A GIS-based method for dividing a gas pipeline passing area into regions and grades

Abstract

The present application relates to gas pipeline engineering design technical field, disclose a kind of based on GIS's gas pipeline passing area area grade division method, obtain the data set of the information of building along pipeline path and its, rely on geographic information system, generate buffer zone and determine building effective vertex and its projection point projected to pipeline path;Recycling dynamic step sliding window mode, determine all sliding windows with any end of pipeline and projection point as the starting point of sliding window;Cyclically filter the target sliding window of the maximum preset index in all sliding windows, adopt the sliding window iteration expansion and distal projection point cross adjustment mode based on index driving, update the boundary and preset index of the target sliding window to complete this regional division;According to area grade division rule, grade is determined using pipeline path each area regional division data and its basic data.It realizes the intelligent division of gas pipeline area grade.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of gas pipeline engineering design, and particularly relates to a GIS-based gas pipeline passing area region grade division method. BACKGROUND

[0002] Once a gas transmission pipeline leaks, it is easy to cause fire, explosion and other accidents, which seriously threatens public safety and the ecological environment. According to the GB 50251-2015 Gas Transmission Pipeline Engineering Design Specification, the region along the pipeline should be divided into grades according to the residential density, and the key design parameters such as pipe material selection, wall thickness, corrosion grade, etc. should be determined accordingly.

[0003] At present, the region grade division mainly relies on manual recognition method, that is, the residential distribution along the line is preliminarily judged through public images, and then confirmed by personnel on-site review. The whole process is time-consuming and inefficient, and it often takes more than a month to divide a 10-kilometer pipeline, which cannot meet the needs of rapid construction and dynamic management. In addition, this method is greatly influenced by subjective experience, and is easy to miss or misjudge, especially in complex areas such as urban and rural junctions and temporary construction areas. The number of residential households is not accurate, which leads to distortion of region grade division. Even with the help of unmanned aerial vehicle aerial photography, a large amount of manual interpretation is still needed, and automatic processing cannot be realized. There is a lack of systematic solution based on multi-source remote sensing data and intelligent analysis algorithm in the prior art, which makes it difficult to realize high-precision, high-efficiency and updatable dynamic identification of region grade, and cannot meet the development needs of modern gas pipeline intelligent and fine management, which restricts the improvement of pipeline intrinsic safety level. SUMMARY

[0004] The present application aims to provide a GIS-based gas pipeline passing area region grade division method to solve the technical problem of the lack of systematic solution based on multi-source remote sensing data and intelligent analysis algorithm.

[0005] The basic scheme provided by the present application is: a GIS-based gas pipeline passing area region grade division method, comprising:

[0006] S1, acquiring a multi-source data set representing the pipeline path and the building information along the pipeline, and generating a buffer zone based on a geographic information system, and synchronously determining the effective vertex of the building and the projection point of the projection of the building to the pipeline path;

[0007] S2, determining all sliding windows with any end of the pipeline and each projection point as the starting point of the sliding window by using a dynamic step sliding window method;

[0008] S3, screening all sliding windows to find the target sliding window with the maximum preset index, adopting the sliding window iteration expansion and far end projection point cross adjustment mode based on the index driving, updating the boundary and preset index of the target sliding window, completing the regional division and determining the regional division data and the basic data thereof; repeating S2-S3 on the pipeline path without regional division until all regional divisions of the pipeline path are completed;

[0009] S5, determining the level according to the regional level division rule and using the regional division data and the basic data thereof.

[0010] The working principle and advantages of the present application are as follows:

[0011] The present application provides accurate basic data sources for subsequent regional level division based on the reasonable fusion of multi-source data; constructs a regional level division mechanism based on the cooperation of three modes of building vertex projection, dynamic step sliding window, sliding window expansion and far end projection point cross adjustment, which is more in line with the engineering requirements of accurate, efficient and low-cost landing of gas pipeline regional level division, and breaks through in the three dimensions of data source accuracy, spatial division flexibility and calculation logic lightweight.

[0012] The cooperative region division mechanism constructed by the application has the following advantages: 1) the effective vertex screening strategy can effectively exclude invalid building vertices outside the buffer zone, avoid the misinclusion of buildings outside the buffer zone into statistics, and ensure the spatial effectiveness of the basic data, thereby improving the division accuracy from the data source; 2) the projection point of the building vertex is accurately positioned to identify the accurate intersection position of the building and the buffer zone, and provide accurate spatial anchor points for the dynamic step; 3) the dynamic step sliding window method is introduced, and the pipeline endpoint and each projection point are used as the sliding starting point, so that the redundant sliding of the area without buildings is avoided, the problem of low efficiency of the fixed step is solved, and the calculation is lightened; for example, in a 1km empty area between two projection points, the existing fixed step technology (such as sliding once every 1m) will cause 1000 times of invalid sliding, while the method only needs to slide once at the front projection point with a reasonable step, which significantly reduces the calculation amount and improves the efficiency; 4) the sliding window iteration expansion and far-end projection point intersection adjustment method based on index driving is adopted, the far-end projection point of the building quadrilateral is used as the boundary anchor point to realize the accurate alignment of the division boundary and the actual outline of the building, and the spatial details such as local cutting and critical entry of the building are effectively captured; combined with the iteration window expansion mechanism driven by the index, the division of the region dynamically responds to the change of the building density, automatically iterates and expands in the dense area to subdivide the region, and efficiently slides in the sparse area; finally, the boundary is expanded by a small distance to ensure compliance, and the local geometry and functional characteristics in the complex environment are fully retained, which can completely cover large building groups across multiple original fixed windows, avoids the problem of forced cutting of building areas by the fixed step of the existing technology, and significantly improves the fineness and accuracy of the division result.

[0013] The application relies on a GIS system, generates a buffer zone combined with gas pipeline path data, reduces invalid analysis areas, and makes the analysis area more consistent with the actual risk distribution, thereby avoiding the omission of high-risk area coverage and reducing the redundant calculation of low-risk areas, and improving the accuracy and efficiency of spatial analysis.

[0014] The application introduces unmanned aerial vehicle image data in the multi-source data and fuses it with the gas pipeline path data. The unmanned aerial vehicle image data has the characteristics of high resolution, strong real-time performance and flexible coverage range. The unmanned aerial vehicle can quickly obtain the latest spatial form (such as building height, land area and appearance structure) and position change of the buildings around the pipeline during the flight task, which makes up for the defects of the lagging update and insufficient details of the traditional GIS map; meanwhile, through the association with the pipeline path data, the dynamic matching of the spatial relationship between the pipeline and the building is realized, which provides more comprehensive and accurate basic data support for subsequent regional grade division. The application breaks through the limitation of relying on single or traditional data source in the prior art, and solves the problem of misjudgment of regional grade caused by data lagging or deficiency in the prior art (such as omission of newly-built high-risk building group). BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 A flowchart of a GIS-based gas pipeline path area region grade division method provided by an embodiment of the present application is shown in FIG. 1.

[0016] Figure 2 A building vertex data and pipeline building number data calculation flowchart provided by an embodiment of the present application is shown in FIG. 2. Figure One ;

[0017] Figure 3 A building vertex data and pipeline building number data calculation flowchart provided by an embodiment of the present application is shown in FIG. 2. Figure Two ;

[0018] Figure 4 A gas pipeline path area region division data and region grade determination calculation flowchart provided by an embodiment of the present application is shown in FIG. 3.

[0019] Figure 5 An effective point calculation flowchart provided by an embodiment of the present application is shown in FIG. 4.

[0020] Figure 6 A region grade determination flowchart provided by an embodiment of the present application is shown in FIG. 5.

[0021] Figure 7 A number diagram provided by an embodiment of the present application is shown in FIG. 6.

[0022] Figure 8 A sliding window determination diagram provided by an embodiment of the present application is shown in FIG. 7.

[0023] Figure 9 A sliding window expansion diagram provided by an embodiment of the present application is shown in FIG. 8. Figure One ;

[0024] Figure 10 A sliding window expansion diagram provided by an embodiment of the present application is shown in FIG. 8. Figure Two ;

[0025] Figure 11 A sliding window expansion diagram provided by an embodiment of the present application is shown in FIG. 8. Figure Three ;

[0026] Figure 12 A sliding window expansion diagram provided by an embodiment of the present application is shown in FIG. 8. Figure Four ;

[0027] Figure 13 A sliding window expansion diagram provided by an embodiment of the present application is shown in FIG. 8. Figure Five ;

[0028] Figure 14 A sliding window expansion diagram provided by an embodiment of the present application is shown in FIG. 8. Figure Six ;

[0029] Figure 15 A schematic diagram of a GIS-based regional classification system for gas pipeline routes provided in this embodiment of the invention. Figure One ;

[0030] Figure 16 A schematic diagram of a GIS-based regional classification system for gas pipeline routes provided in this embodiment of the invention. Figure Two .

[0031] The markings in the accompanying drawings include: 1. Pipeline centerline; 2. Buffer zone boundary line; 3. Sliding window boundary line one; 4. Expansion line one; 5. Building; 6. Sliding window boundary line two; 7. Expansion line two; 8. Final boundary line of the sliding window. Detailed Implementation

[0032] The following detailed description illustrates the specific implementation method:

[0033] The basic implementation examples are as follows: Figure 1 As shown: A GIS-based method for classifying the regional hierarchy of gas pipeline routes, including:

[0034] S1: Obtain a multi-source dataset representing the pipeline path and the information of buildings along the path, and generate a buffer based on the geographic information system to simultaneously determine the effective vertices of buildings and their projection points onto the pipeline path.

[0035] Specifically, this includes:

[0036] S11, acquire gas pipeline path data and UAV imagery data collected along the pipeline path;

[0037] Gas pipeline route data (file): Coordinate data of the gas pipeline route in the design or construction. Since the pipeline is straight between two bends, the pipeline data mainly consists of the node coordinate information of each bend; the straight pipeline between two adjacent bends is used as the node segment.

[0038] The UAV imagery data includes UAV orthophoto TIFF data, TIFF image coordinate information, UAV additional data, and information on special buildings.

[0039] UAV orthophoto TIFF data (file): Tag Image File Format, which is a bitmap format file. This format is commonly used for image files generated when a UAV takes orthophotos.

[0040] TIFF image coordinate information (text file): TFW format (TIFF World File) file. This file is generated simultaneously when the orthophoto is taken by the UAV and the TIFF format file is generated. It defines the affine relationship between the image pixel coordinates and the actual geographic coordinates.

[0041] UAV additional data: the data of building height, floor area, appearance structure and other data of buildings along the pipeline path area collected and analyzed by the UAV when performing the flight task.

[0042] Special building information: a file recording special building information related to gas pipeline integrity, including but not limited to four-story and above four-story building information, gas station, oil depot, school, hospital, nursery, nursing home, prison, shopping mall, market, temple, sports field, square, entertainment and leisure place, theater, campsite, etc. In this embodiment, the special building information is calculated by the UAV additional data. In other embodiments, the special building information is obtained by a third-party map API, and can also be obtained by manual annotation.

[0043] Residential space distribution: the number of buildings in a certain area. In this embodiment, the data is calculated according to the UAV image by the method. In the prior art, the data is obtained by manual visit in the research stage of pipeline design.

[0044] S12, using the gas pipeline path data and the UAV image data, identifying and processing to obtain the building vertex data in the geodetic coordinate system around the pipeline path and the pipeline building number data.

[0045] Specifically, as shown in Figure 2 and Figure 3

[0046] In S12, the process of obtaining the building vertex data includes:

[0047] The UAV image data includes UAV orthophoto TIFF data and TIFF image coordinate information;

[0048] The building vertex pixel coordinate data is obtained by identifying and processing the UAV orthophoto TIFF data (file) using image recognition technology;

[0049] The building vertex pixel coordinate data is converted to building vertex data in the geodetic coordinate system by affine transformation combined with the actual geographic coordinates in the TIFF image coordinate information (text file).

[0050] The affine transformation formula is:

[0051]

[0052] wherein, is the geographic X coordinate corresponding to the pixel; is the geographic Y coordinate corresponding to the pixel; is the pixel coordinate (column number); ​Pixel coordinate (row number) ；A Pixel resolution in X direction; D Pixel resolution in Y direction; B Rotation factor; E Pixel resolution in Y direction; C X coordinate of the center of the top-left pixel of the original raster image; F Y coordinate of the center of the top-left pixel of the original raster image. The pixel coordinates after conversion will be converted to CGCS2000 coordinate system coordinates.

[0053] In S12, the process of obtaining pipeline building number data includes the following, as shown in Figure 7

[0054] Each building is represented by a quadrilateral, and the buildings are numbered from 1 to F (e.g., J1, J2…Jf…JF are buildings numbered 1, 2…f…F, respectively).

[0055] One building corresponds to four building vertices, and the building vertices are numbered from 1 to N, for example, the four building vertices of J1 are numbered 1, 2, 3, and 4 (as shown by d1, d2, d3, and d4), and the corresponding projection points are t1, t2, t3, and t4; the four building vertices of J2 are numbered 5, 6, 7, and 8 (as shown by d5, d6, d7, and d8), and so on.

[0056] Take any end of the pipeline (e.g., D1) as the starting point, number the pipeline bending nodes from 1 to G, and number the node segments from 1 to H. There are multiple bending points on the pipeline center line 1, such as w1, w2…wg…wG, which are numbered 1, 2…g…G, respectively. The straight pipeline segment between two adjacent bending points is a node segment, such as JDD1, JDD2…JDDh…JDDH, which are numbered 1, 2…h…H, respectively. The node segment is associated with the numbering of its adjacent two bending points.

[0057] Subsequently, the building vertices are associated with buffer zone, regional area, and other information.

[0058] The pipeline building number data is introduced, and a unique identifier is assigned to each pipeline surrounding building, and is bound with the gas pipeline path data and building vertex data, forming a data management mode of one building per file, realizing accurate traceability and dynamic management of building data. In subsequent regional level adjustment (e.g., building function from ordinary residence to commercial complex, population density improvement requires level adjustment) or accident traceability (e.g., safety hazards in the pipeline around a building can quickly locate the building-related data), target building information can be efficiently retrieved, greatly improving the convenience and decision-making efficiency of data application.

[0059] ​S13, based on the gas pipeline path data, the building vertex data and the pipeline building number data, generating a buffer zone and determining effective vertices and projection points of the effective vertices projected to a pipeline center line representing the gas pipeline path based on a relationship between the buffer zone and the building vertices.

[0060] Specifically, as shown in Figure 4

[0061] Because the earth is an ellipsoid, and the altitude of the area through which the gas pipeline passes is constantly changing, the straight-line distance cannot be directly calculated using the Euclidean distance formula. In particular, in mountainous areas where the terrain is more complex, if only the planar straight-line distance is used, the calculation result may be quite different from the actual distance. The geographic information system (Geographic Information System or Geo-Information system, GIS) can perform spatial calculations taking into account altitude information, for example, the GIS software PostGIS spatial function calculates the distance between two points in the CGCS2000 latitude and longitude geographic coordinate system more accurately, so the present application uses GIS software to calculate the distance to improve the accuracy of data calculation.

[0062] In S13, the process of generating the buffer zone includes:

[0063] According to the gas pipeline path data, there are multiple bending points on the pipeline center line, and the straight-line pipeline segment between two adjacent bending points is a node segment; the buffer zone includes two end sub-buffer zones of the pipeline, each straight-line pipeline segment sub-buffer zone and each bending point sub-buffer zone; the outer edges of all sub-buffer zones are continuously transitioned, and the envelope area formed by the outer edges is the buffer zone.

[0064] Specifically, using the geographic information system, taking each straight-line pipeline segment center line as the center line, a belt-shaped area is formed by vertically extending to both sides by a fourth preset distance, and the belt-shaped area is used as each straight-line pipeline segment sub-buffer zone;

[0065] Taking each bending point as the center and the fourth preset distance as the radius, an arc-shaped area is constructed to connect adjacent belt-shaped areas, and the arc-shaped area is used as each bending point sub-buffer zone;

[0066] Taking each bending point as the center and the fourth preset distance as the radius, an arc-shaped area is constructed to connect adjacent belt-shaped areas, and the arc-shaped area is used as each bending point sub-buffer zone;

[0067] The outer edges of all belt-shaped areas, arc-shaped areas and semicircular areas are continuously transitioned, and the envelope area formed by the outer edges is the buffer zone.

[0068] ​The geographic information system (GIS) can be PostGIS or QGIS. According to the GB 50251-2015 Gas Pipeline Engineering Design Code, the fourth preset distance is 200 meters, thus the total width of the strip area is 400 meters. Constructing an arc-shaped area at the bend is to avoid calculation errors caused by blank areas. This can be achieved by using the "offset curve" or "buffer segmentation" techniques in the GIS software, such as setting the "rounded corners" parameter in QGIS's buffer tool to construct the arc-shaped area.

[0069] In S13, the process of determining whether a building vertex contained in the buffer is a valid vertex includes:

[0070] Based on the gas pipeline route data, there are multiple bends along the pipeline centerline. The straight pipeline segments between two adjacent bends are node segments. Based on the building vertex data and pipeline building number data, the traversal starts from the first vertex and the first node segment:

[0071] Based on the relationship between the distance between the vertex and the two endpoints of the node segment and the buffer, the first determination of the valid vertex is performed;

[0072] For each node segment, construct a right-angled triangle within the buffer zone. Compare the length of the hypotenuse of the right-angled triangle with the distance between the vertex and the two endpoints of the node segment to perform a second judgment on the valid vertices.

[0073] Based on the relationship between the vertical distance between the vertex and the node segment and the buffer, a third determination of the valid vertex is made;

[0074] Each time the condition is met, the process returns to the first check of the next vertex or the next node segment; finally, the check of whether all building vertices are valid vertices is completed.

[0075] Specific examples Figure 5 As shown:

[0076] Step 1: Calculate the distances L1 and L2 between the nth building vertex and the two endpoints of the hth node segment; these two distances are calculated as the distances between points in space.

[0077] Step 2 (first judgment): If Min(L1, L2) ≤ the first preset distance (200 meters), then record the vertex as a valid vertex and return to step 1 to calculate the (n+1)th vertex; otherwise, go to step 3.

[0078] Step 3, calculate the length L3 of the h-th node segment;

[0079] Step 4, calculate the reference length L4:

[0080]

[0081] According to the node segment length L3 and the pipeline center line extending the first preset distance 200 meters according to the specification requirements, L4 is calculated, and the principle is to calculate the length of the hypotenuse according to the two straight sides of the right triangle.

[0082] Step 5 (second judgment), if Max (L1, L2) > L4, then ignore the node segment and return to step 1 to calculate the h+1 node segment; otherwise, go to step 6;

[0083] Step 6, calculate the vertical distance L5 of the vertex and the node segment;

[0084] After the previous steps, if the vertex is not recorded as a valid point and is not ignored, it can be judged that the vertex is located in the vertical area of the node segment, and the vertical point of the vertex will not be located on the extension line of the node segment. The calculated vertical distance is the distance of the vertex from the node segment, so it can be judged whether the vertex is located in the buffer area.

[0085] Step 7 (third judgment): if L5 > the first preset distance (200 meters), then ignore the node segment and return to step 1 to calculate the h+1 node segment; otherwise, record the vertex as a valid vertex and return to step 1 to calculate the n+1 vertex;

[0086] Step 8, repeat steps 1-7 until all vertices are traversed, and obtain the set of valid vertices;

[0087] Step 9, store each valid vertex and its corresponding building quadrilateral, that is, build a correspondence between valid vertices and building quadrilaterals. Each building quadrilateral corresponds to at least one valid vertex, that is, as long as the building quadrilateral has a valid vertex, it is considered that the building quadrilateral is located in the buffer area, which is used for subsequent household number statistics.

[0088] In S13, the projection point determination process of the valid vertex projected to the pipeline path includes:

[0089] The nearest point algorithm from the point to the pipeline center line is used to calculate the orthogonal projection position of the valid vertex on the pipeline center line; when the valid vertex is projected to the pipeline center line, the projection point on the pipeline center line is taken as the final projection point; when the valid vertex is projected to the extension line of the pipeline center line, the nearest bending point in the region of the valid vertex is taken as the projection point.

[0090] There are two cases here, one is that the valid vertex can be projected to the pipeline center line, at this time the projection point on the pipeline center line is directly taken as the final projection point. The other is that the point projected by the valid vertex is the extension line of a node segment of the pipeline center line, which is due to the fact that the valid vertex is in the sub-buffer area of the pipeline bending. In this case, the projection point is recorded as the pipeline bending point.

[0091] S2, determining all sliding windows with either end of the pipeline and each projection point as the starting point of the sliding window by using a dynamic step sliding window method;

[0092] Specifically, the dynamic step sliding window method is as follows: taking one end of the pipeline as the starting point, extending a first preset distance to the other end of the pipeline to form a first sliding window; taking each projection point as the starting point of the next sliding window in the direction from one end of the pipeline to the other end, extending the sliding window by the first preset distance, until the length of the sliding window is less than the first preset distance, or the other end of the pipeline is reached, to determine all sliding windows. Figure 8 As shown in (a), the first sliding window HD1 is obtained by extending from the end point D1 of the pipeline. Figure 8 As shown in (b), the second sliding window HD2 is obtained by extending from the projection point t1 closest to D1.

[0093] It can be understood that, when performing regional division for the first time, sliding windows are determined for all pipeline end points and all projection points; subsequently, the sliding windows are re-divided on the excluded divided regions, i.e., the starting points of the re-divided sliding windows are located on the un-divided regions, and the end points and projection points included in the divided regions are no longer subjected to dynamic step sliding window.

[0094] According to the provisions of GB 50251-2015 Gas Pipeline Engineering Design Specification, the first preset distance is 2 kilometers.

[0095] S3, screening a target sliding window with the largest preset index from all sliding windows, updating the boundary and the preset index of the target sliding window by using an index-driven sliding window iterative expansion and far-end projection point cross adjustment method, completing the current regional division and determining the regional division data and the basic data thereof; repeating S2-S3 on the pipeline path that has not been subjected to regional division, until all regional divisions of the pipeline path are completed.

[0096] Specifically, the preset index in S3 includes the number of households; and the process of S3 includes:

[0097] S31, traversing the set of building quadrilaterals intersecting with each sliding window, and counting the number of building quadrilaterals in each sliding window; if at least one of the four vertices of a building quadrilateral is located in the sliding window, it is determined that the building quadrilateral intersects with the sliding window.

[0098] S32, taking one building quadrilateral as one household, screening a sliding window with the largest number of households from all sliding windows; updating the boundary and the number of households of the target sliding window by using the index-driven sliding window iterative expansion and far-end projection point cross adjustment method, and taking the adjusted sliding window as a regional region, the basic data corresponding to the regional region including the updated number of households.

[0099] The index-driven sliding window iterative expansion and far-projection point cross adjustment method is as follows:

[0100] Using a second preset distance as the length, the sliding window is expanded forward and backward sequentially, ceasing expansion upon reaching the starting or ending point of the pipeline. If the preset index within the sliding window increases after expansion, the boundary of the sliding window is adjusted to the far projection point of the added building quadrilateral, and the expansion of the sliding window in that direction is repeated with the adjusted boundary. This process continues until the preset index no longer increases after expansion. Then, the boundary of the sliding window is determined at the far projection point of the added building quadrilateral from the previous expansion, and then expanded by a third preset distance. The second preset distance is greater than the third preset distance, and the second and third preset distances are determined according to the relevant boundary line regulations. The sliding windows completed by forward and backward expansion are recorded as a region, with the maximum number of households counted as the basic data corresponding to that region.

[0101] According to the GB 50251-2015 Code for Design of Gas Pipeline Engineering, "the boundary line should be no less than 200m from the outer edge of the nearest building". Therefore, the second preset distance should be no less than 200 meters. When the third preset distance is 200 meters, the second preset distance can be 400 meters.

[0102] The calculation results, when applied to actual projects, ensure that the regional classification meets the standardized requirements, resulting in more accurate classifications.

[0103] like Figure 9 -like Figure 14 For example, as shown Figure 9 As shown, along the pipe centerline 1, the inner region bounded by the buffer zone boundary lines 2 extending on both sides of the pipe centerline 1, and the sliding window starting from the pipe endpoint (e.g.) Figure 9 The area between the two dashed lines shown is the initial boundary of the sliding window along the direction of the arrow, which is the sliding window boundary line -3; as shown... Figure 10 As shown, the expansion extends L3 in the direction of the arrow, reaching the expansion line 4; buildings exist within the expansion area, such as... Figure 11 As shown, the boundary is adjusted to the sliding window boundary line 26 by taking the farthest endpoint of quadrilateral 5 of the building furthest along the expansion direction; continue expanding in the direction of the arrow, as... Figure 12 As shown, taking the sliding window boundary line 6 as the initial boundary for the second expansion, the second expansion L3 continues in the direction of the arrow, reaching the expansion line 7; there are two cases as follows:

[0104] 1) This expansion did not increase the number of households (no buildings were added, such as...). Figure 12 As shown in the figure, because the standard requires that "the boundary line should be no less than 200m from the outer edge of the nearest building", such as Figure 13As shown, the sliding window boundary is adjusted to the sliding window boundary line two 6 at the expansion L4, i.e. the final sliding window boundary line 8; as shown Figure 14 The range between the two dashed lines is the expanded sliding window.

[0105] 2) If the number of houses in the expansion range increases, i.e. there are buildings in the expansion range, then the boundary determination process continues as shown in Figures 10-14

[0106] S33, exclude the expanded sliding window area, and perform S2 again. In the newly determined all sliding window areas, S31-S32 are performed in a loop until all sliding window areas are classified into corresponding region areas.

[0107] S34, mark the remaining unmarked areas along the pipeline path. If there are remaining unmarked areas, it is because there are no buildings in the buffer area or the buildings are far away. Then mark these areas as independent region areas respectively until all areas along the pipeline path are classified into corresponding region areas.

[0108] S4, according to the region classification rules, use the pipeline path region area classification data and its basic data to determine the level, as shown in Figure 6

[0109] Specifically:

[0110] The basic data of each region area also includes the expanded sliding window number, the corresponding pipeline start and end point information, the corresponding building number, and the corresponding special building information, i.e. the data correlation mapping of the buffer area, sliding window, building, building vertex, pipeline bending node, node segment, effective point, and projection point in the foregoing process.

[0111] The four-story and above buildings in the special building information are obtained by using the additional data of the unmanned aerial vehicle through the following calculation:

[0112] When the building height is greater than or equal to the first preset height, and the floor area is greater than or equal to the first preset area, the building is marked as a four-story and above building. Usually, the height of each floor is about 3 meters, so the first preset height is 12 meters. The floor area of a building is usually more than 30 square meters, so the first preset area is 30 square meters.

[0113] According to the rules in GB 50251-2015 Gas Pipeline Engineering Design Specification, the levels of each region along the gas pipeline path are determined:

[0114] ​​If the number of houses in the sliding window is ≥ 100, the area grade of the area region is marked as three;

[0115] If the number of houses in the sliding window is ≥ 100, the area grade of the area region is marked as three;

[0116] If 15 < the number of houses in the sliding window < 100, the area grade of the area region is marked as two

[0117] If the number of houses in the sliding window is ≤ 15, the area grade of the area region is marked as one.

[0118] As shown in Figure 15 Further, S6, a GIS-based gas pipeline passing area area grade division system is constructed to execute a GIS-based gas pipeline passing area area grade division method; the system comprises:

[0119] A data acquisition unit is configured to acquire gas pipeline path data and unmanned aerial vehicle image data collected along the pipeline path;

[0120] An identification processing unit is configured to identify and process building vertex data in a terrestrial coordinate system around the pipeline path and pipeline building number data by using the gas pipeline path data and the unmanned aerial vehicle image data;

[0121] A GIS unit is configured to generate a buffer zone based on the gas pipeline path data, the building vertex data, and the pipeline building number data by relying on a geographic information system, and determine effective vertices and projection points of the effective vertices onto a pipeline center line representing the gas pipeline path based on the relationship between the buffer zone and the building vertices;

[0122] An area division unit is configured to slide and collect gas pipeline path area region division data and basic data for determining area grades of each area region in a dynamic step sliding window manner with any end of the pipeline and each projection point as a starting point of the sliding window, and in combination with an index-driven sliding window iterative expansion and far-end projection point cross-adjustment manner;

[0123] A grade confirmation unit is configured to determine the grades of each area region of the gas pipeline path according to area grade division rules by using the gas pipeline path area division unit data and the basic data.

[0124] It can be understood that the above system is any form of carrier that fully executes the above method, and the process and effect are the same, which will not be repeated here.

[0125] Further, as shown in Figure 16As shown, a practical application system is given, including terminal, partition server, identification server, GIS server, and execution process can be referred to Figures 1 to 6 .

[0126] The terminal can be a web terminal or a mobile terminal, including a data transmission first module and a visualization module.

[0127] The data transmission first submodule obtains gas pipeline path data and unmanned aerial vehicle image data collected along the pipeline path, and sends them to the partition server, wherein the unmanned aerial vehicle image data includes unmanned aerial vehicle orthophoto TIFF data, TIFF image coordinate information, unmanned aerial vehicle additional data and special building information; of course, it can be understood that the data transmission related submodule can be further divided into data receiving related module and data sending related module, which is specifically deployed according to actual system requirements.

[0128] The partition server includes a data transmission second module, a number association module, a region division module and a level confirmation module.

[0129] The data transmission second module receives the gas pipeline path data and the unmanned aerial vehicle image data sent by the terminal, and sends the unmanned aerial vehicle orthophoto TIFF data to the identification server.

[0130] The identification server includes a data transmission third module and an identification calculation module.

[0131] The data transmission third module receives and sends the unmanned aerial vehicle orthophoto TIFF data to the identification calculation module.

[0132] The identification calculation module uses image recognition technology to identify the unmanned aerial vehicle orthophoto TIFF data, obtains identification result information, and sends it to the data transmission second module of the partition server through the data transmission third module, wherein the identification result information includes building vertex coordinate information in the pipeline path surrounding geodetic coordinate system.

[0133] The data transmission second module sends the identification result information and the gas pipeline path data to the number association module, which numbers and associates the pipeline and the building to obtain pipeline building number data.

[0134] The data transmission second module sends the gas pipeline path data, building vertex data and pipeline building number data to the GIS server.

[0135] The GIS server includes a data transmission fourth module and a GIS calculation module.

[0136] The data transmission fourth module receives and sends the gas pipeline path data, building vertex data and pipeline building number data to the GIS calculation module.

[0137] The GIS calculation module receives the gas pipeline path data, the building vertex data and the pipeline building number data, and generates a buffer zone based on a geographic information system, and determines effective vertices and projection points of the effective vertices projected to a pipeline center line representing the gas pipeline path based on a relationship between the buffer zone and the building vertices, and sends the GIS calculation result to the data transmission second module through the data transmission fourth module;

[0138] The data transmission second module sends the GIS calculation result to the region division module. The region division module uses a dynamic step sliding window mode with any end of the pipeline and each projection point as a sliding window starting point, and combines a sliding window expansion mode to slide and collect gas pipeline path region region division data and basic data for determining the region level, and sends the data to the level confirmation module through the data transmission second module.

[0139] The level confirmation module determines the level of each region of the gas pipeline path according to the region level division rule, using the gas pipeline path region region division data and the basic data.

[0140] The data transmission second module sends the data representing the region level information in the partition server to the data transmission first module of the terminal, the data transmission first module receives and sends to the visualization module, and the visualization module visually displays the data representing the region level information, including but not limited to pipeline starting point and ending point information, region level, and spatial distribution of residential households.

[0141] The GIS-based gas pipeline passing region region level division method provided in this embodiment reduces manual intervention, improves the efficiency and accuracy of data collection and analysis, and can more comprehensively and objectively reflect the actual situation of the gas pipeline passing region, providing a scientific basis for the planning, construction, operation and maintenance of the gas pipeline.

[0142] Embodiment Two

[0143] Unlike Embodiment One, in the traditional region level division system, the number of households is the core basis for division. Based on such region level division, the traditional high consequence identification focuses on high-level regions. However, this traditional mode of dividing region level only by the number of households and identifying high consequences based on it has obvious limitations. Although the number of households in low-level regions is small, some special risk factors may be overlooked. Therefore, simply dividing region level by the number of households for high consequence identification cannot comprehensively and accurately assess the true risk status of each region, which may lead to missed judgment of potential high risks in low-level regions, and may cause hidden dangers for subsequent safety management.

[0144] The embodiment is based on building type to construct a building function density index, and improve the multidimensionality and accuracy of regional grade judgment.

[0145] S1, each building is classified, and the classification criteria include: residential type (including single-family, multi-story, high-rise), public type (school, hospital, nursing home), commercial type (mall, hotel, market), industrial type (factory, warehouse), temporary building (shack, mobile home), etc. can be automatically classified through a deep learning model (such as ResNet+GIS semantic segmentation);

[0146] S2, different risk weight coefficients w are given according to the building type, for example: residential type w = 1.0 (baseline); school / kindergarten w = 2.5 (personnel intensive, difficult to evacuate); hospital / nursing home: w = 2.2 (many vulnerable groups); commercial center: w = 1.8 (large peak flow); industrial plant: w = 1.3 (potential secondary disaster); temporary building: w = 1.6 (fragile structure).

[0147] S3, the influence factor value of all buildings in each sliding window is calculated, which is defined as the building function density index Q:

[0148]

[0149] In the formula, represents the number of buildings in the e-th sliding window; represents the risk weight of the i-th building; represents the projection area of the i-th building; represents the total area of the e-th sliding window;

[0150] The above formula integrates building type, size and spatial density, and reflects the concentration of high-risk function bodies in unit area.

[0151] S4, the building function density index Q and the traditional number of households are output in parallel to form a two-dimensional evaluation atlas. The regional grade is still mainly judged by the household number threshold value specified in GB 50251-2015, but when the number of households is in the critical interval of the grade (such as close to the lower limit of the fourth grade), if the building function density index Q is significantly higher than the regional average, the grade can be triggered. Warning for upgrading, for manual review and confirmation.

[0152] The embodiment provides a GIS-based gas pipeline passing area region grade division method, constructs a building function density index based on a building category, normalizes expression of "high-risk function body density" on unit land through a ratio of a weighted area sum and a region area, and the higher the value is, the more high-risk attribute buildings are gathered around the region, so that even if a house number does not reach a high-grade standard, attention should be paid. The building function density index constructed by the scheme serves as an auxiliary evaluation index in a region grade division stage, can reveal potential risk differences caused by different building functions under the same population quantity, provides multi-dimensional data support in the region grade division stage, can be used as a prepositive and structural input parameter of high-consequence identification, and improves foresight and scientificity of judgment.

[0153] The above is only an embodiment of the present application, and common knowledge such as specific structures and characteristics in the scheme is not described too much here. The person skilled in the art knows all the common technical knowledge in the technical field of the present application before the application date or the priority date, can know all the prior art in the field, and has the ability to apply conventional experimental means before the date. The person skilled in the art can improve and implement the present scheme in combination with the ability of the person skilled in the art under the guidance of the present application. Some typical known structures or known methods should not be an obstacle for the person skilled in the art to implement the present application. It should be pointed out that, for the person skilled in the art, without departing from the structure of the present application, a number of modifications and improvements can be made, which should be regarded as the protection scope of the present application, and these will not affect the implementation effect and practicality of the patent.

Claims

1. A method for classifying the regional grading of gas pipeline routes based on GIS, characterized in that, include: S1: Obtain a multi-source dataset representing the pipeline path and the information of buildings along the path, and generate a buffer based on the geographic information system to simultaneously determine the effective vertices of buildings and their projection points onto the pipeline path. S2, using the dynamic step size sliding window method, determines all sliding windows with any end of the pipe and each projection point as the starting point of the sliding window; S3: Select the target sliding window with the largest preset index among all sliding windows, and adopt the index-driven sliding window iterative expansion and far-end projection point cross adjustment method to update the boundary and preset index of the target sliding window, complete the current region division and determine its regional division data and its basic data; repeat S2-S3 on pipeline paths that have not been divided into regions until the region division of all pipeline paths is completed. S4. Based on the regional classification rules, the classification of each region along the pipeline route and its basic data are used to determine the level. In S2, the dynamic step-size sliding window method is as follows: Starting from one end of the pipe, extend a first preset distance to the other end of the pipe as the first sliding window; along the direction from one end of the pipe to the other end, take each projection point as the starting point of the next sliding window, extend the sliding window by the first preset distance, until the length of the sliding window is less than the first preset distance, and reach the other end of the pipe to determine all sliding windows. In S3, the index-driven sliding window iterative expansion and far-end projection point cross adjustment method is as follows: The sliding window is expanded forward and backward sequentially with a second preset distance as its length, and expansion stops when it reaches the starting or ending point of the pipeline. If the preset index within the sliding window increases after expansion, the boundary of the sliding window is adjusted to the far projection point of the added building quadrilateral, and the expansion of the sliding window in that direction is repeated with the adjusted boundary. This continues until the preset index no longer increases after expansion. Then, the boundary of the sliding window is determined to be the position of the far projection point of the added building quadrilateral during the previous expansion, and then expanded by a third preset distance. The second preset distance is greater than the third preset distance, and the second and third preset distances are determined according to the relevant regulations for boundary lines.

2. The method for classifying the regional hierarchy of gas pipeline routes based on GIS according to claim 1, characterized in that, The preset indicators in S3 include the number of households; the S3 process includes: S31, traverse the set of building quadrilaterals that intersect with each sliding window, and count the number of building quadrilaterals in each sliding window; S32, taking a quadrilateral of a building as a household, select the sliding window with the largest number of households from all sliding windows, and adopt an index-driven sliding window iterative expansion and far-end projection point cross adjustment method to update the boundary and number of households of the target sliding window, thus completing the current area division. The adjusted sliding window is taken as a region, and the basic data corresponding to the region includes the updated number of households. S33, exclude the sliding window regions that have been expanded, repeat S2, and cycle through S31-S32 in all newly determined sliding windows until all sliding window regions are assigned to the corresponding regions. S34, mark the remaining undefined areas as independent regions until all areas along the pipeline route are designated as corresponding regions.

3. The method for classifying the regional hierarchy of gas pipeline routes based on GIS according to claim 1, characterized in that, In S1, the multi-source dataset includes UAV imagery data collected along the pipeline path and building vertex data; the process of determining the building vertex data includes: UAV imagery data includes UAV orthophoto TIFF data and TIFF image coordinate information; Image recognition technology was used to identify and process TIFF orthophotos from UAVs to obtain the vertex pixel coordinates of buildings around the pipeline path; By combining the building vertex pixel coordinate data with the actual geographic coordinates in the TIFF image coordinate information, an affine transformation is performed to convert the building vertex pixel coordinate data into building vertex data in the geodetic coordinate system.

4. The method for classifying the regional grading of gas pipeline routes based on GIS according to claim 1, characterized in that, In S1, the multi-source dataset includes gas pipeline path data; the process of generating the buffer includes: Based on the gas pipeline path data, there are multiple bends on the pipeline centerline. The straight pipeline segment between two adjacent bends is a node segment. The buffer zone includes sub-buffer zones at both ends of the pipeline, sub-buffer zones for each straight pipeline segment, and sub-buffer zones at each bend. The outer edges of all sub-buffer zones transition continuously, and the envelope area formed by these outer edges is the buffer zone.

5. The method for classifying the regional hierarchy of gas pipeline routes based on GIS according to claim 4, characterized in that, Using a geographic information system, a strip-shaped area is formed by extending vertically to both sides of the center line of each straight pipeline segment as the center line, and the strip-shaped area serves as a buffer zone for each straight pipeline segment. Using each bend point as the center and the fourth preset distance as the radius, construct an arc-shaped region to connect adjacent strip-shaped regions, and use the arc-shaped region as a sub-buffer zone at each bend point; Using the two ends of the pipe as centers and the fourth preset distance as the radius, construct semi-circular regions to connect adjacent strip-shaped regions, and use the semi-circular regions as buffer zones at both ends of the pipe.

6. The method for classifying the regional hierarchy of gas pipeline routes based on GIS according to claim 1, characterized in that, In S1, the multi-source dataset includes gas pipeline path data, building vertex data, and pipeline building number data; the building vertices included in the buffer are determined as valid vertices, and the determination process includes: Based on the gas pipeline route data, there are multiple bends along the pipeline centerline, and the straight pipeline segments between two adjacent bends are node segments. Based on the building vertex data and pipeline building number data, the traversal begins from the first vertex and the first node segment: Based on the relationship between the distance between the vertex and the two endpoints of the node segment and the buffer, the first determination of the valid vertex is performed; For each node segment, construct a right-angled triangle within the buffer zone. Compare the length of the hypotenuse of the right-angled triangle with the distance between the vertex and the two endpoints of the node segment to perform a second determination of the valid vertex. Based on the relationship between the vertical distance between vertices and node segments and the buffer, a third determination of valid vertices is made; Each time the condition is met, the process returns to the first check of the next vertex or the next node segment; finally, the check of whether all building vertices are valid vertices is completed.

7. The method for classifying the regional hierarchy of gas pipeline routes based on GIS according to claim 1, characterized in that, In S1, the process of determining the projection points of valid vertices onto the pipeline path includes: The nearest point algorithm from a point to the pipe centerline is used to calculate the orthogonal projection position of the valid vertex on the pipe centerline. When the valid vertex is projected onto the pipe centerline, the projection point on the pipe centerline is taken as the final projection point. When the valid vertex is projected onto the extension of the pipe centerline, the nearest bend point in the area where the valid vertex is located is taken as the projection point.

8. The method for classifying the regional hierarchy of gas pipeline routes based on GIS according to claim 1, characterized in that, It also includes constructing a GIS-based regional classification system for gas pipeline routes, to implement a GIS-based regional classification method for gas pipeline routes; the system includes: The data acquisition unit is used to acquire gas pipeline path data and UAV imagery data collected along the pipeline path; The identification and processing unit is used to identify and process building vertex data and pipeline building number data in the geodetic coordinate system around the pipeline path using gas pipeline path data and UAV image data. The GIS unit is used to generate a buffer based on the geographic information system, gas pipeline path data, building vertex data, and pipeline building number data. It also determines the effective vertices and the projection points of the effective vertices onto the pipeline centerline that represents the gas pipeline path based on the relationship between the buffer and the building vertices. The regional division unit is used to obtain regional division data of gas pipeline path and basic data of each region for determining the regional level by using a dynamic step-size sliding window with any end of the pipeline and each projection point as the starting point of the sliding window. It is combined with index-driven sliding window iterative expansion and far-end projection point cross adjustment to obtain regional division data of gas pipeline path and basic data of each region for determining the regional level. The grade confirmation unit is used to determine the grade of each region along the gas pipeline route based on the regional grade classification rules, using regional division data and basic data.

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