A method, computing device and storage medium for measuring characteristics of high-density three-dimensional composite urban form

Abstract

The present invention relates to a method, computing device, and storage medium for measuring the morphological characteristics of high-density, three-dimensional, and composite cities. The method comprises: defining a three-dimensional identification boundary and obtaining original map data; screening and processing the original map data to perform three-dimensional modeling within the identification boundary; calculating three-dimensional characteristic measurement indicators; selecting a three-dimensional base surface coverage rate and a three-dimensional base surface volume ratio to construct a coordinate system, and dividing the sample indicators into hierarchical levels according to their distribution characteristics; employing a hierarchical clustering algorithm and continuously iterating until all data are merged into a single category; storing the data, establishing a three-dimensional city database, and maintaining data updates. The present invention addresses the morphological characteristics of three-dimensional composite urban development during high-density urban renewal, resolving the problems of prior art in accurately expressing three-dimensional urban morphology and effectively quantifying and analyzing three-dimensional urban morphology during urban design.

Description

Technical Field

[0001] The present invention relates to the technical field of high-density urban renewal, and in particular to a method, a computing device and a storage medium for measuring the morphological characteristics of a high-density three-dimensional composite city. Background Art

[0002] The three-dimensional development of urban space is a key spatial strategy for improving land use efficiency. It not only manifests itself in the high-density aggregation and intermingling of diverse functions and spaces within limited land resources, but also in the vertical dimension, where layered utilization and efficient connections are achieved. At the block level, this manifests itself in interblock aerial (or underground) corridors, vertically layered three-dimensional ground surfaces, and the urbanized utilization of building interiors, transcending the constraints of the flattened street / plot and site / building hierarchies. The high dynamism and complexity of three-dimensional morphology present challenges in fully understanding and grasping the essential characteristics of high-quality examples of three-dimensional urban development. Especially in the era of high-quality urban development, the creation of new models for three-dimensional urban blocks poses new requirements and challenges to the methodological frameworks for understanding, evaluating, and designing morphology. Summary of the Invention

[0003] In order to address the above-mentioned deficiencies in the prior art, the present invention provides a method for measuring the characteristics of high-density three-dimensional composite urban morphology, comprising the following steps:

[0004] S1. Delineate the three-dimensional recognition boundary and obtain original map data.

[0005] S2. Filter and process the original map data, extract the information required for three-dimensional modeling, and perform three-dimensional modeling within the identification boundary.

[0006] S3. Calculate the three-dimensional feature measurement indicators, including the three-dimensional base surface coverage, the three-dimensional base surface volume ratio, the three-dimensional base surface layer degree, the three-dimensional base surface connectivity and the three-dimensional base surface overlap.

[0007] S4. Select the three-dimensional base surface coverage rate and the three-dimensional base surface volume ratio to construct a coordinate system, and divide the sample indicators into levels according to their distribution characteristics.

[0008] S5. Use a hierarchical clustering algorithm to classify samples based on the three-dimensional base layer order, three-dimensional base surface connectivity and three-dimensional base surface overlap indicators, and iterate continuously until all data are merged into one category.

[0009] S6. Store data, build a 3D city database, and keep it updated. This allows for horizontal comparisons of existing 3D city cases, as well as vertical comparisons of the pre- and post-update states of 3D city designs, to evaluate update plans.

[0010] Furthermore, the calculation formula of the three-dimensional base surface coverage is: MPR=P / A, where MPR is the three-dimensional base surface coverage, P is the three-dimensional base surface projection area, and A is the selected calculation area.

[0011] Furthermore, the calculation area A is set to the area of a circle with a radius of 500m.

[0012] Furthermore, the calculation formula for the three-dimensional base surface volume ratio is: MAR=S / A, MAR is the three-dimensional base surface volume ratio, S is the three-dimensional base surface area; S=B+U, B is the three-dimensional base surface area borne by the development land, and U is the three-dimensional base surface area borne by the urban public area.

[0013] Furthermore, the calculation formula of the three-dimensional base surface layer step is: MLI=S / P, where MLI is the three-dimensional base surface layer step.

[0014] Furthermore, the calculation formula of the three-dimensional base surface connectivity is: MCI=N / S, where MCI is the three-dimensional base surface connectivity and N is the number of connection nodes.

[0015] Furthermore, the number of bidirectional connection nodes is recorded as 2, and the number of unidirectional connection nodes is recorded as 1.

[0016] Furthermore, the calculation formula for the three-dimensional base plane overlap is: MOI=B / S, where MOI is the three-dimensional base plane overlap.

[0017] The present invention also provides a computing device, comprising a processor and a memory, wherein the memory stores executable code, and when the executable code is executed by the processor, the processor executes the method described above.

[0018] The present invention also provides a non-transitory machine-readable storage medium having executable code stored thereon. When the executable code is executed by a processor of an electronic device, the processor is caused to execute the method described above.

[0019] The present invention provides a method for measuring the morphological characteristics of urban three-dimensional complex development in the process of high-density urban renewal, which solves the problems that the existing technology cannot accurately express the three-dimensional urban morphology and cannot effectively quantify the three-dimensional urban morphology in the urban design process. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0021] Figure 1 It is a summary diagram of the boundary range of the three-dimensional research and related three-dimensional elements in the embodiment of the present invention;

[0022] Figure 2 It is a three-dimensional city model in an embodiment of the present invention;

[0023] Figure 3 It is a process battery pack for calculating the three-dimensional urban morphological characteristic index in the embodiment of the present invention;

[0024] Figure 4 is a scatter plot of the results of the three-dimensional base surface coverage and the three-dimensional base surface volume ratio of the samples in the embodiment of the present invention;

[0025] Figure 5 It is a clustering tree diagram showing the hierarchical clustering results of sample level, connectivity and overlap in an embodiment of the present invention;

[0026] Figure 6 is a three-dimensional scatter plot of the connectivity, stacking and overlap of five cluster sample nodes in an embodiment of the present invention;

[0027] Figure 7 Schematic diagram of the three-dimensional base surface coverage in the present invention;

[0028] Figure 8 Schematic diagram of the volume ratio of the solid base surface in the present invention;

[0029] Figure 9 Schematic diagram of the three-dimensional base layer steps in the present invention;

[0030] Figure 10 Schematic diagram of the solid base surface connectivity in the present invention;

[0031] Figure 11 It is a schematic diagram of the overlap of the three-dimensional base surfaces in the present invention. DETAILED DESCRIPTION

[0032] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0033] Example 1:

[0034] This embodiment is a method for measuring the characteristics of high-density three-dimensional composite urban morphology, comprising the following steps:

[0035] S1. Delineate the 3D identification boundary and obtain original map data. In this embodiment, the research boundary is defined using methods such as satellite maps and field research visits. The 3D urban research boundary is determined by connecting 3D base surfaces. These base surfaces form a continuous urban public space system in the underground or aerial layers (not the ground layer), and all connected plots are included in the research scope. Then, through field research and mapping, and by downloading online map services (such as cadmapper), obtain the original map data for the required research area.

[0036] S2. Screening and processing the original map data to extract the information required for 3D modeling and perform 3D modeling within the identification boundary. In this embodiment, the obtained original map data is screened and processed to extract the information required for 3D modeling. Figure 1-Figure 2 All the information was compiled into a DWG map and three-dimensional city modeling was performed in Rhino. Based on the identification of three-dimensional elements, the modeling layers were divided into three-dimensional base surfaces, horizontal links, etc.

[0037] S3, calculate the three-dimensional feature measurement index, including the three-dimensional base surface coverage, three-dimensional base surface volume ratio, three-dimensional base surface layer level, three-dimensional base surface connectivity and three-dimensional base surface overlap. In this embodiment, the three-dimensional feature measurement index is calculated by running a calculation program in Grasshopper of Rhino, see Figure 3 , use Grasshopper to build a battery pack, identify the development land-base surface and connection node layers of the three-dimensional urban Rhino model established in step S2, calculate the three-dimensional base surface area, three-dimensional base surface projection area and the number of connection nodes respectively, and calculate the three-dimensional base surface coverage rate, volume ratio, layer level, connectivity and overlap indicators of the modeling case.

[0038] S4. Select the three-dimensional base surface coverage rate and the three-dimensional base surface volume ratio to build a coordinate system, and divide the sample indicators into levels according to their distribution characteristics. Figure 4 In this embodiment, the sample index values are classified into four levels to reveal the differences in the degree of spatial aggregation of each sample. The specific classification standard can be manual experience classification or classification by setting a corresponding index range.

[0039] Figure 4 The spatial distribution patterns of 3D block sample data points from different regions are presented on a two-dimensional scatter plot, with the 3D base area coverage ratio as the horizontal axis and the 3D base area ratio as the vertical axis. Based on their distribution characteristics, the sample data are divided into four cluster types, each reflecting specific 3D project development intensity and spatial agglomeration characteristics.

[0040] Cluster A, including La Défense in Paris and Futian Center in Shenzhen, represents high-intensity, large-scale, three-dimensional projects. These examples generally feature large-scale, outdoor or underground three-dimensional surface systems. Cluster A samples share a common characteristic: ultra-high concentration, defined by extremely high floor area ratios and coverage ratios.

[0041] Cluster B, including examples such as Shinjuku in Tokyo and Umeda in Osaka, China, Qianjiang New Town in Hangzhou, China, Beijing's CBD, and Zhujiang New Town in Guangzhou, represents a range of high-intensity, three-dimensional project types. These examples are generally characterized by continuous, relatively large-scale aerial podiums or underground spaces, or by development dominated by large-scale complexes. Cluster B examples share a high degree of agglomeration, characterized by high floor area ratios and high coverage ratios.

[0042] Cluster C, encompassing West Kowloon in Hong Kong, China, Wujiaochang in Shanghai, Stratford Station in London, England, and the Tokyo Station area in Tokyo, Japan, represents a range of medium-intensity, three-dimensional developments, generally characterized by one or more large-scale mixed-use developments leading the development. Cluster C samples share a common characteristic of medium concentration, meaning a medium plot ratio and coverage ratio.

[0043] The spatial aggregation effect of cluster d samples is average, but there are differences in their characterization. Development in neighborhoods such as London's Canary Wharf and Hong Kong's Tung Chung, Tsing Yi, and Tsim Sha Tsui is clearly centered around rail station complexes. Areas like Tokyo's Shibuya, Hong Kong's Admiralty and Taikoo Shing, Shanghai's Lujiazui area, Wujiaochang, and Zhengzhou's Erqi Square lack a distinct core. Instead, a relatively small, continuous system of aerial or underground corridors connects development sites of varying ownership. This, combined with localized complexes, forms a three-dimensional pedestrian network within a certain range.

[0044] S5. Use a hierarchical clustering algorithm to classify samples based on the metrics of 3D surface order, 3D surface connectivity, and 3D surface overlap. Repeat the process until all data is merged into a single category. This example uses a hierarchical clustering algorithm (a hierarchical clustering algorithm in SPSS software) with the advantage of process visualization to classify samples based on three variables: 3D surface order, 3D surface connectivity, and 3D surface overlap.

[0045] Hierarchical clustering is a type of clustering algorithm. It calculates the similarity between data points and merges the two most similar data points among all data points. It continuously iterates until all data are merged into one category, forming a hierarchical clustering structure, similar to a hierarchical nested clustering tree. The significant advantage of hierarchical clustering is that it can present information about the entire clustering algorithm process at one time, which is especially suitable for data sets with small sample sizes.

[0046] like Figure 5As shown, when the iterative calculation is carried out for the 8th time, the sample data are divided into five groups. The size and distribution of the index values of each group are shown in the three-dimensional scatter plot. Figure 6 shown.

[0047] Cluster 1 includes Wujiaochang, Lujiazui, Shapingba, Qianjiang New Town and Beijing CBD in China, Stratford Station in London and Shinjuku area in Tokyo. These samples all show a pattern of local connection of the base surface of the complex, with common characteristics of high overlap, low hierarchy and low connectivity.

[0048] Group 2 includes Shenzhen Futian Center, Guangzhou Zhujiang New Town and Zhengzhou Erqi Square, which are domestic complexes connected by underground corridors, as well as Tokyo Station in Japan, London Canary Wharf and Tsim Sha Tsui in Hong Kong, China, which are transportation hubs connected by underground corridors. The common characteristics of the samples are low overlap, low hierarchy and low connectivity.

[0049] Cluster 3 includes Shatin and Central in Hong Kong, China, and Roppongi and Shiodome in Tokyo. It presents a network of corridors connecting single-story base complexes, characterized by high connectivity, low hierarchy and high overlap.

[0050] Cluster 4 includes Admiralty, Hong Kong, China; Taikoo, Hong Kong, China; Shibuya, Tokyo; Umeda, Osaka; and Taikoo Li, Chengdu. These samples adopt a network-type corridor connecting multi-layer base complexes. Their common characteristics are high connectivity, high level and high overlap.

[0051] Cluster 5 includes La Défense in Paris, where large, monolithic two-story developments are employed, and West Kowloon, Tsing Yi, and Tung Chung in Hong Kong, China, where multi-story, mixed-use developments are the primary model. These examples share common characteristics: high levels of hierarchy, high overlap, and low connectivity.

[0052] S6. Store data, build a 3D city database, and keep it updated. This allows for horizontal comparisons of existing 3D city cases, as well as vertical comparisons of the pre- and post-update states of 3D city designs, to evaluate update plans.

[0053] For details, see Figure 7 The formula for calculating the three-dimensional base surface coverage is: MPR = P / A, where MPR is the three-dimensional base surface coverage ratio, which expresses the proportion of block area with multiple layers of base surfaces within a unit area. P is the projected area of the three-dimensional base surface, and A is the selected calculation area. Furthermore, the calculation area A is set to the area of a circle with a radius of 500m.

[0054] See also Figure 8The calculation formula of the three-dimensional base surface volume ratio is: MAR=S / A, MAR is the three-dimensional base surface volume ratio, which characterizes the overall strength of the public base surface in the three-dimensional block, and S is the three-dimensional base surface area; S=B+U, B is the three-dimensional base surface area borne by the development land, and U is the three-dimensional base surface area borne by the urban public area.

[0055] See also Figure 9 The calculation formula of the three-dimensional base surface layer step is: MLI=S / P, where MLI is the three-dimensional base surface layer step, which represents the degree of overlap between different base surfaces.

[0056] See also Figure 10 The formula for calculating the 3D surface connectivity is: MCI = N / S, where MCI is the 3D surface connectivity, which measures the degree of 3D connectivity between plots within a 3D block, and N is the number of connected nodes. There are two specific types of connections: bidirectional and unidirectional. The former connects two plots and has a connection count of 2; the latter connects a 3D surface with a plot without a 3D surface and has a connection count of 1.

[0057] See also Figure 11 The calculation formula for the three-dimensional base surface overlap is: MOI=B / S, where MOI is the three-dimensional base surface overlap, which reflects the degree to which the developed land contributes to urban public activities. The specific forms of overlap include indoor space and outdoor space.

[0058] The characteristic elements involved in identifying the three-dimensional urban form in this embodiment include:

[0059] Ground and base: The "ground layer" is defined as the original natural terrain surface, or the surface of artificial structures that have been modified and integrated into the natural terrain. The "base" refers to the base surface that supports public activities and functions. In a three-dimensional city, in addition to the ground as a base surface, three-dimensional base surfaces are also derived in the air and underground, increasing the vertical area supporting public activities.

[0060] Public areas and development land: Public land such as roads, squares, and green spaces, along with development plots and the buildings within them, constitute the permanent urban form. Generally speaking, the former is built by the government and its development platforms and serves a greater public purpose, while the latter is built by developers and has a relatively low degree of publicness. However, the division of labor in a three-dimensional city does not follow the principle of planar division. The development of land occupied by or adjacent to train stations, tracks, and bus stops often requires the government and its development platforms to lead the construction. Land and buildings owned by private developers often contribute some space to the city, so development plots also have strong public service functions.

[0061] Three-dimensional surfaces and connection nodes: A three-dimensional surface is the prerequisite for determining whether an urban area is three-dimensional. Both public areas and developed land can be used to construct a three-dimensional surface. Its existence requires: 1) it must be a continuous, completely public space detached from the ground; and 2) it must connect two or more city blocks (areas enclosed by urban roads) or two or more development plots through a non-ground layer. Connection nodes are the elements that establish connections between different surface spaces. The greater the number of connection nodes per unit area, the higher the connection efficiency of the surface.

[0062] Example 2:

[0063] This embodiment is a computing device, including a processor and a memory, wherein the memory stores codes for executing the method in the above embodiment.

[0064] The processor may be a multi-core processor or may include multiple processors. In some embodiments, the processor may include a general-purpose main processor and one or more special coprocessors, such as a graphics processing unit (GPU), a digital signal processor (DSP), etc. In some embodiments, the processor may be implemented using customized circuits, such as application-specific integrated circuits (ASICs) or field-programmable gate arrays (FPGAs).

[0065] The memory may include various types of storage units, such as system memory, read-only memory (ROM), and permanent storage devices. ROM may store static data or instructions required by the processor or other modules of the computer. The permanent storage device may be a readable and writable storage device. The permanent storage device may be a non-volatile storage device that does not lose stored instructions and data even if the computer is powered off. In some embodiments, the permanent storage device uses a large-capacity storage device (such as a magnetic or optical disk, flash memory) as the permanent storage device. In other embodiments, the permanent storage device may be a removable storage device (such as a floppy disk, optical drive). The system memory may be a readable and writable storage device or a volatile readable and writable storage device, such as dynamic random access memory. The system memory may store some or all instructions and data required by the processor during operation. In addition, the memory may include any combination of computer-readable storage media, including various types of semiconductor memory chips (DRAM, SRAM, SDRAM, flash memory, programmable read-only memory), and magnetic disks and / or optical disks may also be used. In some embodiments, the memory may include a readable and / or writable removable storage device, such as a compact disc (CD), a read-only digital versatile disc (e.g., DVD-ROM, dual-layer DVD-ROM), a read-only Blu-ray disc, an ultra-density optical disc, a flash memory card (e.g., SD card, mini SD card, Micro-SD card, etc.), a magnetic floppy disk, etc. Computer-readable storage media do not include carrier waves and transient electronic signals transmitted wirelessly or wired.

[0066] The memory stores executable codes thereon, and when the executable codes are executed by the processor, the processor is enabled to perform the above method.

[0067] Example 3:

[0068] This embodiment provides a non-transitory machine-readable memory having executable code stored thereon. When the executable code is executed by a processor of an electronic device, the processor is caused to execute the above method.

[0069] A non-transitory machine-readable memory (or computer-readable memory, or machine-readable memory) having executable code (or computer program, or computer instruction code) stored thereon, which, when executed by a processor of an electronic device (or computing device, server, etc.), enables the processor to perform the various steps of the above-mentioned method according to the present invention.

[0070] Those skilled in the art will further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the disclosure herein may be implemented as electronic hardware, computer software, or combinations of both.

[0071] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A method for measuring the characteristics of high-density three-dimensional composite urban morphology, characterized in that: The following steps are involved: S1. Delineate the three-dimensional recognition boundary and obtain original map data; S2. Screening and processing the original map data, extracting the information required for 3D modeling, and performing 3D modeling within the identification boundary; S3. Calculate the three-dimensional characteristic measurement indicators, including three-dimensional base surface coverage, three-dimensional base surface volume ratio, three-dimensional base surface layer level, three-dimensional base surface connectivity, and three-dimensional base surface overlap; S4. Select the three-dimensional base surface coverage rate and the three-dimensional base surface volume ratio to construct a coordinate system, and divide the sample indicators into levels according to their distribution characteristics; S5. Use a hierarchical clustering algorithm to classify samples based on the three-dimensional base layer order, three-dimensional base surface connectivity, and three-dimensional base surface overlap indicators, and iterate continuously until all data are merged into one category; S6. Store data, build a three-dimensional city database, and keep the data updated.

2. The high-density three-dimensional composite urban morphological characteristics measurement method according to claim 1 is characterized in that: The calculation formula of the three-dimensional base surface coverage is: MPR=P / A, where MPR is the three-dimensional base surface coverage, P is the three-dimensional base surface projection area, and A is the selected calculation area.

3. The method for measuring the characteristics of high-density three-dimensional composite urban morphology according to claim 2 is characterized in that: The calculation area A is set to the area of a circle with a radius of 500m.

4. The method for measuring characteristics of high-density three-dimensional composite urban morphology according to claim 1 is characterized in that: The calculation formula for the three-dimensional base surface volume ratio is: MAR=S / A, MAR is the three-dimensional base surface volume ratio, S is the three-dimensional base surface area; S=B+U, B is the three-dimensional base surface area borne by the development land, and U is the three-dimensional base surface area borne by the urban public area.

5. The method for measuring characteristics of high-density three-dimensional composite urban morphology according to claim 1 is characterized in that: The calculation formula of the three-dimensional base surface layer step is: MLI=S / P, where MLI is the three-dimensional base surface layer step.

6. The method for measuring characteristics of high-density three-dimensional composite urban morphology according to claim 1 is characterized in that: The calculation formula of the three-dimensional base surface connectivity is: MCI=N / S, where MCI is the three-dimensional base surface connectivity and N is the number of connected nodes.

7. The method for measuring characteristics of high-density three-dimensional composite urban morphology according to claim 6, characterized in that: The number of connections for bidirectionally connected nodes is recorded as 2, and the number of connections for unidirectionally connected nodes is recorded as 1.

8. The method for measuring characteristics of high-density three-dimensional composite urban morphology according to claim 1 is characterized in that: The calculation formula of the three-dimensional base plane overlap is: MOI=B / S, where MOI is the three-dimensional base plane overlap.

9. A computing device, characterized in that: The method comprises a processor and a memory, wherein the memory stores executable codes, and when the executable codes are executed by the processor, the processor executes the method according to any one of claims 1 to 8.

10. A non-transitory machine-readable storage medium, characterized in that Executable codes are stored thereon, and when the executable codes are executed by a processor of an electronic device, the processor is caused to execute the method according to any one of claims 1 to 8.

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