A bus stop coverage evaluation method based on walking distance

Abstract

The application discloses a bus station coverage evaluation method based on walking distance, and relates to the technical field of transportation planning and management. The method comprises the following steps: acquiring basic data related to bus station coverage evaluation; unifying the acquired data to a projection coordinate system, and implementing vector topological processing on the processed data after unifying the coordinates; constructing a bus station service range with a specified walking distance; cross-matching the bus station walking coverage range with the present construction land classified according to land use properties, screening out covered building lands, defining part of the covered land blocks as the first type of covered land, loading population and post grid data, calculating the total population of the first type of covered land and the corresponding construction land, and performing comparison and analysis, when the population proportion of the first type of covered land exceeds a set threshold, the land block is determined to be completely covered by the bus station, and the final covered building land data is updated, and the bus station coverage evaluation is realized.

Description

Technical Field

[0001] This invention relates to the field of transportation planning and management technology, specifically a method for assessing bus stop coverage based on walking distance. Background Technology

[0002] As urban transportation planning increasingly demands precision and scientific rigor, bus stop coverage assessment is playing an increasingly important role in the development of urban public transportation. As a key indicator for measuring the quality of public transportation services, the accuracy and comprehensiveness of bus stop coverage assessment directly affect the optimization decisions of the urban public transportation network and the convenience of residents' travel.

[0003] However, traditional methods for assessing bus stop coverage often face the following problems when considering passengers' actual travel experience and comprehensively analyzing the impact of multiple factors: First, the assessment of walking distance is inaccurate. Traditional assessments often use a 500-meter radius to simply define the service area of ​​a bus stop. This method does not fully consider the limitations of actual walking paths. Although some starting points are within 500 meters of the bus stop in a straight line, the actual walking distance may exceed 1 kilometer, which can cause significant errors in identifying potential passengers within the bus stop coverage area. Second, the assessment process lacks comprehensive consideration of multiple factors. Existing technologies do not fully consider important factors affecting passenger flow, such as land use and population density within the coverage area, when assessing bus stop coverage. In addition, existing bus stop coverage assessment systems lack the ability to dynamically adjust and conduct refined analysis. Traditional assessment methods cannot adjust the assessment model and parameters in a timely manner according to these dynamic changes, making it impossible to achieve dynamic tracking and accurate assessment of bus stop coverage. Summary of the Invention

[0004] The purpose of this invention is to provide a method for assessing the coverage of public transport stops based on walking distance, in order to solve the problems raised in the prior art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for assessing bus stop coverage based on walking distance, the method comprising the following steps: Acquire bus stop data, vector road network data, existing construction land data, and integrate population and job grid distribution data; The acquired data is unified into a projected coordinate system, and after the coordinates are unified, the processed data is subjected to vector topology processing using a GIS platform. Establish service areas for bus stops within a specified walking distance; The system cross-matches the pedestrian coverage area of ​​bus stops with the existing construction land classified by land use, filters out the covered building land, and defines the partially covered plots as the first type of covered land. Population and job grid data are loaded, the total population of the first type of covered land and the corresponding construction land is calculated and compared. When the proportion of the population of the first type of covered land exceeds a set threshold, the plot is considered to be completely covered by the bus stop, and the final covered building land data is updated.

[0006] Obtain basic data related to the assessment of public transport stop coverage, specifically including: Using geographic surveying tools and technologies, the latitude and longitude information of each bus stop is recorded, as well as the route and stop order of each bus line. The data is then spatialized, and with the help of Geographic Information System (GIS) technology, the bus stop and route information is transformed into a visualized spatial data layer. Acquire vector road networks with data refined to the standard of community roads; Differentiate existing construction land parcels according to their land use nature; Obtain population and job grid distribution data layers.

[0007] The specific methods for obtaining vector road network and integrating population and job grid distribution data are as follows: Through on-site surveys of all bus stops in the city, the latitude and longitude of the physical bus stops and bus routes, as well as the current construction land, were recorded; Use the domestic road vector network provided by NavInfo or OpenStreetMap to obtain a vector network with details down to the standard of community roads; Population and job grid distribution data provided by Baidu Insight were used.

[0008] The obtained bus stop, vector road network, existing construction land, and integrated population and job grid distribution data are converted to a unified projected coordinate system. After the coordinates are unified, the processed data is subjected to vector topology processing on the GIS platform.

[0009] The steps for constructing a service area analysis based on specified walking distances using ArcGIS 10.8 software include: Select the path in the software's directory window and create a new file geodatabase; Within the newly created database, select "Create New Feature Dataset" and configure its parameters, including setting the XY coordinate system, Z coordinate system, XY tolerance, Z tolerance, and M tolerance. The XY coordinate system setting is determined by the region where the data is located and must be a projected coordinate system. Specific values ​​or parameters should be customized based on the actual situation of the target city. Since the Z coordinate system does not involve elevation calculations, the vertical coordinate system is not selected by default. The XY tolerance setting relates to the accuracy of calculating the 500-meter coverage area of ​​bus stops; set the tolerance to less than 1 meter. Leave the Z tolerance setting at its default value (empty). Leave the M tolerance setting at its default value (empty). Select "Import Feature Class" on the feature dataset to import the detailed road network into the feature dataset. In this operation, only one feature class is imported at a time. Import the detailed road network into the feature dataset, where the output feature names are set to default and all field mappings are preserved; Load bus stops and existing construction land in the main window for later use, without importing the element dataset; Create a new network dataset on the feature dataset. Configure the parameters of this new network dataset, including setting the type, version, source, turns, connectivity, elevation model, attributes, and direction. The type setting is a network dataset based on a geodatabase; the version setting selects the default dataset version; the source setting selects adding fine-grained road network feature classes to the network dataset; during the construction of the dataset network, no corresponding turning model needs to be built for the turning parameter; the connectivity setting selects the default value; the elevation model is set to "None"; the direction setting is set to "No" because it considers 500-meter walking coverage and therefore does not require setting a driving direction for the network dataset. Based on the settings summary displayed after configuration, determine whether changes are needed. If changes are needed, return to modify again. If no changes are needed, build the network dataset and display it in the main window.

[0010] Right-click in the blank area of ​​the interface menu bar, select Network Analyst, and open the network analysis tool, which will be displayed in a floating window in front of you. By selecting "New Service Area" from the Network Analyst dropdown menu, the "Service Area" window will pop up. Select the "Load Location" option at the facility point to load the bus stop layer. The location analysis attributes and location positioning of the bus stop layer are set to default. In the service area layer properties, under the analysis settings directory, set the two parameters: default interruption and direction. Set the default interruption to 500 meters and the direction to "leave facility point". In the service area layer properties, set the impedance to length (meters). Run Network Analyst to solve the problem and obtain the area covered by the specified walking distance of the bus stop. After merging, the complete region is obtained.

[0011] The specific steps for determining the building land area covered by the prescribed walking distance to bus stops include: By cross-matching the area covered by the prescribed walking distance of bus stops obtained from the above analysis with the existing construction land plots classified by land use, all building land covered by the prescribed walking distance of bus stops is obtained.

[0012] By cross-matching the area covered by the prescribed walking distance of the bus stops obtained from the above analysis with the existing construction land plots classified by land use nature, some plots covered by the prescribed walking distance of the bus stops are selected and recorded as the first type of covered land.

[0013] The first type of covered land was verified using population and job grid distribution data layers provided by Baidu Insight. The first type of covered land was compared with the population of the area covered by the land. The specific steps included: A unique ID is assigned to the first type of covered land, and it uniquely corresponds to the ID of the same complete plot in the plots of existing construction land that are distinguished by land use nature; Load the population and job grid distribution data layer, and use spatial connection and summary statistics tools to count the number of people in the population and job grid distribution data layer contained in the first type of covered land and the plots of existing construction land distinguished by land use nature; Using the analysis tools, overlay analysis, and spatial connection in the toolbox, the population and job grid distribution data layers are spatially connected to the first type of covered land and the plots of existing construction land distinguished by land use nature, respectively. Use the analysis tools, statistical analysis, and summary statistics in the toolbox to distinguish fields by plot ID and select summation as the statistical type; The ratio of the number of people covered by the first type of land to the number of people covered by the corresponding existing construction land plots classified by land use is compared with a set threshold. If the ratio of the number of people covered by the first type of land to the number of people covered by the corresponding existing construction land plots classified by land use is greater than the set threshold, it is determined that the plot is completely covered by the bus stop, and the process is updated to obtain all building land plots covered by the specified walking distance of the bus stop.

[0014] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention performs secondary precise identification based on population and job distribution, and filters out plots not covered by bus stops within 500 meters of different land use types such as residential plots, industrial plots, administrative office plots, and educational plots. Unlike existing technologies that lack in-depth analysis of different land use types, this invention analyzes areas with insufficient bus stop coverage based on the characteristics of different land use types, and can provide better optimization scheme indicators for uncovered areas of different land use types, and provide a reasonable basis for setting optimization measures for bus stop relocation. 2. By combining four types of refined data—bus stop vector data, vector map data detailed down to the internal roads of residential communities, the latest construction land data, and population and job grid data—this invention enables the assessment of bus stop coverage areas. Unlike traditional assessment methods that rely solely on simple distances or single data types, this invention utilizes the fusion of multi-source data, considering various factors affecting bus stop coverage. In the initial identification of bus stop coverage areas within a 500-meter walking distance, the refined vector map data ensures a simulation of actual walking paths, avoiding coverage deviations caused by neglecting actual road conditions. The latest construction land data clarifies the boundaries and nature of urban construction areas, providing a foundation for subsequent analysis based on land use types and offering reliable data support for public transportation planning. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of the structure of a public transport stop coverage assessment method based on walking distance according to the present invention. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] In the embodiment: such as Figure 1 As shown, the present invention provides a technical solution, a method for assessing bus stop coverage based on walking distance, the method comprising the following steps: Acquire bus stop data, vector road network data, existing construction land data, and integrate population and job grid distribution data; The acquired data is unified into a projected coordinate system, and after the coordinates are unified, the processed data is subjected to vector topology processing using a GIS platform. Establish service areas for bus stops within a specified walking distance; The system cross-matches the pedestrian coverage area of ​​bus stops with the existing construction land classified by land use, filters out the covered building land, and defines the partially covered plots as the first type of covered land. Population and job grid data are loaded, the total population of the first type of covered land and the corresponding construction land is calculated and compared. When the proportion of the population of the first type of covered land exceeds a set threshold, the plot is considered to be completely covered by the bus stop, and the final covered building land data is updated.

[0018] Obtain basic data related to the assessment of public transport stop coverage, specifically including: Using geographic surveying tools and technologies, the latitude and longitude information of each bus stop is recorded, as well as the route and stop order of each bus line. The data is then spatialized, and with the help of Geographic Information System (GIS) technology, the bus stop and route information is transformed into a visualized spatial data layer. Acquire vector road networks with data refined to the standard of community roads; Differentiate existing construction land parcels according to their land use nature; Obtain population and job grid distribution data layers.

[0019] Specifically, bus stops are identified through on-site surveys of all bus stops within the city. The latitude and longitude of each physical bus stop and the corresponding bus routes are recorded, and these are spatially designated as "stops." The latitude and longitude of the physical bus stops and bus routes are recorded according to the following format. For example, in a GIS (Geographic Information System) identification window interface, information about physical bus stops is displayed. Currently, "<Top Layer>" is selected, indicating that the identification operation is performed on the top layer. The displayed information is for "Jianzheng Road (Bus Stop)," with location coordinates of 42.444, 143.075, 4,860, 849.786 meters. The attribute fields and values ​​in the window interface are as follows: FID: value 2648, which is the unique identifier of this feature in the database; Shape: value is a point, indicating that the bus stop is a point feature on the map. The following information is provided: OBJECTID: value 2649, which is also the unique identifier of this bus stop in the element class; name: name is "Jianzheng Road (Bus Stop)"; category: belongs to "Transportation Facilities Services: Bus Stops: Bus Stop Related"; code: code is 150701; address: address is "Jianzheng Road / Z261 / Z255"; GD_X: value is 125.311249, which is latitude and longitude related information (projected coordinates); GD_Y: value is 33.64798, which is latitude and longitude related information (projected coordinates); region: the region is "Chaoyang District"; WGS84_Lng: longitude in the WGS84 coordinate system is 125.304765; WGS84_Lat: latitude in the WGS84 coordinate system is 43.882407. Use the NavInfo vector road network or download the latest domestic road vector road network provided by the OpenStreetMap official website. The road details need to be refined to the standard of community roads, and set it as roadline. Existing construction land is categorized into different plots based on land use, and these are set as blocks. The following format is used to differentiate plots based on land use: For example, in a GIS (Geographic Information System) identification window, relevant information about existing construction land is displayed. The currently selected layer is "<Top Layer>", meaning the identification operation is performed on the topmost layer. The identified layer is "Existing Construction Land 2022," and the location information shows the coordinates of this construction land as -575.308, 1,570.192 meters. The attribute fields and values ​​in the window are as follows: FID: value 9701, which is the unique identifier of this feature in the database; Shape: value "ZM," indicating that the construction land... The land is represented as a polygon feature on the map; OBJECTID: value 0, which is also an identifier for this feature in the feature class; Shape_Leng: value 922.743953, representing the boundary length of this polygonal construction land; YDDM_1: value "R2", which is the land use code; New Changes: no content displayed, indicating that there were no new change records for this land during the relevant monitoring period; YDM: value "Urban Residential Land", which clarifies the land use nature of this plot; BZ: no content displayed; Shape_Le_1: value 922.744215, related to the boundary length; Shape_Area: value 33544.010484, representing the area of ​​this polygonal construction land; Using 50m×50m population and job grid distribution data provided by Baidu Insight, designated as "home_work", the population and job grid distribution data were collected according to the following format. For example, in a GIS identification window interface, the information of geographic elements related to "workplace distribution" is displayed: Identification range: Currently selected is "<top layer>", meaning the identification operation is performed on the top layer, and the identified layer is "workplace distribution"; Location information: The location coordinates of this element are displayed as 42,444,113.898, 4,859,043.261 meters; Attribute fields and values: OBJECTID: Value is 97179, which is the unique identifier of this element in the element class; Shape: Value is 97179; Sequence number: Value is 97179; City: Value is "Changchun City", indicating that the work... Location information: City; Subway line: value is "Metro Line 1", indicating that this job distribution is related to Metro Line 1; Residential grid center latitude and longitude are given as (125.36206, 43.849533) and (125.304698, 43.86458); Route planning starting station: value is "Gongnong Square Station", which is the starting station of the route planning; Route planning terminal station entrance: value is "(Exit B)", indicating the entrance of the terminal station; Route planning starting station entrance to the line: value is "Metro Line 1", indicating the line to which the entrance belongs; Route planning terminal station: value is "Northeast Normal University Station", which is the terminal station of the route planning; Route planning terminal station exit: value is "(Exit B)", indicating the exit of the terminal station; Number of people: value is 1, indicating the number of people related to this job distribution.

[0020] The specific methods for obtaining vector road network and integrating population and job grid distribution data are as follows: Through on-site surveys of all bus stops in the city, the latitude and longitude of the physical bus stops and bus routes, as well as the current construction land, were recorded; Use the domestic road vector network provided by NavInfo or OpenStreetMap to obtain a vector network with details down to the standard of community roads; Population and job grid distribution data provided by Baidu Insight were used.

[0021] The obtained bus stop, vector road network, existing construction land, and integrated population and job grid distribution data are converted to a unified projected coordinate system. After the coordinates are unified, the processed data is subjected to vector topology processing on the GIS platform.

[0022] The steps for constructing a service area analysis based on specified walking distances using ArcGIS 10.8 software include: Select the path in the software's directory window and create a new file geodatabase; Within the newly created database, select "Create New Feature Dataset" and configure its parameters, including setting the XY coordinate system, Z coordinate system, XY tolerance, Z tolerance, and M tolerance. The XY coordinate system setting is determined by the region where the data is located and must be a projected coordinate system. Specific values ​​or parameters should be customized based on the actual situation of the target city. Since the Z coordinate system does not involve elevation calculations, the vertical coordinate system is not selected by default. The XY tolerance setting relates to the accuracy of calculating the 500-meter coverage area of ​​bus stops; set the tolerance to less than 1 meter. Leave the Z tolerance setting at its default value (empty). Leave the M tolerance setting at its default value (empty). Specifically, in the directory window, select any file path and create a new file geodatabase GDB_1. Subsequent data and analysis will be performed within this database. Within GDB_1, select "Create New Dataset," and name the generated feature dataset DSet_1. Then configure the parameters of DSet_1, namely setting the XY coordinate system, Z coordinate system, XY tolerance, Z tolerance, and M tolerance. Specifically, in the "Attribute Domain, Resolution, and Tolerance" tab of the feature dataset attribute settings window in the Geographic Information System (GIS), the meanings of each part are as follows: The attribute domain is used to define the spatial range of values ​​for feature data: X-coordinate range: The minimum value of X is 36,876,800, and the maximum value of X is 900,756,802,274.099, representing the spatial range of the data in the horizontal direction; Y coordinate range: The minimum value of Y is -10002100, and the maximum value of Y is 900709923374.099, representing the spatial range of the data in the vertical direction; Z-coordinate range: The minimum value of Z is -100000, and the maximum value of Z is 900719825474.099. It is used when dealing with three-dimensional information such as elevation, and defines the range of values ​​in the Z direction. M coordinate range: The minimum value of M is -100000, and the maximum value of M is 900719825474.099. The M value is often used to store measurement values ​​related to geometric features (distance values ​​in a linear reference system). Here, its value range is defined. Resolution describes the precision of data across different dimensions: XY resolution: The value is 0.0001 Meter, which means that the smallest distance that the data can distinguish in the plane (XY direction) is 0.0001 meters, that is, the accuracy can reach 0.1 millimeters; Z-resolution: The value is 0.0001. With elevation information available, this means that the smallest distance that can be distinguished in the Z direction is 0.0001. M resolution: A value of 0.0001 indicates that the smallest interval that the M value can distinguish is 0.0001; Tolerance is used to set the allowable error range during data processing: XY tolerance: The value is 0.001 Meter. When performing spatial data processing, such as topology checking and feature snapping, features that are less than or equal to 0.001 meters apart on the XY plane will be considered to conform to certain spatial relationships. Z-tolerance: The value is 0.001. When performing related spatial operations in the Z direction, features with a distance difference within 0.001 (estimated to be in meters) will meet the corresponding conditions. M tolerance: The value is 0.001. When processing operations related to the M value, the allowable difference range is 0.001. Select "Import Feature Class" on the feature dataset to import the detailed road network into the feature dataset. In this operation, only one feature class is imported at a time. Import the detailed road network into the feature dataset, where the output feature names are set to default and all field mappings are preserved; Load bus stops and existing construction land in the main window for later use, without importing the element dataset; Create a new network dataset on the feature dataset. Configure the parameters of this new network dataset, including setting the type, version, source, turns, connectivity, elevation model, attributes, and direction. The type setting is a network dataset based on a geodatabase; the version setting selects the default dataset version; the source setting selects adding fine-grained road network feature classes to the network dataset; during the construction of the dataset network, no corresponding turning model needs to be built for the turning parameter; the connectivity setting selects the default value; the elevation model is set to "None"; the direction setting is set to "No" because it considers 500-meter walking coverage and therefore does not require setting a driving direction for the network dataset. Specifically, the summary information interface for creating a new network dataset in a Geographic Information System (GIS) provides detailed explanations of the key parameters and settings for the new network dataset. The following is an explanation of each part: Name: DSet_1_ND; Type: Geographic database-based network dataset, indicating that the dataset is built on a geographic database and is used to simulate and analyze network structures; Version: 10.1, indicating the software version applicable to the network dataset or its own version number.

[0023] Source-EdgeSource: Central Urban Area Road Network. This indicates that the edges (i.e., the connections in the network, such as roads and rivers) that make up the network dataset originate from the "Central Urban Area Road Network" data, defining the basic topology of the network. Connectivity - Group 1 - Edge Connectivity: Central Urban Area Road Network (Endpoints), indicating that the connectivity between edges in the network is determined based on the endpoints of the "Central Urban Area Road Network", that is, the nodes of the road network determine the connection method of the network; The elevation model value is zero, indicating that the network dataset did not consider elevation factors when it was constructed, does not involve height changes in three-dimensional space, and is mainly used for planar network analysis. Attribute - Length: Usage type: Cost means that in network analysis, "length" is used as a cost attribute, and in route planning, the length of a road segment is used as an indicator to calculate the cost of travel. Data type: Double, indicating that the data storage type of the "Length" attribute is a double-precision floating-point number; Unit type: meter, which clarifies that the unit of measurement for the "length" attribute is the meter; By default, True is used, meaning the "length" attribute will be used by default when performing network analysis. Source attribute assigner: Here, expressions written in VBScript are used for the fields "Central urban area road network (from to)" and "Central urban area road network (to to from)" to assign values ​​to the length attribute of the network edge. The specific assignment logic is determined by the corresponding VBScript expression. Default attribute assigner: The default edge and default intersection point are set to constant values ​​of 0. This may be because the relevant attributes at these positions are 0 when no explicit assignment is made.

[0024] Direction - Configured Direction: No, indicating that the current network dataset has not yet been configured with direction information, and prompts you to configure the direction. At least one edge source must have a mapped street field name; Based on the settings summary displayed after configuration, determine whether changes are needed. If changes are needed, return to modify again. If no changes are needed, build the network dataset and display it in the main window.

[0025] Right-click in the blank area of ​​the interface menu bar, select Network Analyst, and open the network analysis tool, which will be displayed in a floating window in front of you. By selecting "New Service Area" from the Network Analyst dropdown menu, the "Service Area" window will pop up. Select the "Load Location" option at the facility point to load the bus stop layer. The location analysis attributes and location positioning of the bus stop layer are set to default. In the service area layer properties, under the analysis settings directory, set the two parameters: default interruption and direction. Set the default interruption to 500 meters and the direction to "leave facility point". In the service area layer properties, set the impedance to length (meters). Run Network Analyst to solve the problem and obtain the area covered by the specified walking distance of the bus stop. After merging, the complete region is obtained.

[0026] The specific steps for determining the building land area covered by the prescribed walking distance to bus stops include: By cross-matching the area covered by the prescribed walking distance of bus stops obtained from the above analysis with the existing construction land plots classified by land use, all building land covered by the prescribed walking distance of bus stops is obtained.

[0027] By cross-matching the area covered by the prescribed walking distance of the bus stops obtained from the above analysis with the existing construction land plots classified by land use nature, some plots covered by the prescribed walking distance of the bus stops are selected and recorded as the first type of covered land.

[0028] The first type of covered land was verified using population and job grid distribution data layers provided by Baidu Insight. The first type of covered land was compared with the population of the area covered by the land. The specific steps included: A unique ID is assigned to the first type of covered land, and it uniquely corresponds to the ID of the same complete plot in the plots of existing construction land that are distinguished by land use nature; Load the population and job grid distribution data layer, and use spatial connection and summary statistics tools to count the number of people in the population and job grid distribution data layer contained in the first type of covered land and the plots of existing construction land distinguished by land use nature; Using the analysis tools, overlay analysis, and spatial connection in the toolbox, the population and job grid distribution data layers are spatially connected to the first type of covered land and the plots of existing construction land distinguished by land use nature, respectively. Specifically, the area covered by a 500-meter walk from a bus stop obtained from the analysis is set as (busbuf500). The busbuf500 and the block are cross-matched using map layers to filter out all land areas (blk_bus) covered by a 500-meter walk from a bus stop. In blk_bus, some plots are completely covered by busbuf500, while some plots are only partially included in busbuf500. Since bus stops serve passengers, not the land parcels, this invention filters out land parcels whose areas are only partially included in busbuf500, denoted as (blk_intersect). The population and job layers (home_work) of Baidu Insight are used to verify blk_intersect. If the population of the area covered by the filtered land parcel exceeds 50% of the total population of the land parcel, it is considered that most people in the land parcel can reach a regular bus stop within 500 meters on foot, and thus the land parcel is considered to be covered by regular bus stop services. Load the population and job grid distribution data layer. Using spatial connection and summary statistics tools, count the number of people in the population and job grid distribution data layer included in the first type of covered land and the plots of existing construction land distinguished by land use nature. In the recognition interface of the 50m×50m population and job grid map, the location is: the coordinates of this element are 42,444,034.221 (X-direction coordinate value) and 4,861,554.33 (Y-direction coordinate value); attribute fields and values: FID: value is 229633, which is the unique identifier number of this element in the database and is used to distinguish it from other elements; Shape: value is "point", indicating that this geographic element is presented in the geometric shape of a point on the map, such as a bus stop or a facility location; nnu: value is 44; id: value is 611603, which is also an identifier of this element; x: value is 125.303592; y: value is 43.887434; The population and job grid distribution data layer is connected to the spatial connection field of the first type of covered land use: the identification window interface in the Geographic Information System (GIS), used to present the relevant attribute information of geographic features: Recognition range: Currently selected is "<topmost layer>", which means that the recognition operation will be performed on the topmost layer; Location: The coordinates of the displayed element are 42,450,956.962 (X value in a specific projected coordinate system) and 4,860,169.268 (Y value in a specific projected coordinate system). Attribute fields and values: FID: The value is 17544, which is the unique identifier of this feature in the database and is used to distinguish it from other features; Shape: point; Join_Count: Value is 1; TARGET_FID: value is 17544; TOIN_FID: 5867; num: value is 3; id: value is 46170; x: value is 125.389766; y: value is 43.875227; Shape_Leng: Value is 5767.714259; blk_intersect: Value is 220100000000000503; The population and job grid distribution data layer is connected to the land parcel spatial connection field that distinguishes existing construction land by land use: The identification window interface in a Geographic Information System (GIS) is used to present relevant attribute information of geographic features: Recognition range: Currently selected is "<topmost layer>", which means that the recognition operation will be performed on the topmost layer; Location: The coordinates of the displayed element are 42,445,074.491 (X value in a specific projected coordinate system) and 4,861,682.998 (Y value in a specific projected coordinate system). Attribute fields and values: FID: The value is 56005, which is the unique identifier of this feature in the database and is used to distinguish it from other features; Shape: point; Join_Count: Value is 1; TARGET_FID: value is 56005; TOIN_FID: 2260; num: value is 19; id: value is 148567; x: value is 125.316946; y: value is 43.888303; Shape_Leng: Value is 5767.714259; blk_intersect: value is 220100000000002261; Use the analysis tools, statistical analysis, and summary statistics in the toolbox to distinguish fields by plot ID and select summation as the statistical type; The ratio of the number of people counted for the first type of covered land to the number of people counted for the corresponding plots of existing construction land classified by land use is compared with a set threshold. If the ratio of the number of people counted for the first type of covered land to the number of people counted for the corresponding plots of existing construction land classified by land use is greater than the set threshold, it is determined that the plot is completely covered by the bus stop, and the process is updated to obtain all building land covered by the specified walking distance of the bus stop.

[0029] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A method for assessing bus stop coverage based on walking distance, characterized in that: The method includes the following steps: Acquire bus stop data, vector road network data, existing construction land data, and integrate population and job grid distribution data; The acquired data is unified into a projected coordinate system, and after the coordinates are unified, the processed data is subjected to vector topology processing using a GIS platform. Establish service areas for bus stops within a specified walking distance; The system cross-matches the pedestrian coverage area of ​​bus stops with the existing construction land classified by land use, filters out the covered building land, and defines the partially covered plots as the first type of covered land. Population and job grid data are loaded, the total population of the first type of covered land and the corresponding construction land is calculated and compared. When the proportion of the population of the first type of covered land exceeds a set threshold, the plot is considered to be completely covered by the bus stop, and the final covered building land data is updated.

2. The method for assessing bus stop coverage based on walking distance according to claim 1, characterized in that: Obtain basic data related to the assessment of public transport stop coverage, specifically including: Using geographic surveying tools and technologies, the latitude and longitude information of each bus stop is recorded, as well as the route and stop order of each bus line. The data is then spatialized, and with the help of Geographic Information System (GIS) technology, the bus stop and route information is transformed into a visualized spatial data layer. Acquire vector road networks with data refined to the standard of community roads; Differentiate existing construction land parcels according to their land use nature; Obtain population and job grid distribution data layers.

3. The method for assessing bus stop coverage based on walking distance according to claim 2, characterized in that: The specific methods for obtaining vector road network and integrating population and job grid distribution data are as follows: Use the domestic road vector network provided by NavInfo or OpenStreetMap to obtain a vector network with details down to the standard of community roads; Population and job grid distribution data provided by Baidu Insight were used.

4. The method for assessing bus stop coverage based on walking distance according to claim 2, characterized in that: The obtained bus stop, vector road network, existing construction land, and integrated population and job grid distribution data are converted to a unified projected coordinate system. After the coordinates are unified, the processed data is subjected to vector topology processing on the GIS platform.

5. The method for assessing bus stop coverage based on walking distance according to claim 4, characterized in that: The steps for constructing a service area analysis based on specified walking distances using ArcGIS 10.8 software include: Select the path in the software's directory window and create a new file geodatabase; Within the newly created database, select to create a new feature dataset and configure the parameters of the feature dataset, including setting the XY coordinate system, Z coordinate system, XY tolerance, Z tolerance, and M tolerance; Select "Import Feature Class" on the feature dataset to import the detailed road network into the feature dataset. In this operation, only one feature class is imported at a time. Import the detailed road network into the feature dataset, where the output feature names are set to default and all field mappings are preserved; Load bus stops and existing construction land in the main window for later use, without importing the element dataset; Create a new network dataset on the feature dataset, generate the new network dataset, and configure the parameters of the new network dataset. The parameters of the new network dataset include setting type, version, source, turn, connectivity, elevation model, attributes and direction. Based on the settings summary displayed after configuration, determine whether changes are needed. If changes are needed, return to modify again. If no changes are needed, build the network dataset and display it in the main window.

6. The method for assessing bus stop coverage based on walking distance according to claim 5, characterized in that: Right-click in the blank area of ​​the interface menu bar, select Network Analyst, and open the network analysis tool, which will be displayed in a floating window in front of you. By selecting "New Service Area" from the Network Analyst dropdown menu, the "Service Area" window will pop up. Select the "Load Location" option in the facility point to load the bus stop layer. The location analysis attributes and location positioning of the bus stop layer are set to default. In the service area layer properties, under the analysis settings directory, set the two parameters: default interruption and direction; Run Network Analyst to solve the problem and obtain the area covered by the specified walking distance of the bus stop. After merging, the complete region is obtained.

7. The method for assessing bus stop coverage based on walking distance according to claim 6, characterized in that: The specific steps for determining the building land area covered by the prescribed walking distance to bus stops include: By cross-matching the area covered by the prescribed walking distance of bus stops obtained from the above analysis with the existing construction land plots classified by land use, all building land covered by the prescribed walking distance of bus stops is obtained.

8. The method for assessing bus stop coverage based on walking distance according to claim 7, characterized in that: By cross-matching the area covered by the prescribed walking distance of the bus stops obtained from the above analysis with the existing construction land plots classified by land use nature, some plots covered by the prescribed walking distance of the bus stops are selected and recorded as the first type of covered land.

9. The method for assessing bus stop coverage based on walking distance according to claim 8, characterized in that: The first type of covered land was verified using population and job grid distribution data layers provided by Baidu Insight. The first type of covered land was compared with the population of the area covered by the land. The specific steps included: A unique ID is assigned to the first type of covered land, and it uniquely corresponds to the ID of the same complete plot in the plots of existing construction land that are distinguished by land use nature; Load the population and job grid distribution data layer, and use spatial connection and summary statistics tools to count the number of people in the population and job grid distribution data layer contained in the first type of covered land and the plots of existing construction land distinguished by land use nature; Using the analysis tools, overlay analysis, and spatial connection in the toolbox, the population and job grid distribution data layers are spatially connected to the first type of covered land and the plots of existing construction land distinguished by land use nature, respectively. Use the analysis tools, statistical analysis, and summary statistics in the toolbox to distinguish fields by plot ID and select summation as the statistical type; The ratio of the number of people counted for the first type of covered land to the number of people counted for the corresponding plots of existing construction land classified by land use is compared with a set threshold. If the ratio of the number of people counted for the first type of covered land to the number of people counted for the corresponding plots of existing construction land classified by land use is greater than the set threshold, it is determined that the plot is completely covered by the bus stop, and the process is updated to obtain all building land covered by the specified walking distance of the bus stop.

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