Urban space unit digital segmentation method

Abstract

The invention discloses an urban space unit digital segmentation method, and belongs to the technical field of urban planning, and the method comprises the steps: inputting site data, simplifying and integrating the plane contour of a building in a site, and obtaining a site space and the integrated plane contour of the first layer of the building; on the basis of the integrated plane contour of the first floor of the building, according to a site space relation, connecting and screening building end points to nearest points of the building contours to obtain preliminary division control lines; performing constraint denaulay triangulation based on the preliminary division control line, the building contour and the site plane contour to generate a triangulation network unit; and merging the triangulation network units according to the maximum edge merging and concave angle avoiding principle to obtain an urban space division result. According to the method, space division can be carried out on a public space in a relatively complex urban plot, a space unit division result relatively conforming to actual space perception of people is formed, and meanwhile, the calculation efficiency and the calculation accuracy are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of urban planning, and in particular to a method for digitally segmenting urban space units. Background Art

[0002] In urban design research, it is often necessary to further divide the large public spaces in the city, dividing the irregular large spaces into relatively small and relatively regular small spaces for further research.

[0003] In existing space syntax, traditional spatial unit division methods mainly include the convex space method, the axis method, and the viewport method. These methods rely on manual judgment or simple geometric rules and are difficult to adapt to the heterogeneity of complex urban spaces, resulting in division results that deviate from actual human spatial perception. Other digital methods developed using computers include overlapping convex space analysis, all-line analysis, and analysis from viewport to visible diagrams. In addition, there are surface segmentation and endpoint segmentation methods. Although these methods improve the automation of spatial division, they are unable to segment the required spatial units when dealing with relatively complex public spaces (such as areas with multiple buildings, open squares, and winding paths). Alternatively, they are computationally intensive, inefficient, prone to computational redundancy, and often result in fragmented or irregular division units.

[0004] Chinese invention patent publication number CN110135043B discloses a method and system for classifying urban streetscape spatial morphology. This method connects building exterior corners and, through limiting and classifying the quantitative results, achieves the goal of reconstructing spatial planar morphological categories using indicators. However, this method only considers the lines connecting exterior corners, ignoring the possibility of connecting exterior corners with building boundaries. This results in some spatial divisions with low spatial regularity and poor alignment with actual spatial perception. To achieve a space that aligns with the designer's perception, further manual delineation and modification are often required.

[0005] Therefore, there is an urgent need for a digital segmentation method for urban spatial units that can balance computational efficiency, spatial regularity, and human perception consistency to support refined urban design and analysis. Summary of the Invention

[0006] The problem to be solved by the present invention is to provide a method for digital segmentation of urban space units, which is used to spatially divide public spaces in more complex urban plots, form a spatial unit division result that is more in line with people's actual spatial perception, and at the same time improve calculation efficiency and accuracy.

[0007] The present invention adopts the following technical solution: a method for digitally segmenting urban space units, comprising the following steps:

[0008] Step 1: Input site data and use 3D modeling software to simplify and integrate the building plane outlines within the site to obtain the site plane outline and the integrated first-floor plane outline of the building;

[0009] Step 2: Based on the integrated first-floor plan outline of the building and the spatial relationship in the site, connect the building endpoints to the nearest points of each building outline and filter them to obtain the preliminary division control line;

[0010] Step 3: Based on the preliminary division control lines, building outlines, and site plane outlines, constrained Denaulay triangulation is performed to generate triangulated network units;

[0011] Step 4: Merge the triangulated mesh units according to the principle of maximum edge merging and avoiding concave corners to obtain the urban space division result.

[0012] Preferably, in step 1, the site data includes: a site plane outline and a building model within the site; the site data is input into a 3D modeling software including: Rhino and Grasshopper.

[0013] Preferably, in step 1, simplifying and integrating the plane outlines of the buildings in the site includes the following sub-steps:

[0014] Step 1.1: Read the building model in the site and convert it into brep format using 3D modeling software. Split the building model into brep format to obtain the surface, and filter out the plane outline of the first floor of the building.

[0015] The plane outline of the first floor of the building is a surface located at an elevation of 0, or is obtained by intersecting the building model with a plane slightly higher than an elevation of 0.

[0016] Step 1.2: Merge the adjacent building outlines using the Region Union method to form the outer contour.

[0017] Step 1.3: Create a buffer zone outward for the merged outer contour according to the distance threshold α, and then offset it inward by the same value to eliminate the concave and convex relationships between buildings that are less than the distance threshold α, simplify the plane, and obtain the integrated plane outline of the first floor of the building.

[0018] Preferably, in step 2, connecting and screening the nearest points of the building endpoints to the contours includes the following sub-steps:

[0019] Step 2.1, based on the integrated first-floor plan outline of the building, extract the endpoints of the building's external corners, calculate the closest points from the external corner endpoints to all other buildings in the site, connect the closest points and the endpoints to obtain a set of line segments;

[0020] Step 2.2: Determine whether the line segments in the line segment set pass through the building, filter out the line segments that pass through the building, and use the remaining line segments as the preliminary division control lines, recorded as line segment set A.

[0021] Preferably, to determine whether a line segment passes through a building, each line segment is shrunk by a preset minimum value, and whether the shrunk line segment intersects with the building outline, or the building outline is offset inward by a preset minimum value, and whether the line segment intersects with the shrunk building outline is determined; if the control lines intersect, the longer control line is deleted and the shorter control line is retained.

[0022] Preferably, in step 3, constrained Denaulay triangulation is performed to triangulate the empty circumcircle under the premise of maintaining given constrained edges, including the following sub-steps:

[0023] Step 3.1, explode the polylines of the building outline and the site plan outline into line segments, denoted as line segment set B;

[0024] Step 3.2: Compare the intersection of line segment set B and line segment set A, and perform a segment break operation on the intersecting line segments in line segment set B;

[0025] The line segment breaking operation includes but is not limited to being executed through the Union method of LineStrings in jts.

[0026] Step 3.3: Repeat step 3.2 until all line segments in line segment set B cannot be interrupted anymore.

[0027] Step 3.4: Using the line segments in set A and set B as input conditions, perform constrained Denaulay triangulation to generate triangulated mesh elements.

[0028] Preferably, in step 4, each triangle in the triangulated mesh unit is regarded as a polygon and merged, which includes the following sub-steps:

[0029] Step 4.1: Create an edge-polygon mapping table and construct a polygon adjacency graph;

[0030] Step 4.2: Perform a merging loop, starting with the longest edge, merging polygons with adjacent edges, following the principle that the merged polygons will not form concave corners, until there are no shared edges, and then end the loop;

[0031] Step 4.3: The obtained polygon set is used as the final urban space unit division result.

[0032] Preferably, in step 4.2, the effect of smaller edges is ignored by setting the edge length parameter len_threshold, and the tiny concave angles are ignored by setting the angle parameter angle_threshold.

[0033] Compared with the prior art, the present invention adopts the above technical solution and has the following technical effects:

[0034] 1. The digital segmentation method for urban spatial units of the present invention can be used to divide public spaces in relatively complex urban plots. By introducing spatial relationship control lines between building corners, site outlines, and building outlines, the resulting spatial unit division results can significantly conform to people's actual spatial perception.

[0035] 2. The digital segmentation method of urban space units of the present invention uses triangulation to prevent the initial unit segmentation from being too dense, thereby being able to organize the initial space units in a relatively efficient manner and having high computational efficiency.

[0036] 3. The digital segmentation method of urban space units of the present invention retains different parameter settings and can adapt to users' different precision requirements for space division and different usage scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 This is a flowchart of the method for digitally segmenting urban space units according to the present invention;

[0038] Figure 2 2D and 3D schematic diagrams of the initial model site and buildings according to an embodiment of the present invention;

[0039] Figure 3 A schematic diagram of the plan outline of a one-story building generated by an embodiment of the present invention;

[0040] Figure 4 This is a schematic diagram of control lines generated according to the relationship between buildings and sites according to an embodiment of the present invention;

[0041] Figure 5 Schematic diagram of the interrupted triangulation constraint control line according to an embodiment of the present invention;

[0042] Figure 6 Schematic diagram of Denaulay triangulation constrained by an embodiment of the present invention;

[0043] Figure 7 This is a schematic diagram of the result of merging polygonal spatial units according to an embodiment of the present invention. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions of the application are further elaborated in detail below with reference to the accompanying drawings. The described embodiments are only a part of the embodiments involved in the present invention. All non-innovative embodiments of other researchers in this field on this embodiment fall within the scope of protection of the present invention. At the same time, the step numbers in the embodiments of the present invention are only set for the convenience of explanation and description, and the order between the steps is not limited in any way. The execution order of each step in the embodiment can be adaptively adjusted according to the understanding of those skilled in the art.

[0045] In one embodiment of the present invention, a method for digitally segmenting urban space units is provided. Figure 1 As shown, the following steps are included:

[0046] 1. Input site data, simplify the building plan outlines within the site, and obtain the site space and the integrated building first floor outline;

[0047] 2. Based on the spatial relationship, connect and filter the lines from the building endpoints to the nearest points of each contour (building contour + site contour) to obtain the preliminary division control line;

[0048] 3. Perform constrained Denaulay triangulation based on control lines, building outlines, and site outlines;

[0049] 4. According to the principle of maximum edge merging and avoiding concave angles, the triangulated mesh units are merged to form the final space division result.

[0050] Specifically, if Figure 2 As shown, a certain urban plot is shown. The building model and the plane outline of the plot are imported into the Rhino software.

[0051] The first step is to read the building model into the brep format using the Grasshopper tool. First, explode the brep to obtain the surface, then filter out the surface with an elevation of 0 to obtain the first-floor plan outlines of all individual buildings. Use the Region Union tool in Grasshopper to merge the outlines of adjacent buildings.

[0052] Then, create a buffer zone outwards for the building outline, set the distance threshold parameter α = 4, and then offset the same value inwards to obtain the following: Figure 3 This operation can eliminate the concave and convex relationships between buildings that are less than the threshold α, simplify the plane, artificially filter out unnecessary small spaces, and make the subsequent generation results less complicated.

[0053] It can be seen that compared with the original building, the new outline used for subsequent calculations has been simplified a lot, especially some small spaces and the inner courtyard in the upper left corner, which no longer participate in the overall subsequent calculations.

[0054] In particular, the plane outline of a building can also be obtained by intersecting the building model with a plane slightly higher than the 0 elevation; the data of the distance threshold α can be independently set according to the user's accuracy requirements.

[0055] In the second step, the endpoints of the building's outer corners are extracted from the new building outline, and the nearest points from these points to other buildings are calculated and connected. At the same time, the line segments that intersect with the buildings are filtered out, and the following is obtained: Figure 4 Control lines shown.

[0056] As can be seen, these control lines effectively connect the buildings and the site contours, creating distinct initial spatial regions. Unlike direct connection of external corners, when the external corners are far apart and their endpoints are close to a side of a building, the building corners and sides form lines, creating some right-angled areas.

[0057] Specifically, to determine whether a line segment passes through a building, you can shrink each line segment by a minimum value (e.g., 0.001) and then determine whether the shrunken line segment intersects the building outline. Alternatively, you can offset the building outline inward by a minimum value and then determine whether the line segment intersects the shrunken building outline. If control lines do intersect, delete the longer control line and retain the shorter one.

[0058] In the third step, the polylines of the building outline and the site outline are exploded into line segments through the explode operation in Grasshopper to obtain line segment set B, which is then compared with the line segment set A of the control line obtained in the second step to determine whether the line segment set B intersects with the line segments in the line segment set A. If so, the line segments are interrupted at the intersection point.

[0059] For example, if line segment PQ in segment set A intersects line segment MN in segment set B at point Q, segment MN is split into MQ and QN. Repeat this process until all segments in segment set B cannot be split any further.

[0060] The interrupted triangulation constraint control line is as follows Figure 5 As shown, the control line segments, the interrupted building and site outline segments, and the endpoints of the segments are displayed.

[0061] In particular, the line segment breaking operation can be completed using the Union method of LineStrings in jts.

[0062] Then, the line segments in set A and set B are used as input conditions to perform constrained denaulay triangulation to generate triangulated network units, as shown below: Figure 6 The constrained Denaulay triangulation result is shown.

[0063] Constrained Delaunay triangulation is a triangulation that satisfies the empty circumcircle property while maintaining given constraining edges. By constraining Delaunay triangulation, some areas can be further segmented, creating conditions for subsequent recombination. Compared to direct triangulation, the resulting triangulated network incorporates the proximity relationships between buildings and between buildings and the site outline.

[0064] The fourth step is to merge the triangulated triangulated units in the previous step. First, establish an edge-polygon mapping table and build a polygon adjacency graph. Then, start from the longest edge and perform a merge cycle to finally get the following: Figure 7 The polygonal space unit results are shown.

[0065] The main principle of the merge loop is to try to merge polygons with adjacent edges starting from the longest edge, while following the merged polygons without forming concave corners.

[0066] Furthermore, the edge length parameter len_threshold can be set to ignore the effect of smaller edges, and the angle parameter angle_threshold can be set to ignore tiny concave angles.

[0067] The specific method of merging loop operations is as follows:

[0068] Traverse all shared edges in the adjacency graph, generate candidate edges, and sort them in descending order of edge length.

[0069] For each candidate edge, its adjacent polygons are recorded as P1 and P2, and the vertices of P1 and P2 are reorganized around the shared edge to generate a new polygon P_New.

[0070] If the new polygon satisfies the following conditions: the side length is greater than len_threshold and the direction change is less than angle_threshold, then P1 and P2 are removed from the original polygon set, and polygon P_New is added, the edge mapping and adjacency relationship are rebuilt, and the next round of merging cycle operation is entered.

[0071] The loop ends when there are no shared edges and the merged polygons meet the conditions. The resulting polygon set is the final spatial unit division result.

[0072] In particular, the side length parameter len_threshold and the angle parameter angle_threshold are set independently according to the user's control of the shape. At the same time, depending on different parameters, 2 to 3 rounds of merging can be set to achieve better results.

[0073] During the generation process, this embodiment performs three merging cycles: the first cycle is strict merging, the second cycle allows for certain concave angles, and the third cycle ignores certain smaller side lengths, thereby obtaining the final result.

[0074] It can be seen that the final polygonal spatial unit division of the entire space is generally consistent with human spatial perception. For example, the small through-space between the two larger spaces on the upper and lower right sides is well preserved, while the large space on the lower left is merged as much as possible.

[0075] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for digital segmentation of urban space units, characterized in that: The steps include: Step 1: Input site data and use 3D modeling software to simplify and integrate the building plane outlines within the site to obtain the site plane outline and the integrated first-floor plane outline of the building; Step 2: Based on the integrated first-floor plan outline of the building and the spatial relationship in the site, connect the building endpoints to the nearest points of each building outline and filter them to obtain the preliminary division control line; Step 3: Based on the preliminary division control lines, building outlines, and site plane outlines, constrained Denaulay triangulation is performed to generate triangulated network units; Step 4: Merge the triangulated mesh units according to the principle of maximum edge merging and avoiding concave corners to obtain the urban space division result.

2. The method for digital segmentation of urban space units according to claim 1, characterized in that: In step 1, the site data includes: the site plane outline and the building model in the site; the site data is input into 3D modeling software, including: Rhino, Grasshopper.

3. The method for digital segmentation of urban space units according to claim 2, characterized in that: In step 1, the building outlines within the site are simplified and integrated, which includes the following sub-steps: Step 1.1: Read the building model in the site and convert it into brep format using 3D modeling software. Split the building model into brep format to obtain the surface, and filter out the plane outline of the first floor of the building. Step 1.2: Merge the adjacent building outlines using the Region Union method to form the outer contour. Step 1.3: Create a buffer zone outward for the merged outer contour according to the distance threshold α, and then offset it inward by the same value to eliminate the concave and convex relationships between buildings that are less than the distance threshold α, simplify the plane, and obtain the integrated plane outline of the first floor of the building.

4. The method for digital segmentation of urban space units according to claim 3, characterized in that: The plane outline of the first floor of the building is a surface located at an elevation of 0, or is obtained by intersecting the building model with a plane slightly higher than an elevation of 0.

5. The method for digital segmentation of urban space units according to claim 3, characterized in that: In step 2, lines are drawn from the building endpoints to the nearest points of each contour and then filtered, including the following sub-steps: Step 2.1, based on the integrated first-floor plan outline of the building, extract the endpoints of the building's external corners, calculate the closest points from the external corner endpoints to all other buildings in the site, connect the closest points and the endpoints to obtain a set of line segments; Step 2.2: Determine whether the line segments in the line segment set pass through the building, filter out the line segments that pass through the building, and use the remaining line segments as the preliminary division control lines, recorded as line segment set A.

6. The method for digital segmentation of urban space units according to claim 5, characterized in that: In step 2.2, determine whether the line segment passes through the building by shrinking each line segment by a preset minimum value and determining whether the shrunken line segment intersects with the building outline, or offset the building outline inward by a preset minimum value and determining whether the line segment intersects with the shrunken building outline; If the control lines intersect, delete the longer control line and keep the shorter control line.

7. The method for digital segmentation of urban space units according to claim 5, characterized in that: In step 3, constrained Denaulay triangulation is performed to triangulate the empty circumcircle while maintaining the given constrained edges. This includes the following sub-steps: Step 3.1, explode the polylines of the building outline and the site plan outline into line segments, denoted as line segment set B; Step 3.2: Compare the intersection of line segment set B and line segment set A, and perform a segment break operation on the intersecting line segments in line segment set B; Step 3.3: Repeat step 3.2 until all line segments in line segment set B cannot be interrupted anymore. Step 3.4: Using the line segments in set A and set B as input conditions, perform constrained Denaulay triangulation to generate triangulated mesh elements.

8. The method for digital segmentation of urban space units according to claim 7, characterized in that: In step 3.2, the line segment breaking operation includes but is not limited to being performed through the Union method of LineStrings in jts.

9. The method for digital segmentation of urban space units according to claim 7, characterized in that: In step 4, each triangle in the triangulated mesh unit is considered as a polygon and merged, which includes the following sub-steps: Step 4.1: Create an edge-polygon mapping table and construct a polygon adjacency graph; Step 4.2: Perform a merging loop, starting with the longest edge, merging polygons with adjacent edges, following the principle that the merged polygons will not form concave corners, until there are no shared edges, and then end the loop; Step 4.3: The obtained polygon set is used as the final urban space unit division result.

10. The method for digital segmentation of urban space units according to claim 9, characterized in that: In step 4.2, the effect of smaller edges is ignored by setting the edge length parameter len_threshold, and the small concave angles are ignored by setting the angle parameter angle_threshold. The specific method of merging the loop operation is as follows: Step 4.2.

1. Traverse all shared edges in the adjacency graph, generate candidate edges, and sort them in descending order of edge length. Step 4.2.2: For each candidate edge, record its adjacent polygons as P1 and P2, bypass the shared edge and reorganize the vertices of P1 and P2 to generate a new polygon P_New; Step 4.2.3: If the new polygon satisfies the following conditions: the side length is greater than len_threshold and the direction change is less than angle_threshold, then remove P1 and P2 from the original polygon set, add polygon P_New, rebuild the edge mapping and adjacency relationship, and enter the next round of merging loop operation.

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