Method for measuring urban space complexity and construction intensity

Abstract

The application discloses a kind of urban space complexity and construction intensity measurement method.Cities are divided into more than one, contour closed polygon space, to obtain basic space unit;Obtain the urban space characteristic index in each basic space unit, using the urban space characteristic index, generate the urban space characteristic index summary table of each basic space unit;c.The data in each space index summary table is standardized according to linear normalization method, then weighted summation is carried out to corresponding index by equal weight method, and the urban space complexity of each basic space unit is quantified USC And urban construction intensity UCI The application avoids the problems that the traditional urbanization index ignores the vertical space change of city and cannot consider the three-dimensional space form of building, leading to the problems that the urbanization level cannot be comprehensively reflected, the interval difference of index cannot be distinguished, the urban space unit planning and updating under the guidance of high-quality development is inefficient and the like.

Description

Technical Field

[0001] This invention relates to the fields of urban planning and urban ecology, and in particular to a method for calculating urban spatial complexity and construction intensity. Background Technology

[0002] Urban construction intensity is one of the urbanization indicators based on land use and is an important measure of the intensity of urban development and construction. In urban ecology research and planning practice, indicators are mainly used to characterize the level of urbanization, primarily examining its impact on various urban ecological environments. However, currently, urban construction intensity is mainly measured by the proportion of impermeable surface area. This quantitative method only considers the transformation of urban land use attributes and, to a certain extent, represents the level of urbanization, but it ignores a very important component of the urban environment—buildings. Due to their three-dimensional characteristics, the construction intensity and spatial complexity of urban units per unit area vary greatly. These differences directly affect light, temperature, and wind in the urban environment, thus impacting the suitability and comfort of the urban ecological environment. Moreover, with the increasing sophistication of urban management, current methods are becoming increasingly inadequate to meet the corresponding requirements. Therefore, constructing urban construction intensity based on three-dimensional building data is of great significance for objectively understanding the characteristics of the urban environment and its impact on the urban ecosystem. Summary of the Invention

[0003] The purpose of this invention is to provide a method for measuring urban spatial complexity and construction intensity. This invention avoids the problems of traditional urbanization indicators neglecting vertical spatial changes in cities and failing to take into account the three-dimensional spatial form of buildings, which leads to problems such as not being able to fully reflect the level of urbanization, being unable to distinguish differences between indicator ranges, and inefficient urban spatial unit planning and renewal under the guidance of high-quality development.

[0004] The technical solution of this invention: a method for calculating urban spatial complexity and construction intensity, comprising the following steps:

[0005] a. Divide the urban space into one or more closed polygonal spaces to obtain basic spatial units;

[0006] b. Obtain urban spatial characteristic indicators within each basic spatial unit, and use these indicators to generate a summary table of urban spatial characteristic indicators for each basic spatial unit; the urban spatial characteristic indicators include: the area S of the basic spatial unit, the impermeable surface area S0, and the area S0 of the impermeable surface. I The following are the building quantities (BN), building footprint (A), building height variation (BHO), total building volume (TBV), building volume density (BVD), and building layout complexity (BLC).

[0007] c. Standardize the data in the summary tables of various spatial indicators using linear normalization, and then sum the corresponding indicators using equal weights to quantify the urban spatial complexity (USC) and urban construction intensity (UCI) of each basic spatial unit.

[0008] In step a of the aforementioned method for calculating urban spatial complexity and construction intensity, the basic spatial unit is obtained by dividing the urban area based on urban roads or urban planning control units, and the basic spatial unit includes at least one building.

[0009] In step c of the aforementioned method for measuring urban spatial complexity and construction intensity, the spatial complexity USC of each basic spatial unit is assigned attribute values ​​and filled with colors for visualization.

[0010] In step c of the aforementioned method for calculating urban spatial complexity and construction intensity, the construction intensity (UCI) of each basic spatial unit is assigned attribute values ​​and filled with colors for visualization.

[0011] In step c of the aforementioned method for measuring urban spatial complexity and construction intensity, the linear normalization process involves obtaining the difference between the maximum and minimum values ​​in the set of urban spatial characteristic indicators and establishing a base. The calculation method is as follows:

[0012]

[0013] In the formula, x' is the normalized value of x in the set, x is the value in the set of spatial characteristic indicators of each city, and x' is the value of x'. min x is the minimum value in the set. max It is the maximum value in the set.

[0014] In step c of the aforementioned method for measuring urban spatial complexity and construction intensity, the quantification process of urban spatial complexity (USC) is carried out according to the following formula:

[0015] USC = w1BLC + w2BN + w3TBV + w4BHO

[0016] In the formula, BLC represents the building layout complexity; BN represents the number of buildings; TBV represents the total building volume; BHO represents the building height variation; w1, w2, w3, and w4 are the weights of the four indicators, and the sum is 1. The maximum value of each variable indicator is normalized and then weighted and summed.

[0017] In the aforementioned methods for measuring urban spatial complexity and construction intensity, the Building Layout Complexity (BLC) is calculated by transforming the building vector surface within the basic spatial unit into building vector points, based on the nearest neighbor index. The nearest neighbor index is calculated as follows:

[0018]

[0019]

[0020] In the formula, R is the nearest neighbor index. The average distance r1 between the nearest neighbors is... Where R is the theoretical nearest neighbor distance, D is the point density, BN is the number of buildings, and S is the area of ​​the basic spatial unit; when R = 1, that is... This indicates that the point elements are randomly distributed; when R>1, i.e. This indicates that point-like features tend to be uniformly distributed; when R < 1, i.e. This indicates that point-like elements are clustered and distributed.

[0021] In step c of the aforementioned method for measuring urban spatial complexity and construction intensity, the quantification process of urban construction intensity (UCI) is carried out according to the following formula:

[0022] UCI = w5PISA + w6BVD

[0023] In the formula, UCI represents urban construction intensity; PISA represents the percentage of impermeable surfaces; BVD represents building volume density; w5 and w6 are the weights of the two indicators, which are summed to 1. The variables are normalized and then summed.

[0024] In the aforementioned methods for measuring urban spatial complexity and construction intensity, PISA is calculated using the following formula:

[0025]

[0026] In the formula, S is the area of ​​the basic spatial unit, S I The area of ​​the impermeable surface.

[0027] Beneficial effects

[0028] Compared with existing technologies, the method for measuring urban spatial complexity and construction intensity based on three-dimensional building data provided by this invention can obtain the spatial complexity of urban spatial units and the urban construction intensity index from building layout, quantity, volume and height variation, impermeable surface ratio and building volume density, respectively. This method can quantitatively characterize urban spatial complexity, effectively avoiding the defects of traditional methods that qualitatively characterize urban spatial structure by building layout or orientation, as well as the problems of traditional urbanization indicators ignoring vertical spatial changes in the city and failing to take into account the three-dimensional spatial form of buildings, resulting in the inability to fully reflect the level of urbanization, the inability to distinguish differences between indicator intervals, and the inefficiency of urban spatial unit planning and renewal under the guidance of high-quality development.

[0029] This invention treats urban street space as a three-dimensional whole, comprehensively considering two-dimensional and three-dimensional spatial characteristics to quantify the complexity and construction intensity of urban street space units. Compared with traditional methods that use qualitative measures such as building layout or orientation, urban spatial complexity can be quantitatively explained from different attributes and dimensions to determine the degree of spatial complexity of basic urban units; furthermore, it uses only the proportion of impermeable surface area to characterize urbanization intensity. Figure 4 ), and the urban construction intensity in this invention ( Figure 3 (b) In contrast, the former amplifies the values ​​for high-construction-intensity areas and reduces the values ​​for low-construction-intensity areas in basic spatial units, which is inconsistent with the actual level of urbanization. The calculation method of this invention, however, is consistent with the construction status of each basic spatial unit in the city. Overall, this invention avoids the problems of the traditional urbanization measurement indicators' single and simplistic dimensions, and their inability to accurately reflect the impact of urban form and construction intensity on the urban ecological environment. It can accurately reveal the actual construction status of basic urban spaces under the current background of high-quality urban development. Attached Figure Description

[0030] Figure 1 This is a flowchart of a method according to an embodiment of the present invention.

[0031] Figure 2 This is an example of the spatial unit division of the street blocks in Guanshanhu District, Guiyang City, in the context of this invention.

[0032] Figure 3 This is a diagram showing the results of urban spatial complexity and construction intensity in an example of the present invention.

[0033] Figure 4 This is a graph representing the intensity of urbanization using only the proportion of impermeable surfaces. Detailed Implementation

[0034] The present invention will be further described below with reference to the accompanying drawings and embodiments, but this should not be construed as limiting the present invention.

[0035] Example 1. A method for measuring urban spatial complexity and construction intensity, see [link to example]. Figure 1 It includes the following steps:

[0036] a. Divide the urban space into one or more closed polygonal spaces to obtain basic spatial units;

[0037] b. Obtain urban spatial characteristic indicators within each basic spatial unit, and use these indicators to generate a summary table of urban spatial characteristic indicators for each basic spatial unit; the urban spatial characteristic indicators include: the area S of the basic spatial unit, the impermeable surface area S0, and the area S0 of the impermeable surface. IThe following are the building quantities (BN), building footprint (A), building height variation (BHO), total building volume (TBV), building volume density (BVD), and building layout complexity (BLC).

[0038] c. Standardize the data in the summary tables of various spatial indicators using linear normalization, and then sum the corresponding indicators using equal weights to quantify the urban spatial complexity (USC) and urban construction intensity (UCI) of each basic spatial unit.

[0039] The area S of the basic spatial unit is obtained by performing geometric calculations on the divided polygonal vector spatial units in the ArcMap platform; the impermeable surface area S I The basic spatial unit is the sum of the building footprint A and the hard surface area; the number of buildings BN is the total number of buildings in the basic spatial unit; the building footprint A is obtained by calculating the vector space of all buildings in the basic spatial unit in ArcMap; the building height variation BHO is the variance of the height of all buildings in the basic spatial unit; the total building volume TBV is the sum of the volumes of all buildings in the basic spatial unit; the building volume density BVD is the ratio of the total building volume TBV in the basic spatial unit to the area S of the basic spatial unit; and the building layout complexity BLC is used to describe the distribution pattern of buildings.

[0040] In step a, the basic spatial unit is obtained by dividing the city based on urban roads or urban planning control units, and the basic spatial unit includes at least one building.

[0041] In step c, the spatial complexity (USC) of each basic spatial unit is assigned attribute values ​​and filled with colors for visualization.

[0042] In addition, in step c, the construction intensity (UCI) of each basic spatial unit is assigned attribute values ​​and filled with colors for visualization.

[0043] Specifically, in step c, the linear normalization process is as follows: The difference between the maximum and minimum values ​​in the set of spatial characteristic indicators for each city is obtained, and a base is established. The calculation method is as follows:

[0044]

[0045] In the formula, x' is the normalized value of x in the set, x is the value in the set of spatial characteristic indicators of each city, and x' is the value of x'. min x is the minimum value in the set. max It is the maximum value in the set.

[0046] Specifically, the quantification process of Urban Spatial Complexity (USC) is carried out according to the following formula:

[0047] USC = w1BLC + w2BN + w3TBV + w4BHO

[0048] In the formula, BLC represents the building layout complexity; BN represents the number of buildings; TBV represents the total building volume; BHO represents the building height variation; w1, w2, w3, and w4 are the weights of the four indicators, and the sum is 1. The maximum value of each variable indicator is normalized and then weighted and summed.

[0049] Specifically, Building Layout Complexity (BLC) is calculated by transforming building vector surfaces within basic spatial units into building vector points, based on the nearest neighbor index; the calculation method for the nearest neighbor index is as follows:

[0050]

[0051]

[0052] In the formula, R is the nearest neighbor index. The average distance r1 between the nearest neighbors is... Let R be the theoretical nearest neighbor distance, D be the point density, BN be the number of buildings, and A be the building footprint; when R = 1, that is... This indicates that the point elements are randomly distributed; when R>1, i.e. This indicates that point-like features tend to be uniformly distributed; when R < 1, i.e. This indicates that point-like elements are clustered and distributed.

[0053] Specifically, in step c, the quantification process of urban construction intensity (UCI) is carried out according to the following formula:

[0054] UCI = w5PISA + w6BVD

[0055] In the formula, UCI represents urban construction intensity; PISA represents the percentage of impermeable surfaces; BVD represents building volume density; w5 and w6 are the weights of the two indicators, which are summed to 1. The variables are normalized and then summed.

[0056] Specifically, PISA is calculated using the following formula:

[0057]

[0058] In the formula, S is the area of ​​the basic spatial unit, S I The area of ​​the impermeable surface.

[0059] Example 2. A method for measuring urban spatial complexity and construction intensity, see [link to example]. Figure 1 It mainly includes the following steps:

[0060] S1: Obtain basic urban spatial data within a given range, and extract urban blocks from the basic data as the basic spatial units for partitioning.

[0061] In this step, basic urban spatial data can be obtained from relevant government departments or data platforms to construct a basic urban spatial database. This database includes urban control units planned according to urban control lines. Alternatively, it can be obtained by processing geographic information software or image data, combined with basic data such as urban roads and buildings. Basic spatial units are typically urban blocks enclosed by urban roads, or control line planning units in urban planning implementation. Their outlines are polygonal spaces composed of closed polylines, and the data format can be dwg or shp, etc. Basic spatial units generally contain buildings, whose outlines are also polygonal spaces composed of closed polylines. The data format can also be dwg or shp. Each building within a basic spatial unit has floor information (e.g., 1, 2, 3...) and / or height information. If height information is missing, it can be calculated from the number of floors (number of floors * 3m).

[0062] S2: For each basic spatial unit, calculate the urban spatial characteristic indicators and generate a summary table of urban spatial characteristics;

[0063] In this step, urban spatial characteristic indicators include indicators that represent urban spatial form and construction intensity, such as block area (i.e., basic spatial unit area), building footprint, impermeable surface area, number of buildings, building height, average building height, building height variation, total building volume, and building volume density.

[0064] The street area is calculated geometrically from the polygonal vector spatial units divided in the geographic information platform; the building footprint is calculated geometrically from the vector spatial units of all buildings in the geographic information platform; the number of buildings is the sum of the number of all buildings in the street spatial unit; the impermeable surface area is the sum of the building footprint and the hard surface area in the spatial unit; the building height is the height or number of floors of the buildings in the street spatial unit multiplied by 3m; the average building height is the average height of all buildings in the street spatial unit; the building height variation is the variance of the height of all buildings in the street spatial unit; the total building volume is the sum of the volumes of all buildings in the street spatial unit, and the building volume is the product of the building footprint and the building height; the building volume density is the ratio of the total building volume to the street area.

[0065] Building layout complexity is calculated by converting building vector surfaces within a block space unit into building vector points, based on the nearest neighbor index.

[0066] S3: The data in the spatial characteristic index summary table are standardized using linear normalization, and the corresponding indicators are weighted and summed using an equal-weight method to quantify the spatial complexity and construction intensity of the spatial unit.

[0067] In this step, the linear normalization (i.e., "max-min" normalization) method is used to standardize the spatial characteristic indicators of the block unit. The spatial complexity of the block unit is obtained by weighting the building layout complexity, number of buildings, building height variation and total building volume in an equal weighted manner. The construction intensity of the block unit is obtained by weighting the proportion of impermeable surface and building volume density in an equal weighted manner.

[0068] S4: Based on the calculation results, the spatial complexity and construction intensity of urban block units are displayed in zoning images.

[0069] The following will use the urban spatial complexity and construction intensity of Guanshanhu District in Guiyang City as an example to illustrate the technical solution of this invention in detail. The specific methods for dividing urban street space morphology mainly include:

[0070] (1) Taking Guanshanhu District of Guiyang City as the research object, basic urban road data is obtained. This example involves vectorizing and spatially dividing the roads, specifically including:

[0071] (1.1) Import the corresponding urban road data into ArcMap software, outline the boundaries of all roads in the city, and form basic spatial units based on road division, such as... Figure 2 .

[0072] (2) Number the divided street blocks and calculate multiple urban spatial characteristic indicators for each basic spatial unit to generate a summary table of urban spatial morphological characteristics; specifically including:

[0073] (2.1) Number the basic spatial units as 1, 2, ..., n, and calculate all spatial indices for each basic spatial unit.

[0074] (3) The spatial characteristic indicators of each basic spatial unit in Guanshanhu District of Guiyang City are summarized and standardized using linear normalization. The processing method is as follows:

[0075]

[0076] In the formula, x' is the normalized value of x in the set, x is the value of x in the set, and x' is the value of x in the set. min x is the minimum value in the set. max It is the maximum value in the set.

[0077] (4) The spatial feature indicators are weighted and summed according to equal weights. The calculation method is as follows:

[0078] USC = w1BLC + w2BN + w3TBV + w4BHO

[0079] In the formula, USC represents urban spatial complexity, BLC represents building layout complexity, BN represents the number of buildings, TBV represents the total building volume, and BHO represents the building height variation. w1, w2, w3, and w4 are the weights of the four indicators, each with a value of 0.25, and the sum is 1. The weighted sum is calculated after normalizing each variable indicator.

[0080] UCI = w5PISA + w6BVD

[0081] In the formula, UCI represents urban construction intensity; PISA represents the percentage of impermeable surfaces; BVD represents building volume density; w5 and w6 are the weights of the two indicators, both 0.5, and the sum is 1. The variables are normalized and then summed.

[0082] (4.1) Import the results of urban spatial complexity and construction intensity of each block unit into the vector file of the corresponding numbered block, assign attribute values, and display the partitioned image using colored blocks, such as... Figure 3 , Figure 3 In the image, 'a' represents a visualization of urban spatial complexity, and 'b' represents a visualization of urban construction intensity.

Claims

1. A method for measuring urban spatial complexity and construction intensity, characterized in that, Includes the following steps: a. Divide the urban space into one or more closed polygonal spaces to obtain basic spatial units; b. Obtain urban spatial characteristic indicators within each basic spatial unit, and use these indicators to generate a summary table of urban spatial characteristic indicators for each basic spatial unit; the urban spatial characteristic indicators include: the area S of the basic spatial unit, the impermeable surface area S0, and the other two indicators. I The following are the building quantities (BN), building footprint (A), building height variation (BHO), total building volume (TBV), building volume density (BVD), and building layout complexity (BLC). c. Standardize the data in the summary table of spatial characteristic indicators by linear normalization, and then sum the corresponding indicators by weighting them equally to quantify the urban spatial complexity (USC) and urban construction intensity (UCI) of each basic spatial unit. In step c, the spatial complexity (USC) and construction intensity (UCI) of each basic spatial unit are assigned attribute values ​​and filled with colors for visualization. In step c, the linear normalization process is as follows: The difference between the maximum and minimum values ​​in the set of spatial characteristic indicators for each city is obtained, and a base is established. The calculation method is as follows: In the formula, x' is the normalized value of x in the set, x is the value in the set of spatial characteristic indicators of each city, and x' is the value of x'. min x is the minimum value in the set. max The maximum value in the set; In step c, the quantification process of urban spatial complexity (USC) is carried out according to the following formula: In the formula, BLC represents the building layout complexity; BN represents the number of buildings; TBV represents the total building volume; BHO represents the building height variation; w1, w2, w3, and w4 are the weights of the four indicators, and the sum is 1. The maximum value of each variable indicator is normalized and then the weighted sum is calculated. Building Layout Complexity (BLC) is calculated by transforming building vector surfaces within basic spatial units into building vector points, based on the nearest neighbor index. The nearest neighbor index is calculated as follows: In the formula, R is the nearest neighbor index. The average distance r1 between the nearest neighbors is... Where R is the theoretical nearest neighbor distance, D is the point density, BN is the number of buildings, and S is the area of ​​the basic spatial unit; when R=1, that is... = This indicates that the point elements are randomly distributed; when R>1, that is... > This indicates that point-like elements tend to be evenly distributed; when R < 1, i.e. < This indicates that point-like elements are clustered and distributed.

2. The method for calculating urban spatial complexity and construction intensity according to claim 1, characterized in that, In step a, the basic spatial unit is obtained by dividing the city based on urban roads or urban planning control units, and the basic spatial unit includes at least one building.

3. The method for calculating urban spatial complexity and construction intensity according to claim 1, characterized in that, In step c, the quantification process of Urban Construction Intensity (UCI) is carried out according to the following formula: In the formula, UCI represents urban construction intensity; PISA represents the percentage of impermeable surfaces; BVD represents building volume density; w5 and w6 are the weights of the two indicators, which are summed to 1. The variables are normalized and then summed.

4. The method for calculating urban spatial complexity and construction intensity according to claim 3, characterized in that, PISA is calculated using the following formula: In the formula, S is the area of ​​the basic spatial unit, S I The area of ​​the impermeable surface.

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