Comprehensive calculation and spatial mapping method of land use mixture considering three-dimensional space

Abstract

The present invention discloses a method for comprehensive calculation and spatial mapping of land use mixture degree taking into account three-dimensional space, and the method includes the following steps: S1, pre-processing road data to obtain block data; S2, summarizing urban data obtained within the block range; S3, integrating building data and points of interest in three-dimensional space, and calculating three-dimensional mixture indexes at different angles respectively; S4, constructing a three-dimensional multi-angle mixture index to measure the land mixture degree of each block in the city; S5, verifying the accuracy of the three-dimensional multi-angle mixture index. By integrating diversity indicators, accessibility indicators and compatibility indicators and three-dimensionalizing and normalizing them respectively to obtain a three-dimensional multi-angle mixture index, it is possible to fundamentally solve the one-sidedness and limitations brought about by the single perspective of the existing technology, thereby improving the accuracy and comprehensiveness of the quantification of urban land mixture, and forming a comprehensive and multi-angle three-dimensional mixture evaluation system.

Description

Technical Field

[0001] The present invention relates to the field of land surveying technology, and in particular to a method for comprehensive calculation of land use mixture degree taking into account three-dimensional space and spatial mapping. Background Art

[0002] Land use mix refers to a land use pattern that integrates different land use types. A reasonable land use mix can improve urban vitality, alleviate urban decay, create jobs, and reduce dependence on cars, thereby building a healthy, safe, and sustainable community. At present, land use mix has become the main principle of sustainable urban planning and design concepts, such as new urbanism, smart growth, and new urbanization.

[0003] Accurate and objective mixed index has important theoretical and practical significance for evaluating land use combinations. It can optimize the land mix quantification system and further provide a scientific basis for urban management. The quantification of land use mix is ​​mainly divided into three aspects: diversity, accessibility and compatibility. Diversity mainly quantifies land mix from the perspective of the proportion of land use types, accessibility mainly reflects land mix from the spatial distribution of land use types, and compatibility mainly reflects land mix from the degree of interaction between land use types.

[0004] However, current hybridity indices usually only consider one of these three perspectives and lack a comprehensive perspective. For example, diversity is the most direct, intuitive and commonly used quantification perspective of land hybridity, but it cannot reflect the accessibility and compatibility between land types, and lacks consideration of the spatial distribution and interaction between different land use types. At the same time, due to the lack of three-dimensional data at the urban scale, such as three-dimensional point clouds and three-dimensional building data, current indicators are mostly limited to two-dimensional space and lack exploration of three-dimensional space. Therefore, related research requires a comprehensive, multi-angle three-dimensional hybridity indicator.

[0005] In addition, another problem in exploring mixed degree indicators is that the data currently used in research is limited to land use data in two-dimensional space, resulting in the measurement results not being able to reflect the actual situation in three-dimensional space. Pi represents the land area ratio of various land use types; in the calculation process of compatible WVMDI, the weighting coefficient is also the land area ratio. However, in the actual situation of the city, some land use types have a small land area, but a large building area, many floors, and carry a large number of social and economic activities. Measuring the land use combination only by land area will underestimate the impact of these land use types. On the contrary, some land use types have a relatively large land area but a small building area. Measuring the land use combination only by land area will overestimate the impact of these land use types. Therefore, it is of great significance to construct a three-dimensional mixed degree index to reflect the actual situation of urban land use combination. However, due to high collection costs and data privacy, large-scale three-dimensional data is often difficult to obtain. With the continuous development of big data technology, the building data currently obtained can directly reflect three-dimensional spatial information such as building floors and building areas. At the same time, point of interest (POI) as a kind of citizen data can represent point data in the Internet electronic map, which basically contains four attributes: name, address, coordinates, and category. Compared with traditional geographic information data, POI has the advantages of large data volume, good status, rich geographic information, and low cost. In addition, POIs on different floors of the same building have different coordinates or address information, which can also reflect facility information in three-dimensional space. Therefore, three-dimensional building data can be integrated with POI to explore the mixed degree index of three-dimensional space.

[0006] Currently, no effective solution has been proposed for the problems in the related technologies. Summary of the invention

[0007] In view of the problems in the related art, the present invention proposes a comprehensive calculation method of land use mixture degree and spatial mapping taking into account three-dimensional space to overcome the above-mentioned technical problems existing in the existing related art.

[0008] To this end, the specific technical solution adopted by the present invention is as follows:

[0009] According to one aspect of the present invention, a method for comprehensively calculating the land use mixture degree taking into account three-dimensional space comprises the following steps:

[0010] S1, preprocessing the road data to obtain block data;

[0011] S2, summarize the urban data obtained within the block;

[0012] S3, integrating the building data and interest points in the three-dimensional space, and calculating the three-dimensional mixing index at different angles;

[0013] S4, construct a three-dimensional multi-angle mixed index to measure the land mix of each block in the city;

[0014] S5. Verify the accuracy of the three-dimensional multi-angle mixing index.

[0015] Furthermore, the preprocessing of the road data to obtain the block data includes the following steps:

[0016] S11, checking the consistency of the road data and removing overlapping roads;

[0017] S12. Perform a topological check and remove overhanging roads and independent road sections.

[0018] Furthermore, the city data includes urban land use data, points of interest, building data and road data;

[0019] Among them, the urban land use data includes residential land, commercial land, first-class industrial land, second-class industrial land, new-type industrial land, public service land, transportation land, logistics and warehousing land, special land and other land.

[0020] Furthermore, the three-dimensional mixing indexes at different angles include a three-dimensional diversity index, a three-dimensional accessibility index and a three-dimensional compatibility index.

[0021] Furthermore, the calculation process of the three-dimensional diversity index includes the following steps:

[0022] S31. Use the Hill number to calculate urban land diversity. The calculation formula is:

[0023]

[0024] Among them, 2D q D represents the Hill number, q represents the order of diversity, and P i represents the proportion of the land area of ​​land type i to the total area of ​​regional land, and k represents the type of land type;

[0025] S32. Integrate the three-dimensional building data to construct the three-dimensional Hill number. The calculation formula is:

[0026]

[0027] Among them, 3D q D represents the three-dimensional Hill number, M i represents the weighted land area ratio of building area of ​​land type i, A i represents the land area of ​​land type i, FA i represents the building area of ​​land type i. When q=0, When q=1, When q = 2,

[0028] S33, according to 3D 0 D. 3D 1 D and 3D 2 The normalized value of D is calculated, and the average value is calculated to obtain the three-dimensional diversity index. The calculation formula is:

[0029]

[0030] Among them, 3DDI represents the three-dimensional diversity index.

[0031] Furthermore, the calculation process of the three-dimensional accessibility index includes the following steps:

[0032] S31′, determine the scope of the area of ​​accessibility;

[0033] S32′, calculate the number of opportunity points that can be reached within 1500m of each block, and calculate the average value of the accessibility of all blocks in each block to obtain the three-dimensional accessibility index of the block. The calculation formula is:

[0034]

[0035] in, represents the total number of POIs within 1500 m of plot i, 3DAI represents the three-dimensional accessibility index of the block, and t represents the number of plots in the block.

[0036] Furthermore, the calculation process of the three-dimensional compatibility index includes the following steps:

[0037] S31″, determine the compatibility judgment matrix;

[0038] S32″, determine the scope of the field of compatibility;

[0039] S33″, by introducing the building area weighted land area ratio, construct the three-dimensional space plot compatibility index and the three-dimensional space block scale compatibility index, the calculation formula is:

[0040]

[0041] Among them, 3DLCI h represents the three-dimensional spatial compatibility index of h plot, C hj represents the compatibility coefficient between plots h and j, n represents the number of plots within the influence range of plot h, M j is the weight coefficient representing the weighted land area ratio of the building area of ​​the j plot, FA j is the building area of ​​plot j, and plot j is within the influence range of plot h, 3DSCI f is the three-dimensional spatial block scale compatibility index of block f, H represents the number of plots in block f, M hrepresents the building area weighted land area ratio between plot h and block f, FA h is the building area of ​​plot h, A j represents the land area of ​​land type j, A h Represents the land area of ​​land type h.

[0042] Furthermore, the construction of a three-dimensional multi-angle mixed index to measure the land mixedness of each block in the city includes the following steps:

[0043] S41. Combining the three perspectives, the land mix index is obtained at the block scale;

[0044] S42. Standardize the three-dimensional diversity index, the three-dimensional accessibility index, and the three-dimensional compatibility index;

[0045] S43, calculating the average value of the normalized values ​​of the three angle indices to obtain the three-dimensional multi-angle mixing index, and the calculation formula is:

[0046]

[0047] in, and They represent the normalized values ​​of 3D diversity index, 3D accessibility index and 3D compatibility index respectively, and 3DMMDI represents the 3D multi-angle mixing index.

[0048] Furthermore, the accuracy verification of the three-dimensional multi-angle mixing index includes the following steps:

[0049] S51. The first method obtains the three-dimensional multi-angle mixed degree at the community scale. The research unit is changed from a block to a community, and the community three-dimensional diversity index, community three-dimensional accessibility index and community three-dimensional compatibility index at the community scale are calculated. Then, the community three-dimensional multi-angle mixed degree index 3DMMDI at the community scale is calculated based on their respective normalized values. α ;

[0050] S52. The second method obtains the community-scale three-dimensional multi-angle mixing degree, using the M of each block. V As a weighting coefficient, the three-dimensional multi-angle mixed index at the block scale is converted to the community scale to finally obtain the three-dimensional multi-angle mixed index at the community scale. The calculation formula is:

[0051]

[0052] Among them, M V represents the building area weighted land area ratio between block v and the corresponding community, A V represents the land area of ​​block v, FA Vrepresents the building area of ​​block v, and W represents the number of blocks in the corresponding community 3DMMDI β It represents the three-dimensional multi-angle mixedness index at the community scale;

[0053] S53, Compare 3DMMDI α and 3DMMDI β Correlation, comparison 3DMMDI α 、3DMMDI β As well as the spatial distribution characteristics of 3DMMDI, the accuracy of the three-dimensional multi-angle mixing index 3DMMDI is verified;

[0054] S54. Use taxi travel distance to verify the relationship with 3DMMDI.

[0055] According to another aspect of the present invention, a land use mixed degree spatial mapping method taking into account three-dimensional space is also provided, the method comprising the following steps:

[0056] Using geographic information system tools and the natural break point classification method, the quantitative results of three-dimensional diversity index, three-dimensional accessibility index, three-dimensional compatibility index and three-dimensional multi-angle mixing index were classified and mapped, and the spatial distribution maps of three-dimensional diversity, three-dimensional accessibility, three-dimensional compatibility and three-dimensional multi-angle mixing were obtained.

[0057] The beneficial effects of the present invention are as follows: by integrating diversity indicators, accessibility indicators and compatibility indicators and performing three-dimensional and normalized processing on them respectively, a three-dimensional multi-angle mixed index is obtained, which can fundamentally solve the one-sidedness and limitations brought about by the single perspective of the existing technology, thereby improving the accuracy and comprehensiveness of urban land mixed quantification, forming a comprehensive multi-angle three-dimensional mixed evaluation system, further providing a scientific basis for urban management, improving urban vitality, alleviating urban decline, creating employment opportunities, and reducing dependence on cars, thereby establishing a healthy, safe and sustainable community.

[0058] In addition, the three-dimensional multi-angle mixed index comprehensively considers the land use information in three-dimensional space. The result can reflect the land mixing situation in three-dimensional space, thereby optimizing the land mixing quantification system, and then improving the coordination of all land use types at the plot scale, reducing the interference of mixed use of industrial land and residential land on the human living environment, and having a positive impact on the economy, society, health and other aspects. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] 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 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.

[0060] Figure 1 is a flow chart of a comprehensive calculation method of land use mixture degree taking into account three-dimensional space according to an embodiment of the present invention;

[0061] Figure 2 is a schematic diagram of a weighted land area ratio of building area in a comprehensive calculation method of land use mixture degree taking into account three-dimensional space according to an embodiment of the present invention;

[0062] Figure 3 is a schematic diagram of block accessibility in a comprehensive calculation method of land use mixture degree taking into account three-dimensional space according to an embodiment of the present invention;

[0063] Figure 4 is a schematic diagram of quantifying the compatibility of a three-dimensional space plot scale and a block scale in a comprehensive calculation method of land use mixture degree taking into account a three-dimensional space according to an embodiment of the present invention;

[0064] Figure 5 is a spatial distribution diagram of a three-dimensional diversity angle mixing index in a block in a spatial mapping method for land use mixing taking into account three-dimensional space according to an embodiment of the present invention;

[0065] Figure 6 is a spatial distribution diagram of a three-dimensional accessibility angle mixing index in a block in a spatial mapping method for land use mixing taking into account three-dimensional space according to an embodiment of the present invention;

[0066] Figure 7 is a spatial distribution diagram of a three-dimensional compatibility angle mixing index in a block in a spatial mapping method for land use mixing taking into account three-dimensional space according to an embodiment of the present invention;

[0067] Figure 8 is a spatial distribution diagram of a three-dimensional multi-angle mixed degree index in a block in a spatial mapping method of land use mixed degree taking into account three-dimensional space according to an embodiment of the present invention;

[0068] Fig. 9 It is a community-scale three-dimensional multi-angle mixed degree index spatial distribution map obtained by the first method in the land use mixed degree spatial mapping method taking into account three-dimensional space according to an embodiment of the present invention.

[0069] Fig.10It is a community-scale three-dimensional multi-angle mixed degree index spatial distribution map obtained by the second method in the land use mixed degree spatial mapping method taking into account three-dimensional space according to an embodiment of the present invention. DETAILED DESCRIPTION

[0070] Land use combination is one of the important themes of urban development planning. Establishing a comprehensive, accurate and reasonable mixed degree index has important theoretical and practical significance. However, the current indicators mostly select one angle from diversity, accessibility or compatibility to quantify land mix, lacking a comprehensive angle. At the same time, the current indicators are also limited to two-dimensional space, mainly due to the lack of three-dimensional data at the urban scale, such as building height data. The present invention integrates three-dimensional building data and POI data, introduces the building area weighted land area ratio (FAW-land area ratio), and constructs a three-dimensional diversity index (3DDI), a three-dimensional accessibility index (3DAI) and a three-dimensional block scale compatibility index (3DSCI). Then, taking the blocks in Shenzhen as the research unit, the three-dimensional space multi-angle mixed degree index (3DMMDI) is calculated to characterize the spatial heterogeneity of land use combination. The research results in Shenzhen show that 3DMMDI combines diversity, accessibility and compatibility sub-indicators, and can solve the one-sidedness of a single angle. At the same time, 3DMMDI can also quantify the degree of land use combination with high accuracy in three-dimensional space. To further verify the reliability of 3DMMDI, the present invention also explores the performance of 3DMMDI at different scales and the relationship between 3DMMDI and taxi travel distance. In short, 3DMMDI can provide further scientific basis for urban planning management.

[0071] Among the three perspectives of land use combination quantification, diversity and accessibility are the main perspectives considered by most current studies. Diversity quantification is usually divided into two types. A simple quantitative method is to directly use the land area ratio of different land use types as a mixed index, such as the area ratio of residential land, public service facility land, industrial land, municipal public land, etc. Another method is to construct more complex indicators to represent the diversity of land use combinations, including: (1) indicators suitable for small scales (communities, blocks, etc.), such as balance index, entropy index and Huffington Hirschman index, etc.; (2) indices suitable for large scales (cities, etc.), such as clustering index, difference index and Gini coefficient, etc. Although these diversity indices are simple and effective in measuring land use combinations, each index can only reflect one aspect and cannot fully describe the diversity of land use combinations. For example, among all the indices, Shannon entropy index (SHDI) is the most commonly used to explore the relationship between land mix and socioeconomic indicators, such as travel distance, community vitality and job-residence separation. However, many studies have shown that SHDI can only represent the "balance" between different land use types and lacks a strict description of diversity. To make up for this deficiency, Jost proposed a land use type diversity measurement method based on Hill numbers, including species richness, Shannon entropy index and Simpson index, which reflect the diversity of land use types from three aspects: richness, randomness and concentration. Hillnumbers have been proven to be successful and effective in many scenarios, such as the relationship between land mix and community vitality and traffic accidents.

[0072] Accessibility measures the proximity between different land types, or the density / number of a certain target (such as schools, recreational activities) within a certain range. The spatial proximity between different land use types is usually reflected by distance, among which Euclidean distance is the most commonly used index. Cumulative opportunity measurement (also known as isochrone measurement or contour measurement) and gravity-based measurement are another representative accessibility quantification method. The gravity-based quantification method includes two aspects: one is the attractiveness of the destination, which is positively correlated with accessibility, and the other is the travel cost (such as travel time), which is negatively correlated with accessibility. The cumulative opportunity quantification method first determines the contour of travel cost (for example, distance / time), and then calculates the number of opportunities within each contour. Compared with the gravity-based quantification method, the cumulative opportunity method is easier to understand and explain because of its simple expression.

[0073] The compatibility between different land use types is another important aspect to measure the degree of land use mixing, but it is rarely considered in current studies. The compatibility of land use combinations refers to the possibility of coexistence of one land type with surrounding land use types. Higher compatibility indicates that the coexistence of two or more land use types has a positive impact on regional development, land quality and urban vitality, such as the mixed use of residential and commercial land. Lower compatibility indicates that the coexistence of two or more land use types may have adverse effects on the economy, society, health and other aspects. For example, the mixed use of industrial land and residential land will interfere with the living environment, resulting in the incompatibility of land use types. The mixed degree index (MDI) can reflect the compatibility of residential and industrial land. Based on the MDI, the vector-based mixed degree index (VMDI) was established to measure the degree of coordination of all land use types at the plot scale. Then, the weighted vector mixed degree index (WVMDI) was established in combination with the land area proportion of each affected plot. VMDI and WVMDI can express compatibility more effectively than MDI.

[0074] According to one embodiment of the present invention, Figure 1-4 As shown, a comprehensive calculation method for land use mixing degree taking into account three-dimensional space is provided, and the method comprises the following steps:

[0075] S1, preprocessing the road data to obtain block data;

[0076] Blocks are the basic units of urban management divided by urban arterial roads. They are divided by highways, main roads and secondary roads. Compared with the smallest administrative unit in China, communities, blocks are smaller in size. A community usually contains several blocks. Shenzhen currently has 734 communities and 6,699 blocks.

[0077] Wherein, step S1 comprises the following steps:

[0078] S11, checking the consistency of the road data and removing overlapping roads;

[0079] S12. Perform a topological check and remove overhanging roads and independent road sections.

[0080] S2, summarize the urban data obtained within the block;

[0081] Wherein, the urban data includes urban land use data, points of interest, building data and road data;

[0082] And the urban land use data includes residential land, commercial land, first-class industrial land, second-class industrial land, new-type industrial land, public service land, transportation land, logistics and warehousing land, special land and other land.

[0083] Category I industrial land refers to industrial land that has basically no interference and pollution to residential areas, such as sewing industry, handicraft manufacturing and other industrial land. Category II industrial land refers to industrial land that has certain interference, pollution and safety hazards to residential and public environment, such as food industry, pharmaceutical manufacturing industry and other industrial land. New industrial land is a classification of urban land proposed to adapt to industrial transformation and upgrading and improve the efficiency of industrial land. Specifically, it refers to industrial buildings and supporting service facilities in industrial land, which are basically free of environmental and noise pollution. Public service land mainly includes public management and service facility land and public facility land. Special land mainly refers to military facilities, religion, prisons, funerals, scenic spots and other land. This type of land will reduce the value of land and produce negative externalities. Other land mainly refers to green space and squares and other land in the current urban land use data.

[0084] S3, integrating the building data and interest points in the three-dimensional space, and calculating the three-dimensional mixing index at different angles;

[0085] The three-dimensional mixing indexes at different angles include a three-dimensional diversity index, a three-dimensional accessibility index, and a three-dimensional compatibility index. Information on each index is shown in Table 1:

[0086] Table 1 Land mixing index

[0087]

[0088] Among them, the positive indicator means that the higher the value, the higher the land mixing degree.

[0089] 1. The calculation process of the three-dimensional diversity index includes the following steps:

[0090] S31. The Hill Number is used to calculate the diversity of urban land types from different dimensions, such as the richness, disorder and aggregation of land types. The calculation formula is:

[0091]

[0092] Among them, 2D q D represents the Hill number, q represents the order of diversity, and P i represents the proportion of the land area of ​​land type i to the total area of ​​regional land, and k represents the type of land type;

[0093] S32. Integrate the three-dimensional building data to construct the three-dimensional Hill number. The calculation formula is:

[0094]

[0095] Among them, 3D qD represents the three-dimensional Hill number, M i represents the weighted land area ratio of building area of ​​land type i, A i represents the land area of ​​land type i, FA i represents the building area of ​​land type i. When q=0, When q=1, When q = 2,

[0096] S33, according to 3D 0 D. 3D 1 D and 3D 2 The normalized value of D is calculated, and the average value is calculated to obtain the three-dimensional diversity index. The calculation formula is:

[0097]

[0098] Among them, 3DDI represents the three-dimensional diversity index.

[0099] The calculation process of the 2D accessibility index includes the following steps:

[0100] S31′, determine the scope of accessibility (“15-minute living circle” has become a new planning direction for many cities, and many cities have successively proposed planning guidelines for “15-minute living circle”. The 15-minute community living circle is the basic unit for cities to build community life, that is, within a 15-minute walking range, it is equipped with basic service functions and public activity spaces required for life, forming a safe, friendly and comfortable social basic life platform. The walking speed of a person is about, and the neighborhood range is set at 1500m in this study.);

[0101] S32′, calculate the number of opportunity points (POIs) that can be reached within 1500m of each block, and calculate the average value of the accessibility of all blocks in each block to obtain the three-dimensional accessibility index of the block. The calculation formula is:

[0102]

[0103] in, represents the total number of points of interest (POI) within 1500 m of plot i, 3DAI represents the three-dimensional accessibility index of the block, and t represents the number of plots in the block.

[0104] 3. The calculation process of the three-dimensional compatibility index includes the following steps:

[0105] S31″, determine the compatibility judgment matrix, as shown in Table 2:

[0106] Table 1 Compatibility judgment matrix

[0107]

[0108] Among them, compatible: 0, conditionally compatible: 0.5, incompatible: 1. R: residential land, C: commercial land, M1: first-class industrial land, M2: second-class industrial land, M0: new industrial land, P: public service land, S: transportation land, W: logistics and warehousing land, SL: special land, OL: other land.

[0109] S32″, determine the scope of the field of compatibility;

[0110] S33″, by introducing the building area weighted land area ratio (FAW-land area ratio), the three-dimensional space plot compatibility index and the three-dimensional space block scale compatibility index are constructed, and the calculation formula is:

[0111]

[0112] Among them, 3DLCI h represents the three-dimensional spatial compatibility index of h plot, C hj represents the compatibility coefficient between plots h and j, n represents the number of plots within the influence range of plot h, M j is the weight coefficient representing the building area weighted land area ratio (FAW-land area ratio) of the j plot, j is the building area of ​​plot j, and plot j is within the influence range of plot h, 3DSCI f is the three-dimensional spatial block scale compatibility index of block f, H represents the number of plots in block f, M h represents the building area weighted land area ratio (FAW-land area ratio) between plot h and block f, FA h is the building area of ​​plot h, A j represents the land area of ​​land type j, A h Represents the land area of ​​land type h.

[0113] exist Figure 4 In the figure, area A represents the three-dimensional land parcel compatibility index (3DLCI); the cuboids, cylinders, etc. represent different plots in three-dimensional space. Area B represents the three-dimensional block compatibility index (3DSCI), the large area on the left represents the plots in block f, and the small area on the right represents the plots in block g.

[0114] S4, construct a three-dimensional multi-angle mixed index to measure the land mix of each block in the city;

[0115] Wherein, step S4 comprises the following steps:

[0116] S41. Combining the three perspectives, the land mix index is obtained at the block scale;

[0117] S42. Standardize the three-dimensional diversity index, the three-dimensional accessibility index, and the three-dimensional compatibility index;

[0118] S43, calculating the average value of the normalized values ​​of the three angle indices to obtain the three-dimensional multi-angle mixing index, and the calculation formula is:

[0119]

[0120] in, and They represent the normalized values ​​of 3D diversity index, 3D accessibility index and 3D compatibility index respectively, and 3DMMDI represents the 3D multi-angle mixing index.

[0121] S5. Verify the accuracy of the three-dimensional multi-angle mixing index.

[0122] Wherein, step S5 comprises the following steps:

[0123] S51. Change the research unit from block to community and calculate the community three-dimensional diversity index (3DDI) at the community scale. α ), Community Three-Dimensional Accessibility Index (3DAI α ) and the Community Three-Dimensional Compatibility Index (3DSCI α ), and then the community-scale community three-dimensional multi-angle mixed index (3DMMDI) is calculated based on their normalized values. α );

[0124] S52, based on the M of each block V As a weighting coefficient, the 3D multi-angle mixed index (3DMMDI) at the block scale is converted to the community scale to obtain the community scale 3D multi-angle mixed index (3DMMDI β ), the calculation formula is:

[0125]

[0126]

[0127] Among them, M V A represents the building area weighted land area ratio (FAW-land area ratio) between block v and the corresponding community, V represents the land area of ​​block v, FA V represents the building area of ​​block v, W represents the number of blocks in the corresponding community, and 3DMMDI β It represents the three-dimensional multi-angle mixedness index at the community scale;

[0128] S53, Compare 3DMMDI α and 3DMMDI β Correlation, comparison 3DMMDI α 、3DMMDI β As well as the spatial distribution characteristics of 3DMMDI, the accuracy of the three-dimensional multi-angle mixing index 3DMMDI is verified;

[0129] S54. Use taxi travel distance to verify the relationship with 3DMMDI.

[0130] From the perspective of correlation, 3DMMDI α and 3DMMDI β There is a strong correlation between them (r = 0.76, Pearman), which not only proves the accuracy of 3DMMDI (block scale), but also verifies the reliability of this method. α and 3DMMDI β And the spatial distribution trend of 3DMMD is roughly the same, which once again proves the reliability of the hybrid metric method of this method.

[0131] In addition, the taxi travel distance is used to verify the relationship with 3DMMDI as follows:

[0132] As the degree of neighborhood mixing increases, people's daily needs can be met by walking and cycling, thus reducing motor vehicle travel. If there is a negative correlation between 3DMMDI and motor vehicle travel distance, it is consistent with the results of previous studies and can also prove the accuracy of 3DMMDI. Travel distance mainly includes the OD line length of taxi travel.

[0133] Get Taxi GPSData information. There are 46927855 Taxi GPSData, and the data attributes include Taxi ID, Time, Latitude, Longitude, Speed; Occupancy Status (1-with passengers & 0-with passengers). After processing the data, delete the data whose starting point and end point are not within 1.5km of Shenzhen City (627 data), and obtain 464090 valid taxi OD data, with an average travel distance of 4949.26m. Count the average taxi travel distance of each block (the average of the average distance of driving in and the average distance of driving out). There are 3472 blocks with average taxi travel distance. There is a weak but significant negative correlation between the average taxi travel distance of each block and the 3DMMDI (r = -0.27, p < 0.0001). This shows that the higher the degree of urban land mixing, the less distance residents travel by taxi. The results indirectly verify the validity of the mixed index. This is consistent with the results of previous studies. The weak correlation (r = -0.27) may be due to the lack of taxi travel data over a long period of time.

[0134] The study explored the distribution of 3DMMDI at different scales and the relationship between 3DMMDI and taxi travel distance. The results showed that the spatial distribution trends of the community-scale and block-scale mixed degree obtained based on the method proposed in the present invention were the same. There was a weak but significant negative correlation between the average taxi travel distance and 3DMMDI (r=-0.27, p<0.0001). The research results verified the reliability of the method proposed in the present invention and the accuracy of 3DMMDI.

[0135] According to another embodiment of the present invention, Figure 5-10 As shown, a land use mixed degree spatial mapping method taking into account three-dimensional space is also provided, and the method comprises the following steps:

[0136] Using geographic information system tools and the natural break point classification method, the quantitative results of three-dimensional diversity index, three-dimensional accessibility index, three-dimensional compatibility index and three-dimensional multi-angle mixing index were classified and mapped, and the spatial distribution maps of three-dimensional diversity, three-dimensional accessibility, three-dimensional compatibility and three-dimensional multi-angle mixing were obtained.

[0137] like Figure 5 As shown, it is the spatial distribution of multi-angle three-dimensional mixing index in the block. Figure 5The 3DDI value is the land diversity of the block. The larger the 3DDI value, the higher the diversity of regional land use. Among them, there are 2767 blocks with low diversity [0, 0.02) (41%), 2814 blocks with relatively low diversity [0.02, 0.15) (42%), and 1118 blocks with high diversity [0.15, 0.74) (17%). It can be found that the land diversity at the block scale in Shenzhen is relatively small. From the perspective of spatial layout, blocks with high land diversity are concentrated in Longhua District and Luohu District.

[0138] Figure 6 Indicates accessibility. The larger the 3DAI, the higher the degree of mixing. There are 2844 blocks (42%) with POIs accessibility in the interval [0, 1198], 3319 blocks (50%) in [1199, 4903], and 536 blocks (8%) in [4904, 13168]. Obviously, the spatial heterogeneity of POIs accessibility is strong. The blocks with the best accessibility are concentrated in the city center (Futian District, Luohu District, southern Guangming District, and southern Baoan District). On the contrary, the living convenience, facility sharing, and service accessibility of residents in Dapeng District are far lower than those in the blocks in the city center.

[0139] Figure 7 It reflects the compatibility of the blocks. The larger the 3DSCI value, the higher the degree of mixing. There are 193 blocks (3%) with low compatibility [0, 0.41), 2316 blocks (34.5%) with relatively compatible [0.41, 0.78), and 4190 blocks (62.5%) with high compatibility [0.78, 1]. There are fewer blocks with low compatibility, and they are mainly concentrated in the industrial park of Longgang District. This is mainly because some highly polluting, high-energy-consuming, and low-efficiency industrial land is difficult to form a benign interactive compatibility relationship with residential public facilities and service land.

[0140] Integrating the diversity, accessibility and compatibility of the blocks, we get the 3DMMDI of each of the 6699 blocks ( Figure 8 ). Among them, there are 689 blocks with low mixing [0.01, 0.22] (10%), 3969 blocks with relatively mixed [0.22, 0.31] (59%), and 2041 blocks with high mixing [0.38, 0.72] (31%). The 3DMMDI quantitative results can clearly show the agglomeration and dispersion areas of Shenzhen's land use combination. Among them, the blocks with high mixing are mainly concentrated in the core areas of Shenzhen, such as Futian District, Luohu District, Longhua District, southern Guangming District, and southern Bao'an District. The relatively mixed areas are mainly distributed adjacent to the high-mixed areas. The low-mixed blocks are mainly distributed in blocks with a high proportion of industrial land, or in the suburbs on the edge of the city. They are active areas for urban renewal and industrial transformation and upgrading, which is consistent with the actual situation.

[0141] exist Fig. 9 Middle, A area 3DMMDI α Obtained by changing the research unit in the research method to community; area B represents 3DMMDI β It is obtained by converting 3DMMDI (block scale) to community scale.

[0142] In summary, with the help of the above-mentioned technical scheme of the present invention, by integrating the diversity index, accessibility index and compatibility index and performing three-dimensional and normalized processing on them respectively, a three-dimensional multi-angle mixed index is obtained, which can fundamentally solve the one-sidedness and limitations brought about by the single perspective of the existing technology, thereby improving the accuracy and comprehensiveness of the quantification of urban land mixedness, forming a comprehensive multi-angle three-dimensional mixed degree evaluation system, further providing a scientific basis for urban management, improving urban vitality, alleviating urban decline, creating employment opportunities, and reducing dependence on cars, thereby establishing a healthy, safe and sustainable community.

[0143] In addition, the three-dimensional multi-angle mixed index comprehensively considers the land use information in three-dimensional space. The result can reflect the land mixing situation in three-dimensional space, thereby optimizing the land mixing quantification system, and then improving the coordination of all land use types at the plot scale, reducing the interference of mixed use of industrial land and residential land on the human living environment, and having a positive impact on the economy, society, health and other aspects.

[0144] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. Comprehensive calculation method of land use mixture considering three-dimensional space, It is characterized in that The method comprises the following steps: S1, preprocessing the road data to obtain block data; S2, summarize the urban data obtained within the block; S3, integrating the building data and interest points in the three-dimensional space, and calculating the three-dimensional mixing index at different angles; S4, construct a three-dimensional multi-angle mixed index to measure the land mix of each block in the city; S5. Verify the accuracy of the three-dimensional multi-angle mixing index; The three-dimensional mixing indexes at different angles include a three-dimensional diversity index, a three-dimensional accessibility index, and a three-dimensional compatibility index; The calculation process of the three-dimensional diversity index includes the following steps: S31. Use the Hill number to calculate urban land diversity. The calculation formula is: Among them, 2D q D represents the Hill number, q represents the order of diversity, and P i represents the proportion of the land area of ​​land type i to the total area of ​​regional land, and k represents the type of land type; S32. Integrate the three-dimensional building data to construct the three-dimensional Hill number. The calculation formula is: Among them, 3D q D represents the three-dimensional Hill number, M i represents the weighted land area ratio of building area of ​​land type i, A i represents the land area of ​​land type i, FA i represents the building area of ​​land type i. When q = 0, When q=1, When q = 2, S33, according to 3D 0 D. 3D 1 D and 3D 2 The normalized value of D is calculated, and the average value is calculated to obtain the three-dimensional diversity index. The calculation formula is: Among them, 3DDI represents three-dimensional diversity index; The calculation process of the three-dimensional accessibility index includes the following steps: S31′, determine the scope of the area of ​​accessibility; S32′, calculate the number of opportunity points that can be reached within 1500m of each block, and calculate the average value of the accessibility of all blocks in each block to obtain the three-dimensional accessibility index of the block. The calculation formula is: in, represents the total number of points of interest within 1500 m of plot i, 3DAI represents the three-dimensional accessibility index of the block, and t represents the number of plots in the block; The calculation process of the three-dimensional compatibility index includes the following steps: S31″, determine the compatibility judgment matrix; S32″, determine the scope of the field of compatibility; S33″, by introducing the building area weighted land area ratio, construct the three-dimensional space plot compatibility index and the three-dimensional space block scale compatibility index, the calculation formula is: Among them, 3DLCI h represents the three-dimensional space compatibility index of the plot h, C hj represents the compatibility coefficient between plots h and j, n represents the number of plots within the influence range of plot h, M j is the weighted land area ratio of the building area of ​​plot j, FA j is the building area of ​​plot j, and plot j is within the influence range of plot h, 3DSCI f is the three-dimensional spatial block scale compatibility index of block f, H represents the number of plots in block f, M h represents the building area weighted land area ratio between plot h and block f, FA h is the building area of ​​plot h, A j represents the land area of ​​plot j, A h Represents the land area of ​​plot h.

2. The method for calculating the land use mix degree taking into account three-dimensional space according to claim 1, It is characterized in that The preprocessing of the road data to obtain the block data comprises the following steps: S11, checking the consistency of the road data and removing overlapping roads; S12. Perform a topological check and remove overhanging roads and independent road sections.

3. The method for calculating the land use mixture degree taking into account three-dimensional space according to claim 1, It is characterized in that The urban data includes urban land use data, points of interest, building data and road data; Among them, the urban land use data includes residential land, commercial land, first-class industrial land, second-class industrial land, new-type industrial land, public service land, transportation land, logistics and warehousing land, special land and other land.

4. The method for calculating the land use mixture degree taking into account three-dimensional space according to claim 3, It is characterized in that The method of constructing a three-dimensional multi-angle mixed index to measure the land mixedness of each block in the city includes the following steps: S41. Combining the three perspectives, the land mix index is obtained at the block scale; S42. Standardize the three-dimensional diversity index, the three-dimensional accessibility index, and the three-dimensional compatibility index; S43, calculating the average value of the normalized values ​​of the three angle indices to obtain the three-dimensional multi-angle mixing index, and the calculation formula is: in, and They represent the three-dimensional diversity index, the three-dimensional accessibility index and the three-dimensional spatial block scale compatibility index 3DSCI respectively. f The normalized value of 3DMMDI represents the three-dimensional multi-angle mixing index.

5. The method for calculating the land use mixture degree taking into account three-dimensional space according to claim 1, It is characterized in that The accuracy verification of the three-dimensional multi-angle mixing index includes the following steps: S51. Change the research unit from block to community, and calculate the community 3D diversity index, community 3D accessibility index and community 3D compatibility index at the community scale, and then calculate the community 3D multi-angle mixed degree index 3DMMDI at the community scale based on their normalized values α ; S52, based on the M of each block V As a weighting coefficient, the three-dimensional multi-angle mixed index at the block scale is converted to the community scale to finally obtain the three-dimensional multi-angle mixed index at the community scale. The calculation formula is: Among them, M V represents the building area weighted land area ratio between block v and the corresponding community, A V represents the land area of ​​block v, FA V represents the building area of ​​block v, W represents the number of blocks in the corresponding community, and 3DMMDI β It represents the three-dimensional multi-angle mixedness index at the community scale; S53, Compare 3DMMDI α and 3DMMDI β Correlation, comparison 3DMMDI α 、3DMMDI β As well as the spatial distribution characteristics of 3DMMDI, the accuracy of the three-dimensional multi-angle mixing index 3DMMDI is verified; S54. Use taxi travel distance to verify the relationship with 3DMMDI.

6. A spatial mapping method for land use mixture degree taking into account three-dimensional space, used to realize the drawing of the spatial distribution map of the comprehensive calculation method of land use mixture degree taking into account three-dimensional space as described in claim 1, It is characterized in that The method comprises the following steps: Using geographic information system tools and the natural break point classification method, the quantitative results of three-dimensional diversity index, three-dimensional accessibility index, three-dimensional compatibility index and three-dimensional multi-angle mixing index were classified and mapped, and the spatial distribution maps of three-dimensional diversity, three-dimensional accessibility, three-dimensional compatibility and three-dimensional multi-angle mixing were obtained.

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