Street street model large-scale defining method based on center point look-around sampling
Through the method of center point surround sampling, the three-dimensional spatial model of the street intersection is accurately measured, which solves the problem of inaccurate definition caused by different sizes of the street intersection, and realizes the refined quantitative analysis of the street intersection morphology, providing a scientific basis for urban design and public space planning.
Patent Information
- Application Number
- CN202510415451.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-04-03
- Publication Date
- 2025-07-25
AI Technical Summary
When defining the street intersection model, the existing technology is difficult to adapt to the heterogeneity of urban street intersections with different scales, resulting in a lack of accuracy in the definition results, unable to provide scientific basis for urban design and street intersection public space planning, and difficult to collect on a large scale.
The method based on center point circumferential sampling is adopted. By identifying the center point of the street, setting the interval angle and expansion coefficient, a center point circumferential polygon and sampling box are constructed, and a three-dimensional space model is constructed based on basic data to achieve accurate measurement and large-scale acquisition of the three-dimensional space of the street.
It has achieved automated and precise definition of the intersection range under different scales and forms, which has improved the scientificity of research and standard uniformity, and has a wide adaptability, reducing errors in manual intervention and subjective judgment.
Smart Images
Figure CN120374841A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of smart city technology, and in particular to a large-scale definition method of street intersection models based on center point surround sampling. Background Art
[0002] Street intersections, also known as "road junctions", are the intersections of streets and are an important part of urban public space. As a point element in the urban spatial structure, street intersection space plays the role of a node in the urban spatial structure. It is one of the "five elements of urban image" proposed by Kevin Lynch and a key component of the city's distinctive features. Therefore, the collection of three-dimensional space at urban street intersections is of prerequisite significance and important value for the detailed study of the spatial morphological characteristics of street intersections and the application of urban design and street intersection public space planning.
[0003] The current technical means for defining street intersection models usually include the grid method and the buffer method. Both methods can quickly convert the point data representing street intersections in the urban morphology database into surface data, thereby defining a clear boundary. However, in the face of the real urban built environment, the heterogeneity of its morphology determines that the scales of each street intersection are different. The street intersection objects defined by the existing methods are very likely to be insufficiently considered and produce inconsistent standards. Defining street intersection objects with a fixed radius may only include a small part of the built environment volume for larger street intersections, while a considerable part of smaller street intersections is reflected in the defined objects. The results of such definition lack precision, making it difficult to provide a scientific and rational basis for urban design and street intersection public space planning, and also limiting the possibility of large-scale collection. Summary of the invention
[0004] Purpose of the invention: In view of the above problems, the purpose of the present invention is to provide a large-scale definition method of street intersection models based on center point surround sampling, which can accurately measure and obtain large-scale three-dimensional spatial models of street intersections, realize refined quantitative analysis of street intersection morphology, and provide a more rational scientific basis for urban design applications and street intersection public space planning.
[0005] Technical solution: A large-scale definition method of street intersection model based on center point surround sampling, comprising the following steps:
[0006] Step 1: Determine the collection scope and obtain basic data, which includes the layer information of the street center point, building outline, and building height within the collection area;
[0007] Step 2: Identify and select valid street intersection center points as viewpoints, number them and register the center point information;
[0008] Step 3: For each street intersection, set the interval angle Δr, and obtain the central point panoramic polygon through continuous equal-angle panoramic sampling.
[0009] Step 4: Record and filter all effective street intersection panoramic line lengths of each street intersection, and calculate the average value as the average open space radius R0 of the street intersection.
[0010] Step 5: Set the expansion coefficient k, and calculate the sampling radius R of all effective street intersection models, where R = k·R0.
[0011] Step 6: Construct the corresponding central point panoramic sampling box for all effective street intersection objects.
[0012] Step 7: Combine the central point panoramic sampling box and the basic data to construct the three-dimensional space model of the effective street intersection object, and associate and mark it with the corresponding street intersection number.
[0013] Furthermore, in Step 1, the building outline has the same height as the street intersection central point, and both of their z-axes are at the 0 elevation; there is a one-to-one correspondence between the building outline and the building height, and each building outline has a corresponding building height data information.
[0014] Furthermore, in Step 2, the screening of the effective street intersection central points includes the following steps:
[0015] S21: Obtain the street center line information, and get all the intersections within each street intersection in this layer through the street center line information. Let the intersection with only one intersection be a single-intersection street intersection, and the rest be multi-intersection street intersections. Record the distance between every two intersections of the multi-intersection street intersections as l n , where n is the number of pairs of these intersections; compare l n with the given length parameter L, and regard the multi-intersection street intersections that meet all l n ≤ L and all single-intersection street intersections as effective street intersections.
[0016] S22: For a single-intersection effective street intersection, set this intersection as the street intersection central point; for an effective street intersection with two intersections, take the midpoint of the line segment formed by these two points as the street intersection central point; for an effective street intersection with three or more intersections, take the centroid of the polygon formed by these intersections as the street intersection central point to obtain the street intersection central points of all effective street intersections.
[0017] Preferably, number the effective street intersections as i, where i = 1, 2..., then the street intersection central point of the effective street intersection is denoted as O i , with coordinates (a i , b i1 ). Arrange the coordinates of all street intersection central points in descending order of the ordinate and number them with natural numbers.
[0018] Optimally, in step S21, the value range of the length parameter L is 5m to 10m.
[0019] Furthermore, in step 3, obtaining the center point viewing polygon includes the following steps:
[0020] S31: Set Δr to be a positive integer satisfying 360° / Δr;
[0021] S32: Starting from the due north direction and taking the center point of the intersection as the center of the circle, draw the sampling rays in the clockwise direction according to the sampling interval angle, and record the first intersection point of each ray with the surrounding building outline. If there is no intersection point between the ray and the building outline, the ray is excluded, and these intersection points are recorded as A. i1 , A i2 , A i3 , ..., A in , a total of n;
[0022] S33: Measure the length of the line segment from the center point of the intersection to each intersection point, recorded as OA i1 , OA i2 , OA i3 ,……,OA in , and record the lower quartile of each line segment length as Q1, the upper quartile as Q3, and set the minimum buffer distance d min , maximum sampling buffer distance d max ,but:
[0023] d min =Q1 -1 .5(Q3-Q1);
[0024] d max =Q3+1.5(Q3-Q1);
[0025] S34: Take any intersection point A in , if the corresponding line segment OA in The length is greater than d min and less than d max , then the point A in is a valid intersection point, otherwise it is excluded, and all intersection points are screened in turn;
[0026] S35: Point A i1 , A i2 , A i3 ,......,A in Connect in sequence, if point A in has been excluded, then skip this point and directly change A in-1 With A in+1 The closed polygon formed by connecting the two points is the center point viewing polygon.
[0027] Preferably, in step 4, the calculation of the average open space radius R0 includes the following steps:
[0028] S41: For the valid intersection point A after the above screening in , record its axial sampling distance r in as the length of line segment OA in , for the invalid intersection point A in , record its axial sampling distance r in as 0, and finally obtain the valid axial sampling lengths r i1 , r i2 , φ i3 ,......, r in ;
[0029] S42: Calculate the average open space radius R0 of the street intersection, and the specific expression is:
[0030]
[0031] Furthermore, in step 5, the value range of the expansion coefficient k is 1.9 - 2.1.
[0032] Furthermore, in step 6, the construction of the central point panoramic sampling box includes the following steps:
[0033] S61: Set the central point panoramic sampling box as a cylinder, whose bottom surface is on the same horizontal plane as the building contour line, that is, at elevation 0, the midpoint of the bottom surface is the central point of the street intersection, and the bottom surface radius is R, so as to obtain the bottom surface of the central point panoramic sampling box;
[0034] S62: Set the height of the central point panoramic sampling box as the maximum value of the building heights within the acquisition area, denoted as H.
[0035] Furthermore, in step 7, the construction of the three-dimensional space model of the valid street intersection object includes the following steps:
[0036] S71: Stretch the heights of all building contours within the acquisition area to form the overall three-dimensional space model of the acquisition area;
[0037] S72: Select all buildings whose contour lines are tangent to or intersect with the central point panoramic polygon of this street intersection from the overall three-dimensional space model, and then cut the three-dimensional space models of these buildings with the central point panoramic sampling box corresponding to the valid street intersection object;
[0038] S73: Combine the obtained building three-dimensional space models with the central point panoramic polygon to obtain the three-dimensional space model of this street intersection, and associate and mark it with the corresponding street intersection number.
[0039] Beneficial effects: Compared with the prior art, the advantages of the present invention are as follows:
[0040] ① Wide adaptability: In the face of research areas with incomplete basic data, basic data for operation can be conveniently obtained, so that a three-dimensional space model of the research street can be quickly collected. It has a wide range of applications, and the difficulty of collecting data on research objects is low.
[0041] ② Strong self-adaptability: It can flexibly cope with street intersections of different scales and shapes, improve the automation degree of the definition process, avoid errors caused by human judgment or insufficient experience in traditional methods, and reduce the influence of manual intervention and subjective judgment.
[0042] ③ High intelligence: By automatically processing the information of the plan view through algorithms, it can accurately identify and define a reasonable street intersection range on a large scale, ensure the standardization in the collection process of urban streets of different scales and types, and enhance the scientificity and rationality of the research on urban streets. Brief description of the drawings
[0043] Figure 1 is the method flow chart of the present invention;
[0044] Figure 2 is the schematic diagram of identifying the center point of the street intersection of the present invention;
[0045] Figure 3 is the schematic diagram of sampling around the center point for the present invention;
[0046] Figure 4 is the schematic diagram of the sampling process from the effective center point of the street intersection to the surrounding building outlines of the present invention;
[0047] Figure 5 is the schematic diagram of the three-dimensional space model around a certain street intersection established by using Sketchup software of the present invention. Detailed implementation manners
[0048] The present invention will be further clarified below in conjunction with the drawings and specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and not to limit the scope of the present invention.
[0049] A method for large-scale definition of a street intersection model based on sampling around the center point, as Figures 1 to 5 shown, includes the following steps:
[0050] Step 1: Determine the collection range and obtain basic data. The basic data includes the layer information of the center points of street intersections, building outlines, and building heights within the collection area. Among them, the building outlines and the center points of street intersections should belong to the same height, that is, the z-axis is located at the 0 elevation. At the same time, the building outlines and the building heights form a one-to-one correspondence, that is, one building outline object corresponds to one building height data information.
[0051] Step 2: Identify and screen out the effective street intersection centers as panoramic view points, number them, and record the center point information.
[0052] S21: Obtain the street center line information, and get all the intersections within each street intersection in this layer through the street center line information. Assume that the intersection with only one intersection is a single-intersection street intersection, and the rest are multi-intersection street intersections. Record the distance between every two intersections in the multi-intersection street intersection as l n , where n is the number of pairs of the intersections; Compare l n with the given length parameter L. Consider the multi-intersection street intersections that meet all l n ≤ L and all single-intersection street intersections as effective street intersections; Usually, the value of the length parameter L is affected by the spatial scale of the street intersection, and usually takes values such as 5m, 10m, etc.
[0053] S22: For the effective street intersections with a single intersection, assume this intersection is the street intersection center; For the effective street intersections with two intersections, take the midpoint of the line segment formed by these two points as the street intersection center; For the effective street intersections with three or more intersections, take the centroid of the polygon formed by these intersections as the street intersection center to obtain the street intersection centers of all effective street intersections.
[0054] S23: Number the effective street intersections as i, where i = 1, 2..., then the street intersection center of the effective street intersection is denoted as O i , with coordinates (a i , b i1 ). Arrange the coordinates of all street intersection centers in descending order of the ordinate and number them with natural numbers.
[0055] Step 3: For each street intersection, set the interval angle Δr, and obtain the central panoramic polygon through continuous equal-angle panoramic sampling.
[0056] S31: Set Δr so that the value of 360° / Δr is a positive integer; The value of Δr is affected by the spatial scale of the street intersection, and usually takes values such as 20°, 15°, 12°, 10°, 7.2°, etc.
[0057] S32: Starting from the due north direction, with the street intersection center as the center, draw panoramic sampling rays clockwise according to the sampling interval angle, and record the first intersection of each ray with the surrounding building outline. If there is no intersection between the ray and the building outline, exclude this ray. Denote these intersections as A i1 , A i2 , A i3 , ……, A in , a total of n.
[0058] S33: Measure the length of the line segment from the street intersection center to each intersection, denoted as OA i1 , OAi2 , OA i3 , ……, OA in , and record the lower quartile of each of the said line segment lengths as Q1, and the upper quartile as Q3, and set the minimum buffer distance d min , the maximum sampling buffer distance d max , then:
[0059] d min = Q1 - 1.5(Q3 - Q1);
[0060] d max = Q3 + 1.5(Q3 - Q1).
[0061] S34: Take any intersection point A in , if the length of the line segment OA in corresponding to it is greater than d min and less than d max , then this point A in is a valid intersection point, otherwise exclude this point, and screen all intersection points in turn.
[0062] S35: Connect the points A i1 , A i2 , A i3 ,......, A in in sequence. If the point A in has been excluded, then directly connect A in-1 to A in+1 across this point, and the formed closed polygon is the central point panoramic polygon.
[0063] Step 4: Record and screen all valid street intersection panoramic line lengths of each street intersection, and calculate the average value as the street intersection average open space radius R0;
[0064] S41: For the valid intersection point A in after the above screening, record its axial sampling distance r in as the length of the line segment OA in . For the invalid intersection point A in , record its axial sampling distance r in as 0. Finally, obtain the effective axial sampling lengths r i1 , r i2 , r i3 ,......, r in .
[0065] S42: Calculate the street intersection average open space radius R0, and the specific expression is:
[0066]
[0067] Step 5: Set the expansion coefficient k and calculate the sampling radius R of all effective street intersection models, where R = k·R0, and the value of the expansion coefficient k is usually around 2.
[0068] Step 6: Construct a corresponding central point surrounding sampling box for all effective street intersection objects;
[0069] S61: Set the central point surrounding sampling box as a cylinder, whose bottom surface is on the same horizontal plane as the building contour line, that is, at elevation 0, the midpoint of the bottom surface is the central point of the street intersection, and the radius of the bottom surface is R, so as to obtain the bottom surface of the central point surrounding sampling box.
[0070] S62: Set the height of the central point surrounding sampling box as the maximum value of the building heights within the acquisition area, denoted as H.
[0071] Step 7: Combine the central point surrounding sampling box with the basic data to construct a three-dimensional space model of the effective street intersection object, and associate and mark it with the corresponding street intersection number.
[0072] S71: Stretch the heights of all building contours within the acquisition area to form an overall three-dimensional space model of the acquisition area;
[0073] S72: Select all the buildings whose contour lines are tangent to or intersect with the central point surrounding polygon of this street intersection from the overall three-dimensional space model, and then cut the three-dimensional space models of these buildings with the central point surrounding sampling box corresponding to the effective street intersection object;
[0074] S73: Combine the obtained three-dimensional space model of the building with the central point surrounding polygon to obtain the three-dimensional space model of this street intersection, and associate and mark it with the corresponding street intersection number.
[0075] Based on the central point surrounding sampling, the present invention can accurately measure and obtain a large number of three-dimensional space models of street intersections by introducing the equal-angle surrounding sight lines to calculate the average open space radius of street intersections and further define the street intersection models, providing a more rational scientific basis for the refined quantitative analysis of street intersection forms and their application in urban design and street intersection public space planning.
Claims
1. A large-scale definition method for street intersection models based on central point panoramic sampling, characterized in that It includes the following steps: Step 1: Determine the acquisition range and obtain the basic data, where the basic data includes the layer information of the street intersection center points, building outlines, and building heights within the acquisition area; Step 2: Identify and screen out the valid street intersection center points as panoramic view points, number them, and register the center point information; Step 3: For each street intersection, set the interval angle Δr, and obtain the center point panoramic polygon through continuous equal-angle panoramic sampling; Step 4: Record and screen the lengths of all valid street intersection panoramic lines of each street intersection, and calculate the average value as the average open space radius R0 of the street intersection; Step 5: Set the expansion coefficient k, and calculate the sampling radius R of all valid street intersection models, where R = k·R0; Step 6: Construct the corresponding center point panoramic sampling box for all valid street intersection objects; Step 7: Combine the center point panoramic sampling box with the basic data to construct the three-dimensional space model of the valid street intersection object, and associate and mark it with the corresponding street intersection number.
2. The large-scale definition method of an intersection model based on central point panoramic sampling according to claim 1, characterized in that: In Step 1, the building outline has the same height as the street intersection center point, and both of their z-axes are at the 0 elevation; the building outline and the building height are in a one-to-one correspondence relationship, and each building outline has a corresponding building height data information.
3. A method for large-scale definition of an intersection model based on central point panoramic sampling, as claimed in claim 1, wherein In Step 2, the screening of the valid street intersection center points includes the following steps: S21: Obtain the street centerline information, and obtain all the intersection points within each street intersection in the layer through the street centerline information. Let the street intersections with only one intersection point be single-intersection street intersections, and the rest be multi-intersection street intersections. Record the distance between every two intersection points in the multi-intersection street intersections as l n , where n is the number of pairs of the intersection points; Compare l n with the given length parameter L, and regard the multi-intersection street intersections that meet all l n ≤ L and all single-intersection street intersections as valid street intersections; S22: For a valid street intersection with a single intersection point, set this intersection point as the street intersection center point; for a valid street intersection with two intersection points, take the midpoint of the line segment formed by these two points as the street intersection center point; for a valid street intersection with three or more intersection points, take the centroid of the polygon formed by these intersection points as the street intersection center point to obtain the street intersection center points of all valid street intersections.
4. A method for large-scale definition of a street intersection model based on central point panoramic sampling according to claim 1 or 3, characterized in that: The valid street intersections are numbered as i, where i = 1, 2,..., and the center point of the valid street intersection is denoted as O i , with coordinates (a i , b i1 ). Arrange the coordinates of all street intersection center points in descending order of the ordinate and number them with natural numbers.
5. A large-scale definition method for a street intersection model based on central point panoramic sampling according to claim 3, characterized in that: In Step S21, the value range of the length parameter L is 5m to 10m.
6. A large-scale definition method for a street intersection model based on central point panoramic sampling according to claim 1, characterized in that, In Step 3, the acquisition of the center point panoramic polygon includes the following steps: S31: Set Δr to satisfy that the value of 360° / Δr is a positive integer; S32: Starting from the due north direction, with the center point of the street intersection as the center, draw panoramic sampling rays in the clockwise direction at the sampling interval angle, record the first intersection point of each ray with the surrounding building outline, and exclude the ray if there is no intersection point between the ray and the building outline. Denote these intersection points as A i1 , A i2 , A i3 ,......, A in , a total of n; S33: Measure the length of the line segment from the center point of the street intersection to each intersection point, denoted as OA i1 , OA i2 , OA i3 ,......, OA in , and record the lower quartile of each of the line segment lengths as Q1, and the upper quartile as Q3, and set the minimum buffer distance d min , the maximum sampling buffer distance d max , then: d min = Q1 - 1.5(Q3 - Q1); d max = Q3 + 1.5(Q3 - Q1); S34: Select any intersection point A in , if the length of the corresponding line segment OA in is greater than d min and less than d max , then this point A in is a valid intersection point, otherwise exclude this point, and screen all intersection points in turn; S35: Point A i1 , A i2 , A i3 , ..., A in Connect in sequence, if point A in has been excluded, then skip this point and directly change A in-1 With A in+1 The closed polygon formed by connecting the two points is the center point viewing polygon.
7. A large-scale definition method for a street intersection model based on central point panoramic sampling according to claim 6, characterized in that In Step 4, the calculation of the average open space radius R0 includes the following steps: S41: For the valid intersection point A screened as above in , record its axial sampling distance r in as the length of line segment OA in . For the invalid intersection point A in , record its axial sampling distance r in as 0. Finally, obtain the valid axial sampling lengths r i1 , r i2 , r i3 ,......, r in ; S42: Calculate the average open space radius R0 of the street intersection, and the specific expression is:
8. A method for large-scale definition of an intersection model based on central point panoramic sampling according to claim 1, characterized in that: In Step 5, the value range of the expansion coefficient k is 1.9 to 2.
1.
9. A method for large-scale definition of an intersection model based on central point panoramic sampling, as claimed in claim 1, wherein In Step 6, the construction of the center point panoramic sampling box includes the following steps: S61: Set the center point panoramic sampling box as a cylinder, whose bottom surface is on the same horizontal plane as the building outline, that is, at the 0 elevation, the midpoint of the bottom surface is the street intersection center point, and the bottom surface radius is R, so as to obtain the bottom surface of the center point panoramic sampling box; S62: Set the height of the center point panoramic sampling box as the maximum value of the building heights within the acquisition area, denoted as H.
10. A method for large-scale definition of an intersection model based on central point panoramic sampling, as claimed in claim 1, wherein In Step 7, the construction of the three-dimensional space model of the valid street intersection object includes the following steps: S71: Stretch the heights of all building outlines within the acquisition area to form the overall three-dimensional space model of the acquisition area; S72: Select all the buildings whose outline lines are tangent to or intersect with the center point panoramic polygon of the street intersection from the overall three-dimensional space model, and then cut the three-dimensional space models of these buildings with the center point panoramic sampling box corresponding to the valid street intersection object; S73: Combine the obtained three-dimensional building space model with the central point panoramic polygon to obtain the three-dimensional space model of the street intersection, and associate and mark it with the corresponding street intersection number.