundary recognition by about 35%, and reduces the error connection rate to less than 3%.

[0027] S102, based on the water system distribution map, taking the contour boundary of the water system network as the baseline, and calculating the buffer zone distance extending outside the water system network along the baseline according to the curvature radius of the river bend and the tributary intersection density; generating a water system safety buffer zone with gradient attenuation characteristics according to the gradient change between the curvature radius, the tributary intersection density and the buffer zone distance; Specifically, first, the center line of the river in the water system distribution map generated in step S1 is used as the baseline, and a multi-parameter coupled buffer calculation model is adopted. For example, when processing a section of the river, the curvature radius distribution of the river section is calculated through GIS tools, and it is found that the average curvature radius of a continuous bend is only 280 meters, which is significantly lower than the preset threshold of 500 meters. At this time, the system automatically triggers the buffer expansion mechanism, and increases the buffer distance of the river section from the base value of 100 meters to 145 meters according to the rule of increasing the buffer distance by 15 meters for every 100-meter reduction in the curvature radius. This design fully takes into account the increased risk of flood scouring caused by the increased curvature of the river, and ensures that the pressure regulating station maintains a safe distance from the unstable river bank.

[0028] Furthermore, the step of calculating the buffer zone distance extending outside the water network along the baseline specifically includes: The average curvature of the local river section is calculated based on the curvature radius of the river bend, and the density of tributary intersection nodes within the unit river length is counted; for curved rivers with a curvature radius less than a second preset threshold, the buffer zone extension distance is increased according to a preset ratio, and the extension distance is reduced in a decreasing manner for areas where the tributary intersection density is greater than the preset density, thereby generating a water system safety buffer zone with gradient attenuation characteristics.

[0029] Specifically, in view of the influence of the hydrological characteristics of tributaries, the system determines the buffer distance correction coefficient through spatial density analysis. For example, in a tributary confluence area, it is calculated that there are 3 tributary confluence points per kilometer of river channel, which exceeds the preset density threshold of 2 / kilometer. At this time, the system starts the decreasing algorithm, and adjusts the original 120-meter basic buffer distance to 104 meters according to the rule of reducing the buffer distance by 8 meters for each additional confluence point. This processing mechanism effectively balances the contradiction between the complexity of hydrological conditions in tributary-dense areas and the efficiency of land resource utilization, and avoids insufficient site selection space due to overly conservative buffer zone settings.

[0030] When comprehensively dealing with the synergistic effect of the curvature radius and the tributary density, the system uses a gradient attenuation model to achieve a smooth transition of the buffer distance. For example, in a certain river section, a curvature radius of 400 meters in a certain curved section triggers an increase in the buffer distance to 112 meters, while the area also has a tributary intersection density of 2.5 / km, triggering a reduction in the buffer distance of 10 meters. After superposition calculation, the buffer distance of the area was finally determined to be 102 meters. This dynamic adjustment mechanism allows the buffer zone boundary to form a natural gradient effect, which not only maintains the hydrological safety requirements, but also optimizes the continuity and availability of the site selection area.

[0031] S103, identifying the built-up area and the forest protection area from the remote sensing image based on color and shape features; marking the outlines of the forest protection area and the built-up area as protection red lines, superimposing the protection red lines with the spatial positions of the water system safety buffer zone, and generating a composite safety constraint layer; Specifically, sub-regions whose greenness index meets the preset index range are extracted from remote sensing images, and the closed contours of the sub-regions are extracted using the edge detection algorithm, and the shape complexity index of the closed contours is calculated; sub-regions whose shape complexity index is greater than the preset index threshold are determined as forest reserves. That is, forest reserves are first extracted based on vegetation spectral characteristics and morphological analysis. The system calculates the normalized vegetation index (NDVI) from remote sensing images and screens vegetation coverage areas with greenness values ​​between 0.3 and 0.8. For example, in the identification of nature reserves, the NDVI of the red band (B4) and near-infrared band (B8) of Sentinel-2 images (Sentinel-2 Satellite Imagery) is calculated, and 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 calculate the shape complexity index (SC=perimeter² / (4π×area)). When the SC value exceeds 1.5, it is determined to be a natural forest area morphological feature. Taking a certain area as an example, the SC value of natural forest patches reached 2.3, significantly higher than 1.1 of artificial nurseries, thus accurately distinguishing the boundaries of the original forest that needs to be protected.

[0032] For the identification of built-up areas, edge detection and polygon fitting are performed on remote sensing images to screen out closed polygonal areas with an area within a preset range and a shape compactness higher than the third preset threshold, and determine them as built-up 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 (CI) of each polygon is calculated. For example, in the processing of urban areas, the CI value of the financial district buildings within it is generally higher than 0.7, while the CI value of natural bare land is lower than 0.3. After setting the CI threshold of 0.6, high-rise building clusters can be effectively screened out. At the same time, combined with the area filtering mechanism, scattered structures with an area of ​​less than 5,000 square meters are excluded. For example, in the analysis of an industrial park, the system accurately identified a business building complex with an area of ​​12 hectares and a CI value of 0.78 on the west side of a lake, while excluding a temporary shed with an area of ​​only 800 square meters from the protection red line. After completing the identification of the two types of areas, the system automatically marks the forest protection boundary and the building area outline as the protection red line layer.

[0033] S104, spatially exclude 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 a preset value in the remaining area according to the slope classification mask; select continuously connected initial candidate areas from multiple initial candidate areas, and retain the continuously connected initial candidate areas with an area greater than a first preset threshold as valid candidate blocks.

[0034] Specifically, the system performs an "erase" operation on the area covered by the protection red line, and removes all areas that have spatial intersections with the protection red line from the entire target area. After completing the spatial exclusion, the system loads the slope classification mask layer generated in step S1 to extract the initial candidate areas with slope values ​​lower than the preset threshold. The slope threshold is set according to the construction specifications of the voltage regulating station, and the ground slope of the station is usually required to be no more than 8%. During implementation, the system merges the areas marked as "flat area" (0-5 degrees) and "gentle slope area" (5-15 degrees) in the slope classification mask, and then screens out sub-areas with a slope ≤8% through reclassification operations.

[0035] Next, the system performs connectivity analysis on the initial candidate regions. A morphological closing algorithm is used to spatially connect discrete candidate regions, including: using a circular structure element to dilate the region edge to bridge adjacent regions, and then using the same size structure element to erode to restore the original geometric features. This process can merge independent regions with a spacing smaller than the structure element radius into a continuous connected body.

[0036] 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 based on the minimum land demand of the voltage regulating station, usually set to 1 hectare. During implementation, the system automatically removes scattered areas with an area smaller than the threshold and retains valid candidate blocks that meet the conditions for large-scale development. This mechanism effectively avoids the problem of fragmented site selection caused by terrain fragmentation and ensures that the candidate blocks have actual engineering feasibility.

[0037] S105, based on the road network data and the digital elevation model data, taking the height difference between two consecutive points less than or equal to the preset height as a feasible path, and taking the height difference between two consecutive points greater than the preset height as an obstacle constraint, calculate the number of paths from the geometric center of each valid candidate block to the nearest main road through a depth-first search algorithm, select the valid 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 output the location of the target area and the location of its corresponding path.

[0038] Specifically, the system first establishes a path accessibility model under the constraints of terrain undulation, and uses the height difference between continuous path nodes as the criterion for passability. 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 to be a passable path segment; otherwise, it is regarded as a terrain obstacle and the path is prohibited from crossing. This constraint condition effectively simulates the actual restrictions of engineering vehicles and pipeline laying on the ground slope, avoiding the selection of construction difficult areas caused by steep terrain.

[0039] The system then uses a depth-first search algorithm to traverse all potential paths from each valid candidate block to the nearest trunk road. The algorithm starts from the geometric center of the candidate block, radiates along eight directions, recursively visits each adjacent grid point and accumulates the path length. When the search reaches the edge of any trunk road, the path is recorded as a valid connected route. Through an exhaustive search strategy, the algorithm can fully detect the terrain features around the block to ensure that no potential paths are missed.

[0040] After completing the path search, the system implements a comprehensive screening of multiple indicators: first, the number of valid paths in each block is counted, and the preset minimum number of connected paths (such as ≥2) is required to ensure that the project access has redundancy protection; secondly, the path length is screened not to exceed the preset maximum distance threshold (such as 5 kilometers) to control the cost of pipeline construction. For example, in the evaluation of a candidate block, the system detected that there were three independent paths in the block: two 4.3-kilometer paths connecting Provincial Road S306, and one 3.1-kilometer path connecting Township Road Y045. Because the number of paths (3) exceeded the preset threshold (2) and the maximum path length (4.3 kilometers) was less than the 5-kilometer limit, the block was retained as a qualified target area. In contrast, in another block, although two paths were detected, the lengths were 5.8 kilometers and 6.2 kilometers respectively, and they were automatically eliminated by the system because they exceeded the length threshold.

[0041] Furthermore, after outputting the position of the target area and the position of the corresponding path, the method further includes: For the path corresponding to each target area, the comprehensive cost value of the path is calculated based on the preset formula, and the target area with the smallest cost value is selected as the optimal address.

[0042] The preset formula is:

[0043] in, Represents the comprehensive cost value of the path, represents the total length of the path, To indicate the path The absolute value of the elevation difference of the segment, represents the standard deviation of the path curvature radius, represents the mean curvature radius of the path, is the length weight coefficient, is the penalty coefficient for elevation change, is the path curvature penalty coefficient, For the path The radius of curvature of the curved segment, is the path segment index variable, The index variable of the curved segment.

[0044] Furthermore, after outputting the position of the target area and the position of the corresponding path, the method further includes: The position of the target area and the position of the corresponding path are marked on the remote sensing image, a result reference map is obtained, and the result reference map is sent to a preset terminal.

[0045] Specifically, after completing the path accessibility screening of the valid candidate blocks, the system integrates the site selection results of the target area with the corresponding connection paths for spatial visualization. That is, the spatial overlay function of the geographic information system is called to overlay the geometric center coordinates of the target area and the spatial trajectory of its connection path determined in step S5 onto the original high-resolution remote sensing image base map in the form of a vector layer. Through the preset legend symbol library, the target area is represented by a red semi-transparent polygon fill, and the path is marked with a yellow dotted line, forming an intuitive result reference map.

[0046] After receiving the confirmation result from the preset terminal, the location of the target area and the location of its corresponding path are saved in the final result document.

[0047] Specifically, after the preset terminal receives the result, the engineer conducts multi-dimensional verification through the human-computer interaction interface: first, check whether the target block completely avoids the water system buffer zone and the protection red line, and secondly, confirm whether the path direction reasonably avoids steep slope obstacles. When the need for manual correction is detected, the engineer can adjust the boundary of the target area or re-plan the path by circling, and the modified data is transmitted back to the system for secondary calculation via the encryption protocol. When the terminal confirms that the result is correct, the system will store the target area coordinates and its path topology data persistently in the final result document. The storage format uses the GeoPackage binary file of the Open Geospatial Consortium (OGC) standard.

[0048] Based on the same inventive concept, the present invention provides an automatic site selection system for a natural gas pressure regulating station, comprising: The slope classification mask generation module 201 is used 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, an edge detection algorithm is used to identify the contour boundary of the water system network on the remote sensing image according to the water body characteristics, and a water system distribution map is generated; a plurality of slope areas are divided according to different slope value ranges to form a slope classification mask; The water system safety buffer zone generation module 202 is based on the water system distribution map, takes the contour boundary of the water system network as the baseline, and calculates the buffer zone distance extending outside the water system network along the baseline according to the curvature radius of the river bend and the tributary intersection density; generates a water system safety buffer zone with a gradient attenuation feature according to the gradient change between the curvature radius, the tributary intersection density and the buffer zone distance; 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 outlines of the forest protection area and the built-up area as protection red lines, and superimposes the protection red lines with the spatial positions of the water system safety buffer zone to generate a composite safety constraint layer; The valid candidate block acquisition module 204 is used to spatially exclude 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 a preset value in the remaining area according to the slope classification mask; select the continuously connected initial candidate area from the multiple initial candidate areas, and retain the continuously connected initial candidate area with an area greater than the first preset threshold as the valid candidate block; The target area acquisition module 205, 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 a feasible path, and takes the height difference between two consecutive points greater than the preset height as an obstacle constraint condition, calculates the number of paths from the geometric center of each valid candidate block to the nearest main road through a depth-first search algorithm, selects the valid 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 location of the target area and the location of its corresponding path.

[0049] 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 in the memory 302 and executable on the processor 301. When the processor 301 executes the computer program, a method for automatic site selection of a natural gas pressure regulating station is implemented.

[0050] Based on the same inventive concept, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a method for automatic site selection for a natural gas pressure regulating station.

[0051] The above are only preferred embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. 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. A method for automatic site selection of a natural gas pressure regulating station, characterized in that: include: Acquire 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 water body characteristics, and generate a water system distribution map; divide multiple slope areas according to different slope value ranges to form a slope classification mask; Based on the water system distribution map, taking the outline boundary of the water system network as the baseline, according to the curvature radius of the river bend and the tributary intersection density, the buffer zone distance extending outside the water system network along the baseline is calculated; according to the gradient change between the curvature radius, the tributary intersection density and the buffer zone distance, a water system safety buffer zone with gradient attenuation characteristics is generated; Identify the built-up area and the 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 protection red lines with the spatial position of the water system safety buffer zone to generate a composite safety constraint layer; The area included in the protection red line in the composite safety constraint layer is spatially excluded, and the initial candidate area with a slope lower than the preset value is extracted in the remaining area according to the slope classification mask; Selecting continuously connected initial candidate regions from the multiple initial candidate regions, and retaining continuously connected initial candidate regions with an area greater than a first preset threshold as valid candidate blocks; Based on road network data and digital elevation model data, a feasible path is defined as one with a height difference between two consecutive points less than or equal to a preset height, and an obstacle is defined as a constraint condition when the height difference between two consecutive points is greater than a preset height. The number of paths from the geometric center of each valid candidate block to the nearest main road is calculated through a depth-first search algorithm. The valid candidate blocks corresponding to the blocks with a number of paths greater than a preset number and a path length less than a preset distance are selected as target areas, and the position of the target area and the corresponding path are output.

2. The method for automatic site selection of a natural gas pressure regulating station according to claim 1, characterized in that: The step of using an edge detection algorithm to identify the contour boundary of the water network on the remote sensing image according to water body characteristics specifically includes: The gradient map is generated by calculating the gradient amplitude of each pixel point of the remote sensing image through the edge detection operator. The gradient threshold range is set based on the spectral characteristics of the sudden drop of the reflectivity of the water body in the visible light band and the near-infrared band. The gradient amplitude threshold determination and spectral reflectance characteristic verification are simultaneously implemented for each pixel point in the gradient map, and the dual-feature pixels that meet both the gradient jump condition and the water body spectral response law are extracted as candidate edge points. The candidate edge pixels are subjected to morphological closing operations, and the broken areas are connected and the internal holes are filled through dilation and erosion operations to generate the contour boundary of a continuous and closed water network.

3. The method for automatic site selection of a natural gas pressure regulating station according to claim 1, characterized in that: The step of calculating the buffer zone distance extending outside the water network along the baseline specifically includes: The average curvature of the local river section is calculated based on the curvature radius of the river bend, and the density of tributary confluence nodes within the unit river length is counted; For curved rivers with a curvature radius less than the second preset threshold, the buffer zone extension distance is increased according to a preset ratio. For areas where the tributary intersection density is greater than the preset density, the extension distance is reduced in a decreasing manner to generate a water system safety buffer zone with gradient attenuation characteristics.

4. The method for automatic site selection of a natural gas pressure regulating station according to claim 1, characterized in that: The step of identifying the built-up area and the forest protection area from the remote sensing image based on color and shape features specifically includes: Extracting a sub-region whose greenness index satisfies a preset index range from the remote sensing image, extracting a closed contour of the sub-region using an edge detection algorithm, and calculating a shape complexity index of the closed contour; determining a sub-region whose shape complexity index is greater than a preset index threshold as a forest reserve; Edge detection and polygon fitting are performed on the remote sensing image to screen out closed polygonal areas whose areas are within a preset range and whose shape compactness is higher than a third preset threshold and are determined to be building areas.

5. The method for automatic site selection of a natural gas pressure regulating station according to claim 1, characterized in that After outputting the position of the target area and the position of the path corresponding to the target area, the method further includes: For the path corresponding to each target area, the comprehensive cost value of the path is calculated based on the preset formula, and the target area with the smallest cost value is selected as the optimal address.

6. A method for automatic site selection of a natural gas pressure regulating station according to claim 5, characterized in that: The preset formula is: in, Represents the comprehensive cost value of the path, represents the total length of the path, To indicate the path The absolute value of the elevation difference of the segment, represents the standard deviation of the path curvature radius, represents the mean curvature radius of the path, is the length weight coefficient, is the penalty coefficient for elevation change, is the path curvature penalty coefficient, For the path The radius of curvature of the curved segment, is the path segment index variable, The index variable of the curved segment.

7. The method for automatic site selection of a natural gas pressure regulating station according to claim 1, characterized in that: After outputting the position of the target area and the position of the path corresponding to the target area, the method further includes: Marking the position of the target area and the position of the corresponding path on the remote sensing image, obtaining a result reference map, and sending the result reference map to a preset terminal; After receiving the confirmation result from the preset terminal, the location of the target area and the location of the corresponding path are saved in the final result document.

8. A natural gas pressure regulating station automatic site selection system, characterized in that: include: The slope classification mask generation module is used 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, an edge detection algorithm is used to identify the contour boundary of the water system network on the remote sensing image according to the water body characteristics, and a water system distribution map is generated; a plurality of slope areas are divided according to different slope value ranges to form a slope classification mask; A water system safety buffer zone generation module is based on the water system distribution map, takes the contour boundary of the water system network as a baseline, calculates the buffer zone distance extending outside the water system network along the baseline according to the curvature radius of the river bend and the tributary intersection density; generates a water system safety buffer zone with a gradient attenuation feature according to the gradient change between the curvature radius, the tributary intersection density and the buffer zone distance; A composite safety constraint layer generation module is used to identify the built-up area and the forest protection area from the remote sensing image based on color and shape features; the outlines of the forest protection area and the built-up area are marked as protection red lines, and the protection red lines are superimposed with the spatial position of the water system safety buffer zone to generate a composite safety constraint layer; The valid candidate block acquisition module is used to spatially exclude 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 classification mask; Selecting continuously connected initial candidate regions from the multiple initial candidate regions, and retaining continuously connected initial candidate regions with an area greater than a first preset threshold as valid candidate blocks; The target area acquisition module is based on road network data and digital elevation model data. It takes the height difference between two consecutive points less than or equal to the preset height as a feasible path, and the height difference between two consecutive points greater than the preset height as an obstacle constraint. It calculates the number of paths from the geometric center of each valid candidate block to the nearest main road through a depth-first search algorithm, selects the valid 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.

9. An electronic device, characterized in that: The electronic device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps corresponding to the method according to any one of claims 1 to 7 when executing the computer program.

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

Images