High-density three-dimensional composite city morphological characteristic measurement method, calculation device and storage medium

Abstract

The invention relates to a high-density three-dimensional composite city morphological characteristic measurement method, a calculation device and a storage medium, and the measurement method comprises the steps: delimiting a three-dimensional recognition boundary, and obtaining original map data; performing screening processing on the original map data, and performing three-dimensional modeling in the identified boundary; measuring and calculating a three-dimensional characteristic measurement index; selecting a three-dimensional base coverage rate and a three-dimensional base plot ratio to construct a coordinate system, and dividing sample indexes into layers according to distribution characteristics; adopting a hierarchical clustering algorithm, and continuously iterating until all data are merged into one category; and storing data, establishing a three-dimensional city database, and keeping data update. Aiming at the morphological characteristics of urban three-dimensional composite development in the high-density urban updating process, the problems that the three-dimensional urban form cannot be accurately expressed and the three-dimensional urban form cannot be effectively and quantitatively analyzed in the urban design process in the prior art are solved.

Description

Technical Field

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

[0002] The three-dimensional development of urban space is an important spatial strategy to improve land use efficiency. It is not only manifested in the high-density aggregation and mixing of multiple functions and spaces under limited land resources, but also in the layered utilization and efficient connection in the vertical dimension. At the block level, it specifically presents cross-block aerial (or underground) corridors, vertically layered three-dimensional ground, and urbanized utilization of internal building space, breaking through the constraints of the flat street / plot, site / building morphological hierarchy. The three-dimensional form is highly dynamic and complex, which brings difficulties to fully understand and grasp the essential characteristics of high-quality cases of three-dimensional cities. Especially in the period of high-quality urban construction, how to create a new type of three-dimensional urban block model has put forward new requirements and challenges to the methodological system of morphological cognition, evaluation and design. Summary of the invention

[0003] In order to solve 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: S1. Delineate the three-dimensional recognition boundary and obtain original map data.

[0004] S2. Screen and process the original map data, extract the information required for three-dimensional modeling, and perform three-dimensional modeling within the identification boundary.

[0005] 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 level, the three-dimensional base surface connectivity and the three-dimensional base surface overlap.

[0006] 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.

[0007] S5. A hierarchical clustering algorithm is used to classify samples based on the stereo base layer order, stereo base connection and stereo base overlap indicators, and iterates continuously until all data are merged into one category.

[0008] S6. Store data, build a three-dimensional city database, and keep the data updated. It can make horizontal comparisons between existing three-dimensional city cases, and can also make vertical comparisons between the three-dimensional city design before and after the update to evaluate the update plan.

[0009] Furthermore, the calculation formula of the three-dimensional base surface coverage is: MPR=P / A, MPR is the three-dimensional base surface coverage, P is the three-dimensional base surface projection area, and A is the selected calculation area.

[0010] Furthermore, the calculation area A is set to the area of ​​a circle with a radius of 500 m.

[0011] Furthermore, the calculation formula of 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.

[0012] 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.

[0013] Furthermore, the calculation formula of the three-dimensional base surface connectivity is: MCI=N / S, MCI is the three-dimensional base surface connectivity, and N is the number of connection nodes.

[0014] Furthermore, the number of bidirectional connection nodes is recorded as 2, and the number of unidirectional connection nodes is recorded as 1.

[0015] Furthermore, the calculation formula of the three-dimensional base surface overlap is: MOI=B / S, where MOI is the three-dimensional base surface overlap.

[0016] The present invention also provides a computing device, including 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 as described above.

[0017] The present invention also provides a non-transitory machine-readable storage medium having executable codes stored thereon. When the executable codes are executed by a processor of an electronic device, the processor is caused to execute the method as described above.

[0018] 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 problem that the prior art cannot accurately describe the three-dimensional urban morphology and cannot effectively quantify and analyze the three-dimensional urban morphology in the process of urban design. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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 creative work.

[0020] 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; Figure 2 It is a three-dimensional city model in an embodiment of the present invention; Figure 3 It is a process battery pack for calculating the three-dimensional urban morphological characteristic index in the embodiment of the present invention; 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; 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; Figure 6 is a three-dimensional scatter plot of the connectivity, stacking and overlapping of five cluster sample nodes in an embodiment of the present invention; Figure 7 Schematic diagram of the three-dimensional base surface coverage in the present invention; Figure 8 It is a schematic diagram of the volume ratio of the solid base surface in the present invention; Fig. 9 It is a schematic diagram of the three-dimensional base layer steps in the present invention; Fig.10 It is a schematic diagram of the solid base surface connectivity in the present invention; Fig.11 It is a schematic diagram of the overlap of the three-dimensional base surfaces in the present invention. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] Embodiment 1:

[0023] This embodiment is a method for measuring the characteristics of high-density three-dimensional composite urban morphology, comprising the following steps: S1. Define the three-dimensional identification boundary and obtain the original map data. In this embodiment, the research boundary is defined by satellite maps, field surveys and visits, etc. The three-dimensional urban research boundary is determined by connecting the three-dimensional base surface. The three-dimensional base surface is in the underground layer or the air layer (not the ground layer), forming a continuous urban public space system, and the plots connected to it are included in the research scope. Then, through field surveys and mapping, downloading online map services (such as cadmapper, etc.), the original map data of the required research scope is obtained.

[0024] S2. Screening and processing the original map data, extracting the information required for three-dimensional modeling, and performing three-dimensional modeling within the identification boundary. In this embodiment, the obtained original map data is screened and processed to extract the information required for three-dimensional modeling. Figure 1-Figure 2 , all information is summarized into a DWG format map, and three-dimensional city range modeling is performed in Rhino. According to the identification of three-dimensional elements, the modeling layer is divided into three-dimensional base surface, horizontal link, etc.

[0025] 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 connection 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 and connection node layers of the three-dimensional urban rhino model established in step S2, calculate the three-dimensional base area, three-dimensional base projection area and the number of connection nodes respectively, and calculate the three-dimensional base coverage, volume ratio, layer order, connectivity and overlap indicators of the modeling case.

[0026] 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. 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.

[0027] Figure 4 The spatial distribution pattern of the sample data points of the three-dimensional blocks in different regions is presented on the two-dimensional scatter plot. The scatter plot is based on the three-dimensional base surface coverage rate as the horizontal axis and the three-dimensional base surface volume ratio as the vertical axis. According to its distribution characteristics, the sample data is divided into four cluster types, each of which reflects the specific three-dimensional project development intensity and spatial agglomeration characteristics.

[0028] Group A includes La Defense in Paris and Futian Center in Shenzhen, representing high-intensity large-scale development of three-dimensional projects, and the common feature of the cases is a large-scale outdoor or underground three-dimensional base system. The common feature of samples in Group A is ultra-high concentration, that is, ultra-high plot ratio and ultra-high coverage.

[0029] Group B includes samples such as Shinjuku in Tokyo, Japan and Umeda in Osaka, Qianjiang New Town in Hangzhou, China, Beijing CBD and Zhujiang New Town in Guangzhou, representing a series of high-intensity three-dimensional project types. The common characteristics of the cases are continuous and relatively large-scale aerial bases or underground spaces, or development dominated by large-scale complexes. The common characteristics of samples in Group B are high concentration, that is, high plot ratio and high coverage rate.

[0030] Group C includes West Kowloon in Hong Kong, China, Wujiaochang in Shanghai, Stratford Station in London, UK, and Tokyo Station in Tokyo, Japan, representing a series of medium-intensity three-dimensional project types, and the common feature of the cases is that they are led by one or several large-scale complexes. The common feature of the samples in Group C is that they have medium concentration, that is, medium plot ratio and medium coverage.

[0031] The spatial aggregation effect of group d samples is average, but there are differences in characterization. The development of London's Canary Wharf, Hong Kong's Tung Chung, Tsing Yi and Tsim Sha Tsui and other blocks are obviously based on the rail station complex. Shibuya in Tokyo, Japan, Admiralty and Taikoo City in Hong Kong, China, Lujiazui area in Shanghai, Wujiaochang in Shanghai, Erqi Square in Zhengzhou, etc. do not have obvious cores, but connect the development land with different property rights with relatively small-scale, continuous aerial or underground corridor systems. It forms a three-dimensional pedestrian network with local complexes within a certain range.

[0032] S5. Using a hierarchical clustering algorithm, classify the samples based on the three-dimensional base surface 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. This embodiment uses a hierarchical clustering algorithm with process visualization advantages (hierarchical clustering algorithm in SPSS software) to classify samples based on three variables: three-dimensional base surface layer order, three-dimensional base surface connectivity and three-dimensional base surface overlap.

[0033] 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, which is similar to a hierarchical nested clustering tree. The significant advantage of hierarchical clustering is that it can present the information of the entire clustering algorithm process at one time, which is especially suitable for data sets with small sample sizes.

[0034] like Figure 5 As shown in the figure, when the iterative calculation is performed for the eighth 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.

[0035] 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.

[0036] 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, Canary Wharf in London and Tsim Sha Tsui in Hong Kong, China, which are transportation hubs connected horizontally by underground corridors. The common characteristics of the samples are low overlap, low hierarchy and low connectivity.

[0037] 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 complexes, characterized by high connectivity, low level and high overlap.

[0038] Group 4 includes Admiralty in Hong Kong, China; Taikoo in Hong Kong, China; Shibuya in Tokyo; Umeda in Osaka; and Taikoo Li in Chengdu. These samples adopt a network-type corridor connecting multi-layer base complexes. Their common characteristics are high connectivity, high level and high overlap.

[0039] Group 5 includes La Defense in Paris, which is a large-scale two-story building, and West Kowloon, Tsing Yi and Tung Chung in Hong Kong, China, which are mainly developed in multi-story complexes. The common characteristics of these samples are high-level order, high overlap and low connectivity.

[0040] S6. Store data, build a three-dimensional city database, and keep the data updated. It can make horizontal comparisons between existing three-dimensional city cases, and can also make vertical comparisons between the three-dimensional city design before and after the update to evaluate the update plan.

[0041] For details, see Figure 7 The calculation formula of the three-dimensional base surface coverage is: MPR=P / A, where MPR is the three-dimensional base surface coverage, which expresses the proportion of the block area with multiple layers of base surfaces in a unit area, P is the projection area of ​​the three-dimensional base surface, and A is the selected calculation area. Furthermore, the calculation area A is set to a circular area with a radius of 500m.

[0042] See also Figure 8 The 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 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.

[0043] See also Fig. 9 The calculation formula of the three-dimensional base surface layer step is: MLI=S / P, MLI is the three-dimensional base surface layer step, which represents the degree of overlap between different base surfaces.

[0044] See also Fig.10, the calculation formula of the stereo base surface connectivity is: MCI=N / S, MCI is the stereo base surface connectivity, which measures the degree of stereo connection between each plot in a stereo block, and N is the number of connection nodes. There are two specific types of bidirectional connections and unidirectional connections. The former connects two plots, and the number of connections is 2; the latter connects the stereo base and the plot without a stereo base, and the number of connections is 1.

[0045] See also Fig.11 The calculation formula of the three-dimensional base surface overlap is: MOI=B / S, MOI is the three-dimensional base surface overlap, which reflects the degree of contribution of the development land to urban public activities. The specific forms of overlap include indoor space and outdoor space.

[0046] The characteristic elements involved in identifying the three-dimensional urban form in this embodiment include: Ground and base: The "ground layer" is defined as the original natural terrain surface, or the surface of artificial structures that have been transformed into the natural terrain. The "base" refers to the reference surface that carries public activities and functions. In a three-dimensional city, in addition to the ground as the base, there are also three-dimensional bases in the air and underground, which increase the carrying area of ​​public activities in the vertical dimension.

[0047] Public areas and development land: Public land such as roads, squares, and green spaces and development plots and their internal buildings constitute the permanent form of the city. Generally speaking, the former is built by the government and its development platform and has more public functions, while the latter is built by developers and has relatively low public nature. However, the division of labor in a three-dimensional city does not follow the principle of planar division. The development of plots occupied or adjacent to railway stations, tracks, and bus stations often requires the government and its development platform to lead the construction. Plots and buildings owned by private developers often contribute part of the space to integrate into the city, so the development plots will also have strong public service functions.

[0048] Three-dimensional base and connection nodes: The three-dimensional base is the premise for judging whether the urban area is three-dimensional, and both public areas and development land can undertake the construction of three-dimensional base. Its establishment requires the following: 1) It must be a continuous space that is detached from the ground and completely public; 2) It connects 2 or more blocks (areas surrounded by urban municipal roads) or 2 or more development plots through the non-ground layer. Connection nodes are elements for establishing spatial connections between different bases. The more connection nodes per unit area, the higher the connection efficiency of the base.

[0049] Embodiment 2:

[0050] 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.

[0051] 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 a customized circuit, such as an application-specific integrated circuit (ASIC) or a field programmable gate array (FPGA).

[0052] The memory may include various types of storage units, such as system memory, read-only memory (ROM), and permanent storage. Among them, ROM can 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 the stored instructions and data even after 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 a permanent storage device. In some 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 a dynamic random access memory. The system memory may store some or all instructions and data required by the processor at run time. 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 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 laser disc (CD), a read-only digital versatile disc (e.g., DVD-ROM, double-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. The computer-readable storage medium does not include carrier waves and transient electronic signals transmitted wirelessly or wired.

[0053] The memory stores executable codes thereon, and when the executable codes are executed by the processor, the processor is enabled to execute the above method.

[0054] Embodiment 3:

[0055] This embodiment provides a non-transitory machine-readable memory having executable codes stored thereon. When the executable codes are executed by a processor of an electronic device, the processor is caused to execute the above method.

[0056] A non-temporary 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.

[0057] 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 a combination of both.

[0058] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

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, define the three-dimensional recognition boundary and obtain the original map data; S2, screening and processing the original map data, extracting the information required for three-dimensional modeling, and performing three-dimensional 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 order, 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 the distribution characteristics; S5. Use a hierarchical clustering algorithm to classify samples based on the three-dimensional base layer order, three-dimensional base connection and three-dimensional base overlap indicators, and iterate 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 morphology characteristic measurement method according to claim 1 is characterized in that: The calculation formula of the three-dimensional base surface coverage is: MPR=P / A, 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 high-density three-dimensional composite urban morphology characteristic measurement method 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 high-density three-dimensional composite urban morphology characteristic measurement method according to claim 1 is characterized in that: The calculation formula for the three-dimensional base surface floor area ratio is: MAR=S / A, MAR is the three-dimensional base surface floor area 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 high-density three-dimensional composite urban morphology feature measurement method 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 high-density three-dimensional composite urban morphology characteristic measurement method according to claim 1 is characterized in that: The calculation formula of the three-dimensional base surface connectivity is: MCI=N / S, MCI is the three-dimensional base surface connectivity, and N is the number of connected nodes.

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

8. The high-density three-dimensional composite urban morphology characteristic measurement method according to claim 1 is characterized in that: The calculation formula of the three-dimensional base surface overlap is: MOI=B / S, where MOI is the three-dimensional base surface 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: An executable code is stored thereon, and when the executable code is executed by a processor of an electronic device, the processor is caused to execute any one of the methods described in claims 1-8.

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