Urban low-efficiency land redevelopment space unit updating mode calculation method and system

Abstract

The invention provides a new urban low-efficiency land redevelopment space unit updating mode calculation method, and creatively provides an urban updating method framework under the territorial space planning background. According to the framework, a redevelopment space unit is delimited by utilizing the spatial position and attribute characteristics of urban low-efficiency land use data; evaluating the performance of the environment built by the redevelopment unit based on the dimensions of development intensity, environment quality, space accessibility and the like, and diagnosing main obstacle factors of the redevelopment unit by using an obstacle degree model; then, clustering the redevelopment unit obstacle factor features by using a K-means clustering algorithm to obtain an update mode type; finally, under the constraint of urban planning limitation and development conditions, multi-type low-efficiency land use influence factors and redevelopment space unit obstacle factors are comprehensively considered, and an urban-low-efficiency land use redevelopment space unit-low-efficiency land use updating strategy framework is formed in a matrix expression mode.

Description

Technical Field

[0001] The present invention relates to the technical field of computer data processing, and in particular to a method and system for calculating a spatial unit renewal mode for redevelopment of urban low-efficiency land. Background Art

[0002] As my country's urbanization development enters the middle and late stages, the urban development model has shifted from incremental expansion to stock optimization, and the redevelopment of urban inefficient land has become an important means to revitalize stock space. Currently, many cities have carried out practical explorations in the redevelopment of inefficient land, but there is still a lack of effective spatial quantification methods for the identification of inefficient land, analysis of influencing factors, and research on transformation strategies, which makes the scientific nature of urban inefficient land renewal actions insufficient.

[0003] At present, the methods for identifying inefficient land include literature analysis, hierarchical analysis, eighteen-equal division method, Delphi method, urban settlement model (AMM) analysis method, etc., or the use of mathematical methods such as Bayes discriminant function, or the compilation of performance coding and verification of the performance evaluation method of the responsibility positioning method. These methods are mainly based on qualitative discussions, which make it difficult to accurately identify inefficient land with complex diversity, and are not conducive to promoting efficient land use and optimizing land use structure.

[0004] The current research on renewal strategies for inefficient urban land has problems such as a single subject (mainly concentrated on industrial land), an imperfect land evaluation index system, strong subjective factors in weight ratios, a lack of verification methods, and a lack of multi-scale coordinated urban renewal decision-making support tools.

[0005] Existing research on renewal decision-making tools for inefficient urban land can be divided into non-spatial decision-making models and spatial decision-making models. Non-spatial decision-making models cannot propose specific renewal strategies from the perspective of spatial layout. Although existing spatial decision-making models have solved this problem, most of them can only be used for renewal plan decisions for small-scale plots. There are still few scientific quantitative plans suitable for large-scale renewal decisions.

[0006] Therefore, it is of great significance to improve the research on the renewal strategy of urban inefficient land. The research direction should focus on developing spatial decision support tools that can adapt to multi-scale coordination. Such tools will help to achieve scientific and refined management in the process of urban renewal and ensure the effectiveness and consistency of renewal strategies at different scales. Summary of the invention The main purpose of the present invention is to provide a method and system for calculating the spatial unit renewal model of urban low-efficiency land redevelopment to solve the above technical problems.

[0007] To achieve the above-mentioned purpose, the present invention provides a method for calculating the updating mode of urban low-efficiency land redevelopment space unit, comprising the steps of: S1, redevelopment unit division: obtaining urban low-efficiency land distribution data, and extracting multiple low-efficiency land clustering areas from the urban low-efficiency land according to preset clustering conditions as n urban redevelopment units; S2, built environment performance assessment, including: S21, construct an environmental performance evaluation index system, which includes 10 characteristics under the three categories of development intensity, environmental quality and spatial accessibility m , m∈[1,10]; S22, the TOPSIS method was used to calculate the comprehensive score of built environment performance of each urban redevelopment unit; S23, using the Getis-Ord Gi method to reveal the spatial differences in urban built environment performance; S3, calculation of main obstacle factors: using the obstacle degree model to perform pathological diagnosis of built environment performance and calculate the obstacle factors that affect built environment performance; S4, Renewal pattern identification: K-means machine learning algorithm is used to cluster the barrier degree, and the main renewal pattern of all urban redevelopment units is identified according to the barrier degree characteristics of each cluster; S5, combining the renewal mode of the city in the development unit with the influencing factors of the low-efficiency land use in the city's redevelopment unit, and obtaining the corresponding renewal strategy according to the corresponding relationship between the preset renewal mode and the influencing factors of the low-efficiency land use.

[0008] Preferably, the 10 features X in step S21 are m include: X1, floor area ratio FAR= ,in, is the base area of ​​building i, is the number of floors of building i, A is the area of ​​the study unit; X2, 400m Functional Diversity SN= ,in, is the percentage of the number of POIs of the i-th category to the number of all POIs in the unit; X3, green viewing rate GR= ,in, is the area of ​​trees, flowers, and grass in the street scene of unit i, and image is the total area of ​​the street scene; X4, openness OP= ,in, is the area of ​​the sky in the street scene of unit i, and image is the total area of ​​the street scene; X5, old building ratio OBR= ,in, is the total area of ​​buildings built before the preset number of years. is the total area of ​​all buildings within the unit; X6, public service coverage PSC= , where h is the width band, n is the number of poi, and K(x) is the kernel function; X7, Commercial Service Coverage CSC= , where h is the width band, n is the number of poi, and K(x) is the kernel function; X8, the nearest park distance NP = min ( ),in, is the walking distance from the study unit to the i-th park; X9, the distance to the nearest bus stop NB=min( ),in, is the walking distance from the study unit to the i-th bus stop; X 10 , the distance to the nearest subway station is NM=min( ),in, is the walking distance from the study unit to the i-th subway station.

[0009] Preferably, the step S22 includes: S221, for each urban redevelopment unit, the 10 characteristics X qm Perform standardization to obtain the standardized index value , where X qm represents the value of the mth indicator of the qth urban redevelopment unit, represents the standardized value of the mth indicator of the qth urban redevelopment unit; S222, calculate the distance D from the evaluation vector of different research units q to the positive ideal solution + The distance D from the positive ideal solution - , , q∈[1,n], is the positive ideal value in the mth index, Negative ideal value in the mth index; S223, , The value range of is [0,1]; The step S23 includes, by formula: ,in, represents the land use efficiency of the qth urban redevelopment unit, represents the qth urban redevelopment unit and the The spatial weight between urban redevelopment units, The average value of the comprehensive urban land efficiency scores of all urban redevelopment units, and S is the standard deviation of the comprehensive urban land efficiency scores of all urban redevelopment units.

[0010] Preferably, the step S221 includes: S2211, data standardization: X is standardized according to the following formula qm To standardize the data, (+) (-) in, represents the mth index of the qth urban redevelopment unit The value after data standardization, (+) indicates that the formula is used to process positive indicators, (-) indicates that the formula is used to process negative indicators, indicators NP, NB, NM are negative indicators; S2212, CRITIC weight calculation: calculated by formula, ,in, is the standard deviation of the mth indicator, is the mean difference of the mth indicator; ,in, is the conflict of the mth indicator, is the evaluation index m and the index The correlation coefficient of ,in, is the amount of information contained in the mth indicator; ,in, The objective weight of the mth indicator; Z = ), where Z represents the weighted normalized matrix.

[0011] Preferably, the preset aggregation conditions include at least two of the following conditions: The proportion of the floor area of ​​low-efficiency land in the total floor area of ​​the designated urban redevelopment unit shall not be less than the preset proportion; among which, the preset proportion in the urban core area is 30%-40%, and the preset proportion in the non-core area of ​​the city is lower than the preset proportion in the urban core area; The urban redevelopment units designated are located within the unified administrative management boundary; The total area of ​​the urban redevelopment unit is 0.5-3km 2 ; The designated urban redevelopment units must comply with the residential area boundaries of the 15-minute living circle; The delineated urban redevelopment units are areas with clear boundaries constructed in accordance with natural environmental conditions, district or street administrative boundaries, and property rights boundaries.

[0012] Preferably, step S3 comprises: ; in, represents the obstacle degree of the qth urban redevelopment unit at the mth indicator, is the deviation of the qth urban redevelopment unit on the mth indicator, It is the indicator weight calculated by entropy weight method.

[0013] Preferably, the step S4 comprises: S41, obtaining the obstacle factor whose obstacle degree meets the preset conditions , the obstacle factors of n urban redevelopment units that meet the preset conditions are As sample data; S42, randomly selecting k centroids from the sample data as initial cluster centers, and the centroids are recorded as: , , ..., ; S43, define the optimization goal, denoted as: ; S44, start the loop, calculate the distance from each sample point to the centroid, and assign it to each centroid, and get k clusters, which are recorded as: ; S45, for each cluster, calculate the average distance of all sample points assigned to the cluster as the new centroid, recorded as: ; S46, until J converges, all clusters no longer change, and clustering results with similar built environment obstacle characteristics are obtained; S47, identifying the update mode corresponding to each cluster according to the mean characteristics of the obstacle factor of each cluster.

[0014] Preferably, the factors affecting the formation of inefficient land include inefficient residential land, inefficient commercial land and inefficient industrial land.

[0015] The present invention also provides a computer system for calculating urban redevelopment unit renewal strategies based on low-efficiency land, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method for calculating the urban low-efficiency land redevelopment spatial unit renewal pattern as described in any one of the above items when executing the computer program.

[0016] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the method for calculating the urban low-efficiency land redevelopment spatial unit update pattern as described in any of the above items.

[0017] This paper proposes a new method for calculating the renewal mode of urban low-efficiency land redevelopment spatial units, and innovatively proposes a renewal decision framework based on redevelopment units. The framework first divides the redevelopment units using the clustering characteristics of urban low-efficiency land data, then measures the built environment performance based on dimensions such as development intensity, environmental quality and spatial accessibility and reveals its spatial differences, then uses the barrier model to diagnose the main barrier factors affecting the built environment performance, and finally uses the K-means machine learning algorithm to identify the renewal mode of different regions. Combined with the renewal mode of the city in the development unit and the influencing factors of the low-efficiency land in the urban redevelopment unit, the corresponding renewal strategy is obtained according to the correspondence between the preset renewal mode and the influencing factors of the low-efficiency land. A coordinated and holistic urban low-efficiency land renewal mode decision framework is established. First, the overall urban control requirements are determined, and the redevelopment behavior of urban low-efficiency land is constrained. Then, for different types of redevelopment units, the applicable renewal mode is clarified, and then the corresponding renewal strategy is formulated for each type of low-efficiency land. Finally, the corresponding renewal measures are determined for each type of low-efficiency land under each redevelopment unit. Such a multi-scale linkage plan is expected to achieve positive results in the coordinated renewal of urban areas, promote the efficient use of land resources, improve the urban environment, and enhance the quality of life of residents. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings are part of the present invention and are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention, but do not constitute an improper limitation of the present invention. Obviously, the drawings described below are only some embodiments. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. In the accompanying drawings: Figure 1 It is a flowchart of a method for calculating a spatial unit updating model for redevelopment of urban low-efficiency land in one embodiment of the present invention.

[0019] Figure 2 The figure is a schematic diagram of the hardware structure for running the calculation method of the urban low-efficiency land redevelopment space unit update mode in one embodiment of the present invention.

[0020] Figure 3 This is a logic diagram of a multi-scale linkage update scheme in a calculation method for a spatial unit update pattern for redevelopment of urban low-efficiency land in one embodiment of the present invention.

[0021] Figure 4It is a relationship diagram of the renewal strategy of the urban redevelopment unit renewal mode and the linkage of the redevelopment of low-efficiency land in the urban low-efficiency land redevelopment space unit renewal mode calculation method in one embodiment of the present invention.

[0022] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0023] The following is a clear and complete description of the technical problems solved by the embodiments of the present invention, the technical solutions adopted, and the technical effects achieved in conjunction with the accompanying drawings and specific embodiments. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other equivalent or obviously modified embodiments obtained by ordinary technicians in this field without creative work fall within the scope of protection of the present invention. The embodiments of the present invention can be concretized in a variety of different ways as defined and covered in the claims.

[0024] It should be noted that in the following description, many specific details are given for ease of understanding, but it is obvious that the present invention can be implemented without these specific details.

[0025] It should be noted that, in the absence of clear limitation or conflict, the various embodiments of the present invention and the technical features therein can be combined with each other to form a technical solution.

[0026] The present invention proposes a method for calculating a spatial unit renewal model for urban low-efficiency land redevelopment, comprising the following steps: S1, redevelopment unit division: obtaining urban low-efficiency land distribution data, and extracting multiple low-efficiency land clustering areas from the urban low-efficiency land according to preset clustering conditions as n urban redevelopment units; S2, built environment performance assessment, including: S21, construct an environmental performance evaluation index system, which includes 10 characteristics under the three categories of development intensity, environmental quality and spatial accessibility m , m∈[1,10]; S22, the TOPSIS method was used to calculate the comprehensive score of built environment performance of each urban redevelopment unit; S23, using the Getis-Ord Gi method to reveal the spatial differences in urban built environment performance; S3, calculation of main obstacle factors: using the obstacle degree model to perform pathological diagnosis of built environment performance and calculate the obstacle factors that affect built environment performance; S4, Renewal pattern identification: K-means machine learning algorithm is used to cluster the barrier degree, and the main renewal pattern of all urban redevelopment units is identified according to the barrier degree characteristics of each cluster; S5, combining the renewal mode of the city in the development unit with the influencing factors of the low-efficiency land use in the city's redevelopment unit, and obtaining the corresponding renewal strategy according to the corresponding relationship between the preset renewal mode and the influencing factors of the low-efficiency land use.

[0027] Specifically, in step S1, the preset aggregation conditions include at least two of the following conditions: The proportion of the floor area of ​​low-efficiency land in the total floor area of ​​the designated urban redevelopment unit shall not be less than the preset proportion; among which, the preset proportion in the urban core area is 30%-40%, and the preset proportion in the non-core area of ​​the city is lower than the preset proportion in the urban core area; The designated urban redevelopment units are located within the unified administrative management boundary; The total area of ​​the urban redevelopment unit is 0.5-3km 2 ; The designated urban redevelopment units must comply with the residential area boundaries of the 15-minute living circle; The delineated urban redevelopment units are areas with clear boundaries constructed in accordance with natural environmental conditions, district or street administrative boundaries, and property rights boundaries.

[0028] In addition, the urban inefficient land distribution data in step S1 can be evaluated and obtained using methods in the prior art, such as the inefficient land extraction method proposed in the article "Identification of Inefficient Urban Land for Urban Regeneration Considering Land Use Differentiation" by Jin et al.

[0029] Preferably, the 10 features X in step S21 are m include: X1, floor area ratio FAR= ,in, is the base area of ​​building i, is the number of floors of building i, A is the area of ​​the study unit; X2, 400m Functional Diversity SN= ,in, is the percentage of the number of POIs of the i-th category to the number of all POIs in the unit; X3, green viewing rate GR= ,in, is the area of ​​trees, flowers, and grass in the street scene of unit i, and image is the total area of ​​the street scene; X4, openness OP= ,in, is the area of ​​the sky in the street scene of unit i, and image is the total area of ​​the street scene; X5, old building ratio OBR= ,in, is the total area of ​​buildings built before the preset number of years. is the total area of ​​all buildings within the unit; X6, public service coverage PSC= , where h is the width band, n is the number of poi, and K(x) is the kernel function; X7, Commercial Service Coverage CSC= , where h is the width band, n is the number of poi, and K(x) is the kernel function; X8, the nearest park distance NP = min ( ),in, is the walking distance from the study unit to the i-th park; X9, the distance to the nearest bus stop NB=min( ),in, is the walking distance from the study unit to the i-th bus stop; X 10 , the distance to the nearest subway station is NM=min( ),in, is the walking distance from the study unit to the i-th subway station.

[0030] Preferably, the step S22 includes: S221, for each urban redevelopment unit, the 10 characteristics X qm Perform standardization to obtain the standardized index value , where X qm represents the value of the mth indicator of the qth urban redevelopment unit, represents the standardized value of the mth indicator of the qth urban redevelopment unit; S222, calculate the distance D from the evaluation vector of different research units q to the positive ideal solution + The distance D from the positive ideal solution -， , , q∈[1,n], is the positive ideal value in the mth index, Negative ideal value in the mth index; S223, , The value range of is [0,1]; The step S23 includes, by formula: ,in, represents the land use efficiency of the qth urban redevelopment unit, represents the qth urban redevelopment unit and the The spatial weight between urban redevelopment units, The average value of the comprehensive urban land efficiency scores of all urban redevelopment units, and S is the standard deviation of the comprehensive urban land efficiency scores of all urban redevelopment units.

[0031] Preferably, the step S221 includes: S2211, data standardization: X is standardized according to the following formula qm To standardize the data, (+) (-) in, represents the mth index of the qth urban redevelopment unit The value after data standardization, (+) indicates that the formula is used to process positive indicators, (-) indicates that the formula is used to process negative indicators, indicators NP, NB, NM are negative indicators; S2212, CRITIC weight calculation: calculated by formula, ,in, is the standard deviation of the mth indicator, is the mean difference of the mth indicator; ,in, is the conflict of the mth indicator, is the evaluation index m and the index The correlation coefficient of ,in, is the amount of information contained in the mth indicator; ,in, The objective weight of the mth indicator; Z = ), where Z represents the weighted normalized matrix.

[0032] Preferably, step S3 comprises: ; in, represents the obstacle degree of the qth urban redevelopment unit at the mth indicator, is the deviation of the qth urban redevelopment unit on the mth indicator, It is the indicator weight calculated by entropy weight method.

[0033] Furthermore, the indicators with a medium barrier degree greater than 0.1 (the mean barrier degree of all indicators) in each sample (city under development unit) can be regarded as the main barrier factors of the sample. In addition, this study calculated the mean barrier degree of each indicator and regarded the indicators with a mean greater than 0.1 as the main barrier factors of the built environment performance of all analysis units.

[0034] Preferably, the step S4 comprises: S41, obtaining the obstacle factor whose obstacle degree meets the preset conditions , the obstacle factors of n urban redevelopment units that meet the preset conditions are As sample data; S42, randomly selecting k centroids from the sample data as initial cluster centers, and the centroids are recorded as: , , ..., ; S43, define the optimization goal, denoted as: ; S44, start the loop, calculate the distance from each sample point to the centroid, and assign it to each centroid, and get k clusters, which are recorded as: ; S45, for each cluster, calculate the average distance of all sample points assigned to the cluster as the new centroid, recorded as: ; S46, until J converges, all clusters no longer change, and clustering results with similar built environment obstacle characteristics are obtained; S47, identifying the update mode corresponding to each cluster according to the mean characteristics of the obstacle factor of each cluster.

[0035] Specifically, the value of k can be obtained by k , elbow rule estimation or Canopy algorithm calculation, etc., which will not be described in detail here; after using the barrier value to perform K-means clustering, the F statistic table shows the n value with the largest F statistic. The maximum pseudo F statistic value indicates the best solution in maximizing the similarity within the cluster and the difference between clusters, and the optimal number of clusters n is taken. Then, the clustering results are subjected to a one-way ANOVA to obtain the F value and p value of each category. Check that the p value of the indicator has passed the significance test. If it passes, it can be considered that the clustering results are basically reasonable.

[0036] According to the mean characteristics of the obstacle factor of each cluster, for example, when analyzing the inefficient land use in Changsha city by the method of this embodiment, it is obtained that Cluster 1 has the highest obstacle ratio, the distance to the nearest bus stop, and the sky openness compared with the mean obstacle ratio of the other three clusters, and the obstacle ratio of the green view rate is second, among which the obstacle ratio of the old building ratio is the most significant, and the obstacle ratio of the nearest bus stop is relatively small. This shows that the cluster has problems such as old buildings, narrow streets, lack of green and public space, which affects the image of the city and the quality of life of residents. However, the obstacle ratio, public service coverage, and POI function richness of the cluster are the smallest, indicating that the urban functions of the region are mature and complete, with high development potential and vitality.

[0037] Therefore, according to the existing urban renewal theory, it can be obtained that the cluster is a historical and cultural protection and renovation area; when carrying out urban renewal, the renewal model corresponding to the historical and cultural protection and renovation area is selected, such as including but not limited to paying attention to the protection of historical and cultural heritage while reasonably demolishing and renovating old buildings, improving the level of urban design, increasing green and open spaces, and improving the livability and vitality of the city.

[0038] The urban renewal theories under other different theories will not be elaborated here. This embodiment mainly clusters the obstacle degree by using the K-means machine learning algorithm based on steps S1-S3 through step S4, and identifies the main renewal mode of all urban redevelopment units according to the obstacle degree characteristics of each cluster. Instead of directly determining the renewal mode of urban redevelopment units through unreasonable means such as experience and regional division.

[0039] Please combine Figure 3 and Figure 4 Preferably, the factors affecting the formation of inefficient land include inefficient residential land, inefficient commercial land and inefficient industrial land.

[0040] In another specific example, in the process of implementing urban renewal, the control requirements of special areas such as historical protection and ecological protection that overlap with the overall national land space plan and related statutory plans must be strictly observed. These requirements involve aspects such as cultural heritage protection and ecological security, and are indispensable rigid control elements in urban renewal. Under the constraints of urban planning restrictions and development conditions, comprehensive consideration of the influencing factors of multiple types of inefficient land and the barrier factors of redevelopment space units is used to form a city-inefficient land redevelopment space unit-inefficient land renewal strategy framework through matrix expression. Specific transmission rules include but are not limited to the following points: (1) Regulatory Detailed Planning: Regulatory Detailed Planning (hereinafter referred to as Regulatory Planning) is an important part of the urban planning system. It sets specific requirements for the land use nature, construction density, building height, road traffic and public facilities layout of a specific area. The main purpose of Regulatory Planning is to ensure the consistency of urban development with the overall plan, while protecting and improving the functions and environmental quality of the city. In urban renewal, Regulatory Planning, as a rigid regulation, plays a strict guiding and restraining role in the design and implementation of renewal projects.

[0041] (2) Urban blue line and green line: Urban blue line refers to the water system protection area in the city, including rivers, lakes, reservoirs and other water bodies and their surrounding areas. Urban green line refers to the green protection area in the city, such as parks, nature reserves, scenic spots, etc. The establishment of urban blue line and green line is aimed at protecting and improving the urban ecological environment, maintaining water resource security, and promoting sustainable urban development. In the process of urban renewal, the control requirements of blue line and green line must be strictly observed. For renewal projects located in or around these areas, measures should be taken to reduce the impact on the ecological environment, such as restricting construction activities and strengthening ecological restoration.

[0042] (3) Historical and cultural protection: Historical and cultural protection aims to protect the city's historical relics, traditional features and cultural characteristics. In urban renewal, buildings and areas with important historical, artistic and scientific values ​​should be given special protection to prevent irreversible cultural heritage losses caused by renewal. The historical and cultural protection scale of Changsha City is 5.10 km2. Historical and cultural streets, historical areas, historical buildings and cultural relics protection units at or above the municipal level need to be protected and repaired. Renewal actions within historical and cultural protection areas should follow the principle of repairing the old as it is, respect the historical context, maintain the integrity and continuity of the historical environment, and preserve the traditional street texture of the historical protection area.

[0043] In order to improve the coordination of urban low-efficiency land redevelopment actions, this study combined the renewal modes of four types of redevelopment units and the influencing factors of the formation of three types of low-efficiency land, and constructed a renewal strategy that links unit coordination with the redevelopment of low-efficiency land, including 12 types of renewal guidelines, such as Figure 4 .

[0044] The present invention also provides a computer system for calculating urban redevelopment unit renewal strategies based on low-efficiency land, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method for calculating the urban low-efficiency land redevelopment spatial unit renewal pattern as described in any one of the above items when executing the computer program.

[0045] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the method for calculating the urban low-efficiency land redevelopment spatial unit update pattern as described in any of the above items.

[0046] Figure 2 FIG. 1 is a schematic diagram of the hardware structure of a computer device / system for running a method for calculating a spatial unit update pattern for urban low-efficiency land redevelopment provided by an embodiment of the present invention. Figure 3 As shown, the embodiment / computer 6 includes: a processor 60, a memory 61, and a computer program 62 stored in the memory 61 and executable on the processor 60, such as a program for executing the software comprehensive quality assessment method. When the processor 60 executes the computer program 62, the steps in the above-mentioned embodiments of the software comprehensive quality assessment method are implemented. Alternatively, when the processor 60 executes the computer program 62, the functions of the modules / units in the above-mentioned device embodiments are implemented.

[0047] Exemplarily, the computer program 62 may be divided into one or more modules / units, which are stored in the memory 61 and executed by the processor 60 to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, and the instruction segments are used to describe the execution process of the computer program 62 in the computer 6.

[0048] The computer 6 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The computer 6 may include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art will appreciate that Figure 3 It is only an example of computer 6 and does not constitute a limitation of computer 6. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the computer 6 may also include input and output devices, network access devices, buses, etc.

[0049] The processor 60 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0050] The memory 61 may be an internal storage unit of the computer 6, such as a hard disk or memory of the computer 6. The memory 61 may also be an external storage device of the terminal device 6, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the terminal device. Further, the memory 61 may include both an internal storage unit of the computer 6 and an external storage device. The memory 61 is used to store the computer program and other programs and data required by the terminal device. The memory 61 may also be used to temporarily store data that has been output or is to be output.

[0051] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0052] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0053] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0054] In the embodiments provided by the present invention, it should be understood that the disclosed devices / terminal equipment and methods can be implemented in other ways. For example, the device / terminal equipment embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0055] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0056] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0057] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0058] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A method for calculating the spatial unit renewal model of urban low-efficiency land redevelopment, characterized in that: Includes steps: S1, redevelopment unit division: obtain the urban low-efficiency land distribution data, and extract multiple low-efficiency land clusters from the urban low-efficiency land according to the preset clustering conditions as n urban redevelopment units; S2, built environment performance assessment, including: S21, construct an environmental performance evaluation index system, which includes 10 characteristics under the three categories of development intensity, environmental quality and spatial accessibility m , m∈[1,10]; S22, the TOPSIS method was used to calculate the comprehensive score of built environment performance of each urban redevelopment unit; S23, using the Getis-Ord Gi method to reveal the spatial differences in urban built environment performance; S3, calculation of main obstacle factors: using the obstacle degree model to perform pathological diagnosis of built environment performance and calculate the obstacle factors that affect built environment performance; S4, Renewal pattern identification: K-means machine learning algorithm is used to cluster the barrier degree, and the main renewal pattern of all urban redevelopment units is identified according to the barrier degree characteristics of each cluster; S5, acquisition of renewal strategy: combining the renewal mode of the city in the development unit with the influencing factors of the low-efficiency land use in the city's redevelopment unit, and obtaining the corresponding renewal strategy according to the corresponding relationship between the preset renewal mode and the influencing factors of the low-efficiency land use.

2. The calculation method for urban low-efficiency land redevelopment space unit renewal model according to claim 1 is characterized by: The 10 features X in step S21 m include: X1, floor area ratio FAR= ,in, is the base area of ​​building i, is the number of floors of building i, A is the area of ​​the study unit; X2, 400m Functional Diversity SN= ,in, is the percentage of the number of POIs of the i-th category to the number of all POIs in the unit; X3, green viewing rate GR= ,in, is the area of ​​trees, flowers, and grass in the street scene of unit i, and image is the total area of ​​the street scene; X4, openness OP= ,in, is the area of ​​the sky in the street scene of unit i, and image is the total area of ​​the street scene; X5, old building ratio OBR= ,in, is the total area of ​​buildings built before the preset number of years. is the total area of ​​all buildings within the unit; X6, public service coverage PSC= , where h is the width band, n is the number of poi, and K(x) is the kernel function; X7, Commercial Service Coverage CSC= , where h is the width band, n is the number of poi, and K(x) is the kernel function; X8, the nearest park distance NP = min ( ),in, is the walking distance from the study unit to the i-th park; X9, the distance to the nearest bus stop NB=min( ),in, is the walking distance from the study unit to the i-th bus stop; X 10 , the distance to the nearest subway station is NM=min( ),in, is the walking distance from the study unit to the i-th subway station.

3. The calculation method for urban low-efficiency land redevelopment space unit renewal model according to claim 2 is characterized in that: The step S22 comprises: S221, for each urban redevelopment unit, the 10 characteristics X qm Perform standardization to obtain the standardized index value , where X qm represents the value of the mth indicator of the qth urban redevelopment unit, represents the standardized value of the mth indicator of the qth urban redevelopment unit; S222, calculate the distance D from the evaluation vector of different research units q to the positive ideal solution + The distance D from the positive ideal solution - , , q∈[1,n], is the positive ideal value in the mth index, Negative ideal value in the mth index; S223, , The value range of is [0,1]; The step S23 includes, by formula: ,in, represents the land use efficiency of the qth urban redevelopment unit, represents the qth urban redevelopment unit and the The spatial weight between urban redevelopment units, It represents the average value of the comprehensive scores of urban land efficiency of all urban redevelopment units, and S is the standard deviation of the comprehensive scores of urban land efficiency of all urban redevelopment units.

4. The calculation method for urban low-efficiency land redevelopment space unit renewal model according to claim 3 is characterized by: The step S221 includes: S2211, data standardization: X is standardized according to the following formula qm To standardize the data, (+) (-) in, represents the mth index of the qth urban redevelopment unit The value after data standardization, (+) indicates that the formula is used to process positive indicators, (-) indicates that the formula is used to process negative indicators, indicators NP, NB, NM are negative indicators; S2212, CRITIC weight calculation: calculated by formula, ,in, is the standard deviation of the mth indicator, is the mean difference of the mth indicator; ,in, is the conflict of the mth indicator, is the evaluation index m and the index The correlation coefficient of ,in, is the amount of information contained in the mth indicator; ,in, The objective weight of the mth indicator; Z = ), where Z represents the weighted normalized matrix.

5. The calculation method for urban low-efficiency land redevelopment space unit renewal model according to claim 1 is characterized in that: The preset aggregation conditions include at least two of the following conditions: The proportion of the floor area of ​​low-efficiency land in the total floor area of ​​the designated urban redevelopment unit shall not be less than the preset proportion; among which, the preset proportion in the urban core area is 30%-40%, and the preset proportion in the non-core area of ​​the city is lower than the preset proportion in the urban core area; The urban redevelopment units designated are located within the unified administrative management boundary; The total area of ​​the urban redevelopment unit is 0.5-3km 2 ; The designated urban redevelopment units must comply with the residential area boundaries of the 15-minute living circle; The delineated urban redevelopment units are areas with clear boundaries constructed in accordance with natural environmental conditions, district or street administrative boundaries, and property rights boundaries.

6. The calculation method for urban low-efficiency land redevelopment space unit renewal model according to claim 3 is characterized by: The step S3 comprises: ; in, represents the obstacle degree of the qth urban redevelopment unit at the mth indicator, is the deviation of the qth urban redevelopment unit on the mth indicator, It is the indicator weight calculated by entropy weight method.

7. The method for calculating the updating mode of urban low-efficiency land redevelopment space unit according to claim 6 is characterized in that: The step S4 comprises: S41, obtaining the obstacle factor whose obstacle degree meets the preset conditions , the obstacle factors of n urban redevelopment units that meet the preset conditions are As sample data; S42, randomly selecting k centroids from the sample data as initial cluster centers, and the centroids are recorded as: , , ..., ; S43, define the optimization goal, denoted as: ; S44, start the loop, calculate the distance from each sample point to the centroid, and assign it to each centroid, and get k clusters, which are recorded as: ; S45, for each cluster, calculate the average distance of all sample points assigned to the cluster as the new centroid, recorded as: ; S46, until J converges, all clusters no longer change, and clustering results with similar built environment obstacle characteristics are obtained; S47, identifying the update mode corresponding to each cluster according to the mean characteristics of the obstacle factor of each cluster.

8. The calculation method for urban low-efficiency land redevelopment space unit renewal model according to claim 7 is characterized by: The factors affecting the formation of inefficient land include inefficient residential land, inefficient commercial land and inefficient industrial land.

9. A computer system for calculating the renewal strategy of urban redevelopment units based on low-efficiency land, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method for calculating the urban low-efficiency land redevelopment space unit update pattern as described in any one of claims 1 to 8 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for calculating the urban low-efficiency land redevelopment spatial unit update pattern as described in any one of claims 1 to 8 are implemented.

Images