An urban green space service online evaluation method based on multi-source data

Abstract

The present application relates to a kind of urban green space service online evaluation method based on multi-source data, comprising: S1: population environment original data is collected and encapsulated as slice map service;S2: population distribution grid data is subdivided to the center point of resident building;S3: the service capacity of different types of recreational green space is extracted and analyzed based on multi-source data, cache mapping database is constructed by TaffyDB, data processing module is constructed based on WebGIS framework using Ajax technology, after data processing module is carried out data processing to the data in cache, update and issue to database server;S4: according to the data in database server, park green space management support and / or park green space recreation service.The present application provides park green space planning analysis and recreational green space recommendation service for users by classifying and analyzing the data of urban park green space, and using intuitive interactive visualization method.

Description

Technical Field

[0001] This invention relates to the field of urban green space planning and management, and in particular to an online evaluation method for urban green space services based on multi-source data. Background Technology

[0002] The scientific, intelligent, and inclusive management of various urban park and green space projects to better serve the people has become a necessity of our time. Currently, the planning and management of urban park and green space suffers from problems such as low public participation, inaccurate delineation of travel areas, and insufficient precision in spatial data processing. Furthermore, analyzing the accessibility relationships between different types of park and green space and residents presents multiple challenges, including high spatial dispersion of data, large computational resource consumption, and significant data processing difficulties. Summary of the Invention

[0003] To address the aforementioned issues, this invention proposes an online assessment method for urban green space services based on multi-source data.

[0004] The specific plan is as follows:

[0005] An online assessment method for urban green space services based on multi-source data includes the following steps:

[0006] S1: Collect raw population and environmental data, store the data and data sources in the database, and encapsulate and publish them to form a standardized WMS or WMTS tile map service;

[0007] S2: Extract building outline data from multiple map base maps, determine the topological relationship of building outline data in different map base maps, realize the deduplication of buildings and the extraction of residential buildings; and subdivide the population distribution data to the center point of each building based on the spatial overlay relationship between the population distribution grid and the buildings.

[0008] S3: Based on multi-source data extraction and analysis of the service capabilities of different types of recreational green spaces, a cache mapping database is constructed using TaffyDB. A data processing module is built using Ajax technology within a WebGIS framework. This module processes the cached data and then updates and publishes it to the database server. The data processing module's process includes the following steps:

[0009] S301: Extract park and green space data from multiple base maps, and merge land use data and land cover data from the park and green space data to obtain green space cover data; after performing buffer analysis on road network data and slope analysis on DEM data, remove data belonging to road network buffer and DEM slope from the green space cover data; classify the green space cover data.

[0010] S302: Based on the level of the road network surrounding the recreational green space data, divide the green space coverage data of different types into isochronous zones;

[0011] S303: Perform spatial overlap analysis between the isochronous circles of recreational green space data and the population distribution data on buildings. When the two overlap, the population distribution data of the overlapping part is added to the park green space service capacity attribute of the green space coverage data, and the green space corresponding to the green space coverage data of the overlapping part is added to the park green space availability attribute of the building.

[0012] S4: Provide support for park and green space management and / or park and green space recreation services based on data from the database server.

[0013] Furthermore, the raw population and environmental data include: land cover data, land use data, urban park data, national park data, mobile phone signaling sampled population data, WordPop population distribution data, and various map base map data.

[0014] Furthermore, the database is built on the open-source GIS data server GeoServer.

[0015] Furthermore, step S301 also includes taking the center point as a population distribution supplement point for population distribution data of missing residential locations.

[0016] Furthermore, the types of recreational green space data include: township-scale park green space, district / county-scale park green space, and city-scale park green space.

[0017] Furthermore, in step S302, the isochronous zones for different types of recreational green space data include: for township-scale parks and green spaces, the isochronous zone is 15 minutes by walking or 15 minutes by cycling; for district / county-scale parks and green spaces, the isochronous zone is 30 minutes by walking or 30 minutes by cycling; and for city-scale parks and green spaces, the isochronous zone is 60 minutes by car.

[0018] Furthermore, the process of supporting park and green space management based on data from the database server includes the following steps:

[0019] S401: Calculate the service capacity of park green space per unit area;

[0020] S402: Heat map drawing based on per capita green space usable area data from Kriging.js, using a layered coloring method to color the data, and delineating green-deficient spaces according to the percentage difference between per capita green space usable area and rated per capita green space usable area.

[0021] S403: By importing GeoJSON data of the implementation scope of the standard greening project, the greening project area is analyzed in conjunction with the road network accessibility to obtain the specific value of the green space use area of ​​the surrounding residents and the value of alleviating the service pressure of other parks and green spaces in the surrounding area.

[0022] Furthermore, the process of providing park and green space recreation recommendation services based on data from the database server includes the following steps:

[0023] S501: Based on the map location of the user's handheld device, delineate all isochronous circles containing the map location, and obtain all parks and green spaces corresponding to the isochronous circles; exclude all parks and green spaces that do not meet the user's required area, and recommend parks and green spaces that meet the requirements to the user in combination with real-time traffic situation data and the corresponding service capabilities of the parks and green spaces.

[0024] S502: Employs WebGL-based spatial data visualization technology to create a 3D scene based on actual images of park green spaces; based on graphics theory, it adds audio, video, and 3D symbols to the scene to abstractly express the park's key features and characteristics, assisting users in making recreational choices.

[0025] This invention adopts the above technical solution, classifies and analyzes urban agglomeration park and green space data, and uses an intuitive interactive visualization method to provide users with park and green space planning analysis and recreational green space recommendations. This helps to promote the construction of ecological public service networks and also helps to promote the popularization of ecological welfare. Attached Figure Description

[0026] Figure 1 The diagram shown is a flowchart of an embodiment of the present invention.

[0027] Figure 2 The diagram shown is a schematic representation of the population distribution data refinement process in an embodiment of the present invention. Detailed Implementation

[0028] To further illustrate the various embodiments, the present invention provides accompanying drawings. These drawings are part of the disclosure of the present invention, primarily used to illustrate the embodiments, and can be used in conjunction with the relevant descriptions in the specification to explain the operating principles of the embodiments. With reference to these drawings, those skilled in the art should be able to understand other possible implementations and the advantages of the present invention.

[0029] The present invention will now be further described in conjunction with the accompanying drawings and specific embodiments.

[0030] This invention provides an online assessment method for urban green space services based on multi-source data, such as... Figure 1 As shown, the method includes the following steps:

[0031] S1: Collect raw population and environmental data, and after packaging and publishing the data and data sources into standardized WMS or WMTS tile map services, store them in a database (vector or raster map service).

[0032] In this embodiment, the database is built based on the open-source GIS data server GeoServer.

[0033] The original dataset in this embodiment includes: land cover data, land use data, urban park data, national park data, mobile signaling sampled population data, WordPop population distribution data, and various map base map data (including: OMS map base map data, Baidu map base map data, Gaode map base map data, and Tianditu map base map data).

[0034] S2: As Figure 2 As shown, building outline data is extracted from multiple map base maps. Topological relationships are determined for the building outline data in different map base maps to achieve building deduplication and extraction of residential buildings. Based on the spatial overlay relationship between the population distribution grid and buildings, the population distribution data is subdivided down to the center point of each building.

[0035] In this embodiment, the method for deduplicating buildings is as follows: if the outline data of buildings in different map base maps have an intersection and the distance between the outline data is less than a preset distance threshold, then the buildings in different map base maps are set to belong to the same building. In this case, the outline data with the larger outline data area in the same building is deleted, and only the outline data with the smaller outline data area is retained as the outline data of the building.

[0036] Furthermore, this embodiment also includes taking the center point as a population distribution supplementary point for population distribution data of missing residential locations.

[0037] S3: Based on multi-source data (i.e., park and green space data extracted from various map base maps), extract and analyze the service capabilities of different types of recreational green spaces. Construct a cache mapping database using TaffyDB, and build a data processing module based on the WebGIS framework using Ajax technology. After processing the data in the cache through the data processing module, update and publish it to the database server.

[0038] The data processing module's data processing procedure includes the following steps:

[0039] S301: Park and green space data are extracted from multiple base maps. Land use and land cover data from the park and green space data are then merged (i.e., the intersection of the two sets of data) to obtain green space cover data. After performing buffer analysis on the road network data and slope analysis on the DEM data, data belonging to road network buffers and DEM slopes are removed from the green space cover data. The green space cover data is then classified to identify green spaces with recreational value.

[0040] In this embodiment, the types of recreational green space data include: township-scale park green space, district / county-scale park green space, and city-scale park green space. The isochronous circles for different types of green space coverage data are as follows: for township-scale park green space, the isochronous circle is 15 minutes walking or 15 minutes cycling; for district / county-scale park green space, the isochronous circle is 30 minutes walking or 30 minutes cycling; and for city-scale park green space, the isochronous circle is 60 minutes driving.

[0041] S302: Based on the level of the road network surrounding the recreational green space data, divide the green space coverage data of different types into isochronous zones.

[0042] S303: Perform spatial overlap analysis between the isochronous circles of recreational green space data and the population distribution data on buildings. When the two overlap, the population distribution data of the overlapping part is added to the park green space service capacity attribute of the green space coverage data, and the green space corresponding to the green space coverage data of the overlapping part is added to the park green space availability attribute of the building.

[0043] S4: Provide support for park and green space management and / or park and green space recreation services based on data from the database server.

[0044] The park and green space management support is primarily aimed at municipal management personnel, providing planning assistance and decision support for parks and green spaces. It can analyze and calculate the service capacity of each park and green space, analyze urban green space deficiencies, and assist in the implementation of greening projects. In this embodiment, the process of providing park and green space management support based on data from the database server includes the following steps:

[0045] S401: Calculate the service capacity of park green space per unit area.

[0046] S402: Heatmaps are drawn based on per capita available green space data from Kriging.js. A layered coloring method is used to color the data, and green-deficient spaces are defined according to the percentage difference between the per capita available green space data and the rated per capita available green space data.

[0047] S403: By importing GeoJSON data of the implementation scope of the standard greening project, the greening project area is analyzed in conjunction with the road network accessibility to obtain the specific value of the green space use area of ​​the surrounding residents and the value of alleviating the service pressure of other parks and green spaces in the surrounding area.

[0048] The park and green space recreation service is primarily aimed at the general public, providing recommendations for recreational spaces in parks and green areas to help people choose suitable green recreation venues. In this embodiment, the process of providing park and green space recreation services based on data from the database server includes the following steps:

[0049] S501: Based on the user's handheld device's map location, delineate all isochronous zones containing that map location, and obtain all parks and green spaces corresponding to those isochronous zones. Exclude parks and green spaces that do not meet the user's area requirements, and, combining real-time traffic data and the corresponding service capabilities of each park and green space, recommend suitable parks and green spaces to the user.

[0050] S502: Employs WebGL-based spatial data visualization technology to create a 3D scene based on actual images of park green spaces. Based on graphics theory, audio, video, and 3D symbols are added to the scene to abstractly express the park's key features and characteristics, assisting users in making recreational choices.

[0051] This invention provides users with park and green space planning analysis and recreational green space recommendations by classifying and analyzing urban agglomeration park and green space data and using an intuitive interactive visualization method. This helps to promote the construction of an ecological public service network and also helps to promote the popularization of ecological welfare.

[0052] Although the invention has been specifically shown and described in conjunction with preferred embodiments, those skilled in the art should understand that various changes in form and detail may be made to the invention without departing from the spirit and scope of the invention as defined in the appended claims, all of which shall be within the scope of protection of the invention.

Claims

1. A method for online evaluation of urban green space services based on multi-source data, characterized in that, Includes the following steps: S1: Collect raw population and environmental data, store the data and data sources in the database, and encapsulate and publish them to form a standardized WMS or WMTS tile map service; S2: Extract building outline data from multiple map base maps, determine the topological relationship of building outline data in different map base maps, realize the deduplication of buildings and the extraction of residential buildings; and subdivide the population distribution data to the center point of each building based on the spatial overlay relationship between the population distribution grid and the buildings. S3: Based on multi-source data extraction and analysis of the service capabilities of different types of recreational green spaces, a cache mapping database is constructed using TaffyDB. A data processing module is built using Ajax technology within a WebGIS framework. This module processes the cached data and then updates and publishes it to the database server. The data processing module's process includes the following steps: S301: Extract park and green space data from multiple base maps, and merge land use data and land cover data from the park and green space data to obtain green space cover data; after performing buffer analysis on road network data and slope analysis on DEM data, remove data belonging to road network buffer and DEM slope from the green space cover data; classify the green space cover data. S302: Based on the level of the road network surrounding the recreational green space data, divide the green space coverage data of different types into isochronous zones; S303: Perform spatial overlap analysis between the isochronous circles of recreational green space data and the population distribution data on buildings. When the two overlap, the population distribution data of the overlapping part is added to the park green space service capacity attribute of the green space coverage data, and the green space corresponding to the green space coverage data of the overlapping part is added to the park green space availability attribute of the building. S4: Provide park and green space management support and / or park and green space recreation services based on data in the database server; The process of supporting park and green space management based on data from the database server includes the following steps: S401: Calculate the service capacity of park green space per unit area; S402: Heat map drawing based on per capita green space usable area data from Kriging.js, using a layered coloring method to color the data, and delineating green-deficient spaces according to the percentage difference between per capita green space usable area and rated per capita green space usable area. S403: By importing GeoJSON data of the implementation scope of the standard greening project, the greening project area is analyzed in conjunction with the road network accessibility to obtain the specific value of the green space use area of ​​the surrounding residents and the value of alleviating the service pressure of other parks and green spaces in the surrounding area.

2. The online assessment method for urban green space services based on multi-source data according to claim 1, characterized in that: The raw population and environmental data include: land cover data, land use data, urban park data, national park data, mobile phone signaling sampled population data, WordPop population distribution data, and various map base map data.

3. The online assessment method for urban green space services based on multi-source data according to claim 1, characterized in that: The database is built on the open-source GIS data server GeoServer.

4. The online assessment method for urban green space services based on multi-source data according to claim 1, characterized in that: Step S301 also includes taking the center point as a population distribution supplement point for population distribution data of missing residential locations.

5. The online assessment method for urban green space services based on multi-source data according to claim 1, characterized in that: The types of recreational green space data include: township-scale park green space, district / county-scale park green space, and city-scale park green space.

6. The online evaluation method for urban green space services based on multi-source data according to claim 5, characterized in that: The isochronous zones for different types of recreational green space data in step S302 include: for township-scale parks and green spaces, the isochronous zone is 15 minutes by walking or cycling; for district / county-scale parks and green spaces, the isochronous zone is 30 minutes by walking or cycling; and for city-scale parks and green spaces, the isochronous zone is 60 minutes by car.

7. The online assessment method for urban green space services based on multi-source data according to claim 1, characterized in that: The process of providing park and green space recreation recommendation services based on data from the database server includes the following steps: S501: Based on the map location of the user's handheld device, delineate all isochronous circles containing the map location, and obtain all parks and green spaces corresponding to the isochronous circles; exclude all parks and green spaces that do not meet the user's required area, and recommend parks and green spaces that meet the requirements to the user in combination with real-time traffic situation data and the corresponding service capabilities of the parks and green spaces. S502: Employs WebGL-based spatial data visualization technology to create a 3D scene based on actual images of park green spaces; based on graphics theory, it adds audio, video, and 3D symbols to the scene to abstractly express the park's key features and characteristics, assisting users in making recreational choices.

Images