Urban facility distribution balance evaluation method and system based on space Gini coefficient and reachability analysis

Abstract

The invention discloses an urban facility distribution balance evaluation method and system based on a spatial Gini coefficient and reachability analysis, and relates to the technical field of urban planning design, and the method comprises the following steps: obtaining urban facility related data, road traffic network data and residential area related data in a target area; constructing a motion model corresponding to the plurality of traffic modes, and performing simulation operation in combination with the urban facility related data, the road traffic network data and the residential area related data to obtain a plurality of corresponding path sets; screening the path set, and determining a corresponding space Gini coefficient in combination with a screening result; determining an actual threshold value of the spatial Gini coefficient, and comparing the spatial Gini coefficient by combining the actual threshold value; according to the method, a more comprehensive and accurate evaluation tool is provided by combining the spatial imbalance measurement and reachability evaluation, and the method is suitable for complex urban planning and public service layout optimization.

Description

Technical Field

[0001] The present invention relates to the technical field of urban planning and design, and more particularly to a method and system for evaluating the distribution balance of urban facilities based on spatial Gini coefficient and accessibility analysis. Background Art

[0002] Urban facilities are a broad concept encompassing the various material infrastructures that provide services for residents' lives, work, leisure, and entertainment. Parks and green spaces, as a crucial component of urban facilities, perform numerous important functions. With the accelerated pace of urbanization and the continuous increase in urban populations, the conflict between population and land has become increasingly prominent. However, the available space for urban facilities (such as parks and green spaces, as recreational areas) is very limited, and the spatial layout faces serious inequality, resulting in limited access to adequate urban facilities for residents in some areas. To address this issue, scientific analytical methods and tools are crucial.

[0003] The Gini coefficient is an indicator used in economics to measure income inequality. Introducing this concept into spatial analysis can assess the degree of imbalance in the distribution of urban facilities. The spatial Gini coefficient has been applied to balance analysis in urban land use, the distribution of public facilities, and the allocation of environmental resources.

[0004] However, the spatial Gini coefficient is used to measure the degree of imbalance in the distribution of spatial resources, and it has the following main problems:

[0005] First, the spatial Gini coefficient is simple and intuitive for evaluating land use, medical facilities, educational resources, and other areas, and can quantify the degree of imbalance. However, this method focuses on spatial distribution and area size, but does not consider the spatial resources available to people, that is, the spatial resources that are actually accessible and available.

[0006] Second, accessibility analysis assesses how easily residents can reach specific public facilities (such as parks, hospitals, and schools). GIS network analysis tools are often used to analyze service areas and shortest paths. These analyses take into account actual transportation networks and time costs, reflecting residents' actual experiences. However, while this method can only qualitatively reflect residents' ease of access to specific facilities, it lacks an assessment of the spatial distribution of accessible resources and cannot directly reflect the balance of urban spatial infrastructure resources.

[0007] Therefore, how to provide a method for evaluating the balance of urban facility distribution that can solve the above problems is an urgent problem that those skilled in the art need to solve. Summary of the Invention

[0008] In view of this, the present invention provides a method and system for evaluating the balance of urban facility distribution based on the spatial Gini coefficient and accessibility analysis. By combining spatial imbalance measurement and accessibility assessment, a more comprehensive and accurate evaluation tool is provided, which is suitable for complex urban planning and public service layout optimization.

[0009] In order to achieve the above object, the present invention adopts the following technical solutions:

[0010] A method for evaluating the balance of urban facility distribution based on spatial Gini coefficient and accessibility analysis includes the following steps:

[0011] Obtain data related to urban facilities, road traffic network, and settlements in the target area;

[0012] Construct motion models corresponding to multiple transportation modes, and conduct simulations based on relevant data on urban facilities, road traffic networks, and settlements to obtain corresponding multiple path sets;

[0013] Filter the path set and determine the corresponding spatial Gini coefficient based on the screening results;

[0014] An actual threshold value of the spatial Gini coefficient is determined, and the spatial Gini coefficients are compared based on the actual threshold value.

[0015] Preferably, the specific process of obtaining the corresponding multiple path sets includes:

[0016] Select walking, cycling, and driving as modes of transportation, and construct corresponding walking motion models, cycling motion models, and driving motion models respectively;

[0017] Preprocessing the urban facility related data, road traffic network data, and settlement related data, and performing simulation operations in combination with the walking motion model, cycling motion model, and vehicle motion model;

[0018] The corresponding first walking path set, first cycling path set, and first vehicle path set are determined according to the simulation results.

[0019] Preferably, the specific process of constructing the corresponding walking motion model, cycling motion model, and vehicle motion model further includes:

[0020] Obtain the actual traffic data of the current target area to modify the walking motion model, cycling motion model, and vehicle motion model;

[0021] The final walking motion model, cycling motion model and vehicle motion model are obtained according to the correction results.

[0022] Preferably, the specific process of determining the corresponding spatial Gini coefficient includes:

[0023] Determine walking motion constraints, cycling motion constraints, and vehicle motion constraints respectively;

[0024] Filtering the first walking path set, the first cycling path set, and the first vehicle path set according to the walking motion constraint condition, the cycling motion constraint condition, and the vehicle motion constraint condition to obtain corresponding second walking path set, second cycling path set, and second vehicle path set;

[0025] The spatial Gini coefficient is calculated based on the number of paths included in the second walking path set, the second cycling path set, and the second vehicle path set, and the number of paths included in the first walking path set, the first cycling path set, and the first vehicle path set.

[0026] Preferably, the specific calculation process of obtaining the spatial Gini coefficient further includes:

[0027] Obtain the historical number of walking paths, cycling paths, and vehicle paths in the target area, and calculate the corresponding mean number of walking paths, cycling paths, and vehicle paths;

[0028] The corresponding cycling Gini coefficient, cycling Gini coefficient, and vehicle Gini coefficient are calculated by combining the mean number of walking paths, the mean number of cycling paths, the mean number of vehicle paths, the number of paths included in the first walking path set, the first cycling path set, the first vehicle path set, the second walking path set, the second cycling path set, and the second vehicle path set.

[0029] Preferably, the specific process of determining the actual threshold value of the spatial Gini coefficient includes:

[0030] Construct a threshold decision model;

[0031] The urban facility-related data, road traffic network data, settlement-related data, the second walking path set, the second cycling path set, the second vehicle path set, the walking movement constraints, the cycling movement constraints, and the vehicle movement constraints are respectively input into the threshold decision model for processing to obtain the corresponding actual walking Gini coefficient threshold, the actual cycling Gini coefficient threshold, and the actual vehicle Gini coefficient threshold.

[0032] The present invention also provides an urban facility distribution balance evaluation system based on spatial Gini coefficient and accessibility analysis, comprising:

[0033] An acquisition module is used to obtain data related to urban facilities, road traffic network data, and settlements in the target area;

[0034] The simulation module is used to build motion models corresponding to multiple transportation modes, and to perform simulations based on data related to urban facilities, road traffic networks, and settlements to obtain corresponding sets of paths.

[0035] The screening module is used to screen the path set and determine the corresponding spatial Gini coefficient based on the screening results;

[0036] The comparison module is used to determine an actual threshold value of the spatial Gini coefficient and compare the spatial Gini coefficient in combination with the actual threshold value.

[0037] It can be seen from the above technical solutions that, compared with the prior art, the present invention discloses a method and system for evaluating the balance of urban facility distribution based on spatial Gini coefficient and accessibility analysis, which has the following beneficial effects:

[0038] 1. The present invention introduces multiple modes of transportation, including walking, cycling, and driving, and constructs motion models for them respectively, fully considering the differences in urban facilities accessible to residents under different transportation modes. Compared with the analysis method of a single transportation mode, it can more comprehensively and accurately reflect the actual accessibility of urban facilities, making the evaluation results more scientific and authentic. At the same time, the present invention corrects the motion model by obtaining actual traffic data in the current target area, ensuring that the model's parameters and assumptions are more in line with actual traffic conditions, further improving the accuracy and reliability of the simulation results.

[0039] 2. This invention integrates data related to urban facilities, road traffic network data, and settlement data, and analyzes the relationship between the distribution of urban facilities and residents' needs from multiple dimensions. It avoids the one-sidedness that may be caused by a single data source and can more systematically and comprehensively evaluate the balance of urban facility distribution.

[0040] The present invention screens the initial path sets under different transportation modes to obtain a valid path set that better meets the actual motion constraints, and compares and analyzes it with the original path number, so as to more accurately grasp the changes in the accessibility and distribution balance of urban facilities under different transportation modes.

[0041] 3. This invention constructs a threshold decision model to determine the actual threshold of the spatial Gini coefficient, providing a clear quantitative standard for evaluating the balance of urban infrastructure distribution. By comparing it with the actual threshold, it is possible to clearly determine whether the distribution of urban infrastructure is balanced and the extent of imbalance.

[0042] 4. Through scientific calculation and analysis, the present invention obtains the quantitative spatial Gini coefficient and the comparison results with the actual threshold, providing intuitive and clear quantitative indicators for urban planners and decision makers. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0044] Figure 1 This is an overall flow chart of a method for evaluating the balance of urban facility distribution based on spatial Gini coefficient and accessibility analysis provided by the present invention;

[0045] Figure 2 This is a structural principle block diagram of an urban facility distribution balance evaluation system based on spatial Gini coefficient and accessibility analysis provided by the present invention. DETAILED DESCRIPTION

[0046] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0047] See also Figure 1 As shown, the embodiment of the present invention discloses a method for evaluating the balance of urban facility distribution based on spatial Gini coefficient and accessibility analysis, comprising the following steps:

[0048] Acquire data related to urban facilities, road traffic network data, and settlements in the target area. The data related to urban facilities may be GIS data of urban facilities. The road traffic network data may include various types of data, such as road traffic network structure data (e.g., road topology, connections with other roads, etc.), traffic flow data, etc. The settlement data may include settlement location data, population data, surrounding environment data, etc.

[0049] Construct motion models corresponding to multiple transportation modes, and conduct simulations based on relevant data on urban facilities, road traffic networks, and settlements to obtain corresponding multiple path sets;

[0050] Filter the path set and determine the corresponding spatial Gini coefficient based on the screening results;

[0051] Determine the actual threshold of the spatial Gini coefficient and compare the spatial Gini coefficients based on the actual threshold.

[0052] In a specific embodiment, the specific process of obtaining the corresponding multiple path sets includes:

[0053] Walking, cycling, and driving are selected as modes of transportation, and corresponding walking, cycling, and driving motion models are constructed respectively. In the process of establishing the walking, cycling, and driving motion models, the conventional speed, conventional travel radius, and conventional travel frequency of the corresponding modes of transportation are obtained through big data, and then combined with the conventional transportation tool model to achieve the desired results.

[0054] Pre-processing urban facility-related data, road traffic network data, and residential area-related data, and combining them with walking motion models, cycling motion models, and vehicle motion models to perform simulation operations. The above simulation process can be implemented using relevant computer software;

[0055] The corresponding first walking path set, first cycling path set and first vehicle path set are determined according to the simulation results. In the process of determining the corresponding path set, the specific location of a park green space is used as the end point and a certain residential area is used as the starting point to perform path planning.

[0056] In a specific embodiment, the specific process of constructing the corresponding walking motion model, cycling motion model, and vehicle motion model further includes:

[0057] Obtain the actual traffic data of the current target area to modify the walking motion model, cycling motion model, and vehicle motion model;

[0058] The final walking motion model, cycling motion model and vehicle motion model are obtained according to the correction results.

[0059] In a specific embodiment, the specific process of determining the corresponding spatial Gini coefficient includes:

[0060] Determine walking motion constraints, cycling motion constraints, and vehicle motion constraints respectively;

[0061] The first walking path set, the first cycling path set, and the first vehicle path set are filtered according to the walking motion constraint condition, the cycling motion constraint condition, and the vehicle motion constraint condition to obtain corresponding second walking path set, second cycling path set, and second vehicle path set, wherein the walking motion constraint condition may include parameters such as environmental factors, speed, and road conditions; the cycling motion constraint condition may include parameters such as real-time road conditions, environmental factors, speed, and road conditions; and the vehicle motion constraint condition may include parameters such as real-time road conditions, driving cost, and vehicle speed;

[0062] The spatial Gini coefficient is calculated based on the number of paths included in the second walking path set, the second cycling path set, and the second vehicle path set, and the number of paths included in the first walking path set, the first cycling path set, and the first vehicle path set.

[0063] In a specific embodiment, the specific calculation process of obtaining the spatial Gini coefficient further includes:

[0064] Obtain the historical number of walking paths, cycling paths, and vehicle paths in the target area, and calculate the corresponding mean number of walking paths, cycling paths, and vehicle paths;

[0065] The corresponding cycling Gini coefficient, cycling Gini coefficient, and vehicle Gini coefficient are calculated by combining the mean number of walking paths, the mean number of cycling paths, the mean number of vehicle paths, the number of paths included in the first walking path set, the first cycling path set, the first vehicle path set, the second walking path set, the second cycling path set, and the second vehicle path set. The corresponding specific expressions are:

[0066]

[0067] Where G 步 represents the walking Gini coefficient, K i1 represents the number of paths contained in the first walking path set, K j1 Indicates the number of paths included in the second walking path set, represents the mean number of walking paths; G 骑 represents the cycling Gini coefficient, K i2 represents the number of paths included in the first cycling path set, K j2 Indicates the number of paths included in the second cycling path set, represents the mean number of cycling paths; G 车 represents the walking Gini coefficient, K i3 represents the number of paths included in the first vehicle path set, K j3 Indicates the number of paths included in the second vehicle path set, Represents the mean number of vehicle paths.

[0068] In a specific embodiment, the specific process of determining the actual threshold value of the spatial Gini coefficient includes:

[0069] Constructing a threshold decision model, wherein the threshold decision model can be a comprehensive decision model combining SVM and decision tree;

[0070] The urban facilities related data, road traffic network data, settlement related data, the second walking path set, the second cycling path set and the second vehicle path set, walking movement constraints, cycling movement constraints and vehicle movement constraints are respectively input into the threshold decision model for processing to obtain the corresponding actual walking Gini coefficient threshold, actual cycling Gini coefficient threshold and actual vehicle Gini coefficient threshold.

[0071] Specifically, the above processing may further include:

[0072] The actual walking Gini coefficient threshold, the actual cycling Gini coefficient threshold and the actual vehicle Gini coefficient threshold are compared with the corresponding actual walking Gini coefficient threshold, the actual cycling Gini coefficient threshold and the actual vehicle Gini coefficient threshold. When the threshold requirements are not met, it means that the supply of facilities is insufficient at this time, and it is necessary to match the surrounding areas of the target area. After matching, the corresponding Gini coefficient is recalculated until the coefficient meets the actual threshold requirements.

[0073] See also Figure 2 As shown, an embodiment of the present invention further provides a system for evaluating the balance of urban facility distribution based on the spatial Gini coefficient and accessibility analysis described in any one of the above embodiments, comprising:

[0074] An acquisition module is used to obtain data related to urban facilities, road traffic network data, and settlements in the target area;

[0075] The simulation module is used to build motion models corresponding to multiple transportation modes, and to perform simulations based on data related to urban facilities, road traffic networks, and settlements to obtain corresponding sets of paths.

[0076] The screening module is used to screen the path set and determine the corresponding spatial Gini coefficient based on the screening results;

[0077] The comparison module is used to determine the actual threshold of the spatial Gini coefficient and compare the spatial Gini coefficient based on the actual threshold.

[0078] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Reference can be made to the common and similar parts between the various embodiments. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method description.

[0079] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for evaluating the balance of urban facility distribution based on spatial Gini coefficient and accessibility analysis, characterized in that: The following steps are involved: Obtain data related to urban facilities, road traffic network, and settlements in the target area; Construct motion models corresponding to multiple transportation modes, and conduct simulations based on relevant data on urban facilities, road traffic networks, and settlements to obtain corresponding multiple path sets; Filter the path set and determine the corresponding spatial Gini coefficient based on the screening results; An actual threshold value of the spatial Gini coefficient is determined, and the spatial Gini coefficients are compared based on the actual threshold value.

2. The method for evaluating the balance of urban facility distribution based on spatial Gini coefficient and accessibility analysis according to claim 1 is characterized in that: The specific process of obtaining the corresponding multiple path sets includes: Select walking, cycling, and driving as modes of transportation, and construct corresponding walking motion models, cycling motion models, and driving motion models respectively; Preprocessing the urban facility related data, road traffic network data, and settlement related data, and performing simulation operations in combination with the walking motion model, cycling motion model, and vehicle motion model; The corresponding first walking path set, first cycling path set, and first vehicle path set are determined according to the simulation results.

3. The method for evaluating the balance of urban facility distribution based on spatial Gini coefficient and accessibility analysis according to claim 2 is characterized in that: The specific process of constructing the corresponding walking motion model, cycling motion model, and vehicle motion model also includes: Obtain the actual traffic data of the current target area to modify the walking motion model, cycling motion model, and vehicle motion model; The final walking motion model, cycling motion model and vehicle motion model are obtained according to the correction results.

4. The method for evaluating the balance of urban facility distribution based on spatial Gini coefficient and accessibility analysis according to claim 2 is characterized in that: The specific process of determining the corresponding spatial Gini coefficient includes: Determine walking motion constraints, cycling motion constraints, and vehicle motion constraints respectively; Filtering the first walking path set, the first cycling path set, and the first vehicle path set according to the walking motion constraint condition, the cycling motion constraint condition, and the vehicle motion constraint condition to obtain corresponding second walking path set, second cycling path set, and second vehicle path set; The spatial Gini coefficient is calculated based on the number of paths included in the second walking path set, the second cycling path set, and the second vehicle path set, and the number of paths included in the first walking path set, the first cycling path set, and the first vehicle path set.

5. The method for evaluating the balance of urban facility distribution based on spatial Gini coefficient and accessibility analysis according to claim 4 is characterized in that: The specific calculation process of the spatial Gini coefficient also includes: Obtain the historical number of walking paths, cycling paths, and vehicle paths in the target area, and calculate the corresponding mean number of walking paths, cycling paths, and vehicle paths; The corresponding cycling Gini coefficient, cycling Gini coefficient, and vehicle Gini coefficient are calculated by combining the mean number of walking paths, the mean number of cycling paths, the mean number of vehicle paths, the number of paths included in the first walking path set, the first cycling path set, the first vehicle path set, the second walking path set, the second cycling path set, and the second vehicle path set.

6. The method for evaluating the balance of urban facility distribution based on spatial Gini coefficient and accessibility analysis according to claim 4 is characterized in that: The specific process of determining the actual threshold value of the spatial Gini coefficient includes: Construct a threshold decision model; The urban facility-related data, road traffic network data, settlement-related data, the second walking path set, the second cycling path set, the second vehicle path set, the walking movement constraints, the cycling movement constraints, and the vehicle movement constraints are respectively input into the threshold decision model for processing to obtain the corresponding actual walking Gini coefficient threshold, the actual cycling Gini coefficient threshold, and the actual vehicle Gini coefficient threshold.

7. A system using the method for evaluating the balance of urban facility distribution based on spatial Gini coefficient and accessibility analysis according to any one of claims 1 to 6, characterized in that: include: An acquisition module is used to obtain data related to urban facilities, road traffic network data, and settlements in the target area; The simulation module is used to build motion models corresponding to multiple transportation modes, and to perform simulations based on data related to urban facilities, road traffic networks, and settlements to obtain corresponding sets of paths. The screening module is used to screen the path set and determine the corresponding spatial Gini coefficient based on the screening results; The comparison module is used to determine an actual threshold value of the spatial Gini coefficient and compare the spatial Gini coefficient in combination with the actual threshold value.

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