Evaluation Method for the Built Environment around Rail Transit Stops Based on the TOD Development Model

Abstract

The present invention discloses an evaluation method for the built environment around rail transit stations based on the TOD development model. A multi-level evaluation index system is established by combining urban traffic big data and built environment evaluation theory. Using multi-source heterogeneous spatio-temporal big data and adopting a variety of computer vision and geospatial analysis methods, a comprehensive index evaluation of the built environment of rail transit stations can be quickly obtained; and the drawing of environmental maps and the visual data expression are added, and the data is entered into the GIS system for summary to form a database of the built environment characteristics around urban rail transit stations; it provides an important basis for formulating planning and management improvement strategies including main deficiencies and main improvement potential points for the score situations of each rail transit station and the branches of different levels of evaluation indicators, and provides the information and system framework required for the dynamic management and sustainable development of the communities around the stations for decision-makers.

Description

Technical Field

[0001] The present invention relates to the technical field of urban built environment evaluation, and particularly to an evaluation method for the built environment around rail transit stations based on the TOD development model.

Background Art

[0002] TOD (Transit-Oriented Development) is a non-motorized planning and design method that maximizes the use of public transportation when planning a residential or commercial area. Its development concept is centered around public transportation and comprehensively develops pedestrianized urban areas. Among them, public transportation mainly refers to rail transit such as subways and light rails, as well as bus trunk lines. Then, with the bus stop as the center and a radius of 400-800 meters (a 5-10 minute walking distance), an urban area integrating work, commerce, culture, education, medical care, residence, etc. is established to achieve an organic coordination model of compact development of each urban cluster.

[0003] Reviewing the relevant research on TOD in China, since the TOD theory was introduced into China for research in 2000, it has attracted more and more thinking in the industry and academia. Researchers have started a large number of studies on TOD, including the impact and guidance on urban space and land use planning at the macro level, and the guidance on the facility layout and space design around bus stops at the micro level, and certain results have been achieved. In recent years, there have also emerged studies on evaluating the effectiveness of TOD and practical analyses of the application of TOD in Chinese cities.

[0004] The prerequisite for the better application of the TOD model is to evaluate the built environment around TOD better. Domestic research on rail transit environmental assessment mainly focuses on the ecological environment impact during the construction process of rail transit, and there is not much research on the assessment of the built environment of rail transit stations. This may be partly because the domestic rail transit construction started relatively late, and partly because there is also a great relationship with the technical means of built environment assessment. Conducting a built environment assessment with a unified standard for a huge number of rail transit stations distributed over a vast area requires a large amount of manpower and material resources under traditional technical conditions, with high statistical difficulty and large workload. However, with the rapid development of communication technology and Internet technology, the rapid rise of the mobile Internet, and the rapid popularization of various new intelligent mobile devices, a huge amount of data has burst out. And the development of artificial intelligence technology has made it possible to interpret a huge amount of information through images.

[0005] Under this background, the research on the quality assessment of the internal and external environments of urban rail transit stations is a beneficial exploration to solve urban traffic problems.

Summary of the Invention

[0006] The main object of the present invention is to provide a method for evaluating the built environment around rail transit stations based on the TOD development model. By using geospatial analysis techniques and computer vision techniques based on deep learning, it can quickly, accurately and comprehensively realize the reasonable evaluation of the built environment of surrounding communities under the TOD development model and build relevant geographic information databases, which plays an important reference value for the subsequent urban planning, construction and management.

[0007] The present invention realizes the above object through the following technical solutions: A method for evaluating the built environment around rail transit stations based on the TOD development model, which includes the following steps:

[0008] Step 1) Construct an evaluation index system for the built environment; the evaluation index system for the built environment includes primary evaluation indexes and secondary evaluation indexes;

[0009] Step 2) Calculate the walking isochrone of each rail transit station:

[0010] 21) With the help of the data interface of Internet map service providers, calculate the walking time between any two geographical locations;

[0011] 22) Taking each rail transit station as an object, mark the geographical locations where the time to reach the same rail transit station is within the set time range to form a regional range, and draw the set-time walking isochrone of each rail transit station;

[0012] Step 3) Calculate the secondary index values of the walking isochrone corresponding to each rail transit station on each secondary evaluation index;

[0013] Step 4) Calculate the primary index values of the walking isochrone corresponding to each rail transit station on each primary evaluation index;

[0014] Step 5) Integrate all the primary index values onto the corresponding rail transit stations, and input the data into the geospatial information system for summary to form a database of the built environment characteristics around urban rail transit stations;

[0015] Step 6) Use a comprehensive graphical method to superimpose and represent the results of each sub-evaluation index, and draw a development status map of the environment around the rail transit station.

[0016] Furthermore, the primary evaluation indexes include convenience, comfort, vitality and style characteristics.

[0017] Furthermore, among the secondary evaluation indexes, the convenience includes transfer convenience, slow travel accessibility, facility diversity and land use complexity; the comfort includes openness, greening, lighting, street furniture, sense of security and beauty; the vitality includes commercial attractiveness and richness of informal business; the style characteristics include style type and style similarity.

[0018] Furthermore, the sub-item evaluation indicators of transfer convenience include the number of subway lines and exits, and the number of connecting bus lines and stations;

[0019] The sub-item evaluation indicators of slow-moving accessibility include walking coverage and cycling coverage;

[0020] The sub-item evaluation indicators of facility diversity include the number of catering, hotels, sports and fitness, and leisure and entertainment facilities;

[0021] The sub-item evaluation indicators of the land use complexity include the number of enterprises and residential areas contained in the walking time zone, and the ranking comprehensive score of supporting facilities;

[0022] The openness is the proportion of sky calculated based on the street view;

[0023] The green area is the green area ratio calculated based on the street view;

[0024] The lighting is the number of street lamps calculated based on the street scene;

[0025] The street furniture is the number of seats calculated based on the street view;

[0026] The sense of security is an environmental sense of security evaluation value obtained based on a machine learning scoring model;

[0027] The aesthetic feeling is an environmental aesthetic evaluation value obtained based on a machine learning scoring model;

[0028] The sub-item evaluation indicators of commercial attractiveness include population heat value, pedestrian distribution and circle structure, bicycle usage heat and motor vehicle usage heat;

[0029] The sub-evaluation indicators of the informal business richness include the number of small vendors;

[0030] The style type is style similarity;

[0031] The uniqueness of the style and features is a style and features characteristic index.

[0032] Furthermore, in the step 3), the secondary indicator value corresponding to each secondary evaluation indicator is the average value of each sub-item evaluation indicator under each secondary evaluation indicator.

[0033] Further, the step 4) comprises:

[0034] 41) Linearly normalizing the secondary index value of each rail transit station in step 3) to calculate the score of each secondary evaluation index;

[0035] 42) Determine the weight of the secondary evaluation index in the corresponding primary evaluation index by using the analytic hierarchy process;

[0036] 43) Calculate the weighted value of the said fraction and the corresponding said weight to obtain the first-level index value corresponding to the first-level evaluation index of each rail transit station.

[0037] Further, the set time is 5 to 15 minutes.

[0038] Compared with the prior art, the beneficial effects of the evaluation method for the built environment around rail transit stations based on the TOD development model of the present invention are as follows: A multi-level evaluation index system is established by combining urban traffic big data and the theory of built environment evaluation, using multi-source heterogeneous spatio-temporal big data, and adopting a variety of computer vision and geospatial analysis methods, so as to quickly obtain a comprehensive index evaluation of the built environment of rail transit stations; And the drawing of the environmental map and the data expression of visualization are added, and the data is entered into the GIS system for summary to form a database of the built environment characteristics around urban rail transit stations; At the same time, it provides an important basis for formulating planning management improvement strategies including main deficiencies and main potential improvement points for the score situation of each rail transit station and the branches of different levels of evaluation indexes, and provides the information and system framework required for the dynamic management and sustainable development of the communities around the stations for decision-makers.

Description of the Drawings

[0039] Figure 1 It is a schematic flow chart of the evaluation method of the embodiment of the present invention;

[0040] Figure 2 It is a schematic diagram of the hierarchical structure of the evaluation index system in the embodiment of the present invention;

[0041] Figure 3 It is a schematic diagram of the distribution of rail transit stations in the embodiment of the present invention;

[0042] Figure 4 It is a schematic diagram of the 10-minute walking isochrone in the embodiment of the present invention;

[0043] Figures 5-1 to 5-6 It is a distribution diagram of the index values of the surrounding environment of some rail transit stations in the embodiment of the present invention;

[0044] Figure 6-1 It is an analysis diagram of the development characteristics of the built environment in terms of convenience in the embodiment of the present invention;

[0045] Figure 6-2 It is an analysis diagram of the development characteristics of the built environment in terms of comfort in the embodiment of the present invention;

[0046] Figure 6-3 It is an analysis diagram of the development characteristics of the built environment in terms of vitality in the embodiment of the present invention;

[0047] Figure 6-4This is an analysis diagram of the development characteristics of the built environment in terms of the style features of the embodiments of the present invention.

Specific Embodiment

[0048] Embodiment 1:

[0049] Please refer to Figure 1 , this embodiment is an evaluation method for the built environment around rail transit stations based on the TOD development model. The evaluation of the built environment (Evaluation Of Built Environment, BEE) refers to the degree judgment of the places involved in meeting and supporting people's external or internal needs and values. It is rooted in the judgment of the environmental value by environmental users. It was formed and developed in the West in the 1960s and is currently widely used. This embodiment analyzes the environment around rail transit stations from four aspects: convenience, comfort, vitality, and style features, and specifically includes the following steps:

[0050] Step 1) Construct an evaluation index system for the built environment:

[0051] Using the analytic hierarchy process, determine the evaluation indexes for the built environment based on the TOD development model, and decompose them layer by layer to construct a multi-level and multi-element evaluation index system for the built environment; the evaluation index system for the built environment includes primary evaluation indexes and secondary evaluation indexes.

[0052] As Figure 2 shown, the primary evaluation indexes include convenience, comfort, vitality, and style features, thus further enriching the scientific nature of the evaluation indexes for the built environment;

[0053] The secondary evaluation indexes are further refinements of the primary evaluation indexes, thus making the reference value of the evaluation system higher and making the evaluation system more reasonable; among the secondary evaluation indexes, the convenience includes transfer convenience, slow travel accessibility, facility diversity, and land use complexity; the comfort includes openness, greening, lighting, street furniture, sense of security, and beauty; the vitality is decomposed into commercial attractiveness and richness of informal business operations; the style features include style types and style similarity.

[0054] Step 2) Calculate the walking isochrone of each rail transit station:

[0055] This embodiment takes each rail transit station in the rail transit station distribution map as shown in Figure 3 as the object for evaluation.

[0056] 21) With the help of the data interface of the Internet map service provider, calculate the walking time between any two geographical locations;

[0057] 22) Taking each rail transit station as an object, mark the geographical locations where the arrival times at the same rail transit station are within the set time range to form an area range, and draw the set-time walking isochrones for each rail transit station. The set time is 5 to 15 minutes, and in this embodiment, it is 10 minutes. As Figure 4 shown, Figure 4 it is the distribution map of the 10-minute walking isochrones.

[0058] Step 3) Calculate the secondary index values of the walking isochrones corresponding to each rail transit station; specifically including:

[0059] 31) The sub-evaluation indicators in the transfer convenience include the number of subway lines and exits, the number of connecting bus lines and stations;

[0060] 32) The sub-evaluation indicators in the slow travel accessibility include the walking coverage range and the cycling coverage range;

[0061] 33) The sub-evaluation indicators in the facility diversity include the number of catering, hotel, sports and fitness, and leisure and entertainment facilities;

[0062] 34) The sub-evaluation indicators in the land use complexity include the convenience of work commuting and the degree of land use function complexity. Among them, the convenience of work commuting includes the number of enterprises and residential areas within the walking isochrone, and the degree of land use function complexity is the comprehensive ranking measurement of each facility;

[0063] 35) The openness is the sky proportion calculated based on street view, and its calculation method can refer to the literature Fan Zhang, Representing place locales using scene elements, Computers, Environment and Urban Systems 71(2018)153 - 164;

[0064] 36) The greening is the greening proportion calculated based on street view, and its calculation method can refer to the literature Fan Zhang, Representing place locales using scene elements, Computers, Environment and Urban Systems 71(2018)153 - 164;

[0065] 37) The lighting is the number of street lamps calculated based on street view, and its calculation method can be found in the reference Fan Zhang, Discovering place-informative scenes and objects using social media photos, Royal Society Open Science 6:181375;

[0066] 38) The street furniture is the number of seats calculated based on street view, and its calculation method can be found in the reference Fan Zhang, Discovering place-informative scenes and objects using social media photos, Royal Society Open Science 6:181375;

[0067] 39) The sense of security is the evaluation value of environmental sense of security obtained based on a machine learning scoring model; its calculation method can be found in the reference Fan Zhang, Measuring human perceptions of a large-scale urban region using machine learning, Landscape and Urban Planning 180(2018)148-160;

[0068] 310) The aesthetic feeling is the evaluation value of environmental aesthetic feeling obtained based on a machine learning scoring model; its calculation method can be found in the reference Fan Zhang, Measuring human perceptions of a large-scale urban region using machine learning, Landscape and Urban Planning 180(2018)148-160;

[0069] 311) The sub-evaluation indicators in the commercial attractiveness include population heat value, pedestrian distribution and circle structure, bicycle usage popularity, and motor vehicle usage popularity, and the data can be sourced from mobile phone signaling data provided by Tencent, Baidu, or communication companies;

[0070] 312) The sub-evaluation indicators in the richness of informal business operations include the number of street vendors;

[0071] 313) The style type is style similarity;

[0072] 314) The style uniqueness is the style feature index.

[0073] The value of each secondary indicator is the average of the sub - evaluation indicator data under each secondary indicator.

[0074] Rail transit is one of the main choices for the public to travel. The convenience of living and working around rail transit stations is an important indicator for evaluating the environment of rail transit stations.

[0075] The transfer convenience is comprehensively analyzed from multiple dimensions such as the accessibility of public transportation and walking around the station, and the richness and complexity of various urban functions around the station. The rail transit accessibility is a characterization evaluation of the traffic energy level for transferring and getting out of the station at this station, which is measured by the number of exits and the number of rail transit transfer lines of rail transit stations within the Fifth Ring Road of Beijing.

[0076] The accessbility of feeder services is a quantitative evaluation of the reach and energy level of feeder buses within the core area of rail transit stations, which is measured by the number of feeder bus stops and the total number of bus lines within the core area of rail transit stations within the Fifth Ring Road of Beijing.

[0077] The slow - travel accessibility is analyzed by dividing it into walking and cycling accessibility. The walking accessibility is a characterization evaluation of the reachable range of walking around this station. By calculating the walking time from rail transit stations within the Fifth Ring Road of Beijing to the surrounding areas, the 5 - minute and 10 - minute isochrones of each station are calculated, and their areas are compared to quantify the accessibility of rail transit. The cycling accessibility is a characterization evaluation of the reachable range of cycling around this station. By calculating the 5 - minute cycling range of each station from rail transit stations within the Fifth Ring Road of Beijing to the surrounding areas, and comparing their areas to quantify the accessibility of rail transit.

[0078] The facility diversity of the surrounding built environment has a significant impact on the convenience of this rail transit station. By retrieving the number of catering, hotel, sports and fitness, and leisure and entertainment facilities within the surrounding walking range, a comprehensive evaluation of the surrounding facility diversity is realized.

[0079] The land - use complexity is measured by the convenience of work commuting and the degree of urban - function complexity. That is, on the one hand, the convenience of work commuting is measured by the number of residential and office POI data points within the research scope around rail transit stations, and on the other hand, the degree of urban - function complexity of the surrounding built environment of this station is evaluated by comprehensively calculating the ranking scores according to the rankings of each station in different categories of POI distributions.

[0080] The comfort level of the environment around rail transit is an important condition for the public to choose public transportation. Evaluating the spatial quality of the rail transit station environment and understanding the public's perception of the station environment are effective ways to understand the comfort of the station environment. In this embodiment, the street comfort experience is comprehensively evaluated from indicators such as sky openness, greening richness, lighting conditions, street furniture, street sense of security, and street beauty.

[0081] The sky visual coverage rate refers to the proportion of the sky area relative to the entire field of view at a certain location, which is used to describe the visible degree of the sky at that location. In this embodiment, a machine learning sky image recognition model is adopted, which can automatically segment the sky part in the panoramic field of view and calculate the area proportion.

[0082] The greening visual coverage rate, namely the green view rate, was first proposed by Yoji Aoki in Japan. It refers to the proportion of greening in the field of view based on the human perspective, which is used to describe the coverage degree of the greening at that location in the vision. In this embodiment, a deep learning semantic segmentation algorithm is adopted to calculate the green view index in the visual environment.

[0083] When coming out of the rail transit station at night, the sections lacking street lights will have a great impact on the travel safety of pedestrians. Therefore, the number and brightness of street lights also largely affect the safety of the rail transit station. In this embodiment, a street light recognition model is established through feature learning of a large amount of street light image data, and the distribution of the number of street lights within the core area of the rail transit station is identified and counted by using urban street view image data and the UGC data of the public.

[0084] The distribution of seats around the rail transit station is of great significance to the walking comfort of pedestrians in the area. In this embodiment, a deep learning algorithm is used to identify the number of street seats and evaluate the walking comfort of pedestrians.

[0085] The measurement of street sense of security and beauty adopts a deep learning algorithm, which is developed by using the public calibration data from MIT's million-level and the massive calibration data of experts and the public collected locally. The public calibration truly reflects the public perception and preference. When the data sample is large enough, it can reduce the influence of the calibration individual preference on the overall model and more truly reflect the overall situation of the public group perception.

[0086] The agglomeration of urban functions near the rail transit station is an important way of urban development and construction. However, whether the agglomerated functions bring agglomerated popularity is also an important aspect of evaluating the quality of the built environment around the station. In this embodiment, its vitality degree is comprehensively analyzed from dimensions such as commercial attractiveness and informal business.

[0087] The commercial attractiveness of each station is obtained by evaluating the popularity around the station. The main indicators include the 24-hour passenger flow counted by mobile phone signaling, the pedestrian distribution obtained by street view recognition, the popularity of bicycle use, and the popularity of motor vehicle use, etc.

[0088] Specifically, the total number of people flowing in the urban space around the subway station in a day can be obtained by counting the mobile phone signaling data. The mobile phone signaling data can save the location information of mobile phone users at different times. In this embodiment, the cumulative value of the number of people in the research scope of each station for 24 hours on November 8, 2017 is counted.

[0089] Meanwhile, pedestrians are the main users of urban rail transit. Identifying the number and distribution of pedestrians within the core area of rail transit stations is of great significance for analyzing the load demand and operation efficiency of the stations. In this embodiment, the number of pedestrians within the core area of all rail transit stations is identified and counted.

[0090] In addition, the transportation connections of rail transit stations mainly rely on slow transportation modes such as walking and cycling. In recent years, with the rise of shared bicycles, the combination of "rail transit + bicycle" for urban travel has gradually become the mainstream. Identifying the number of bicycles outside rail transit stations is of great significance for evaluating the transportation connection capacity of each station. In this embodiment, the number of bicycles within the core area of all rail transit stations is identified and counted.

[0091] Finally, the distribution of motor vehicle density can reflect the attractiveness of the area around rail transit stations and the degree of urban development and prosperity. On the other hand, it can also reflect the size of the potential user group of rail transit. And the motor vehicle density also affects people's perception of the beauty and safety of urban space to a certain extent. In this embodiment, the number of motor vehicles within the core area of all rail transit stations is identified and counted.

[0092] While street vendors in the city provide convenience for public life, the chaotic management and dirty and messy environment also have a negative impact on urban space. The core area of rail transit stations is the area with the most frequent pedestrian activities in the city and is often the area where street vendors are most concentrated. Identifying the number and distribution of street vendors is of great significance. In this embodiment, a street vendor image recognition model is constructed by extracting features based on deep learning from a large amount of image data of street vendors, which can accurately identify the number and distribution of street vendors in urban street images.

[0093] The urban landscape around the exits of rail transit is often the "first impression" of Beijing for foreign tourists. The landscape characteristics around rail transit stations also affect the public's perception and impression of Beijing's landscape. A characteristic urban landscape helps to create the "gateway space" of the city.

[0094] In this embodiment, after collecting about 2 million street view pictures within the research scope around each rail transit station in Beijing, convolutional neural networks are used to extract the features of the street views. Taking each station as the research unit, the visual similarity of the surrounding urban space is analyzed to evaluate the landscape characteristics of the surrounding environment of each station, and to find the urban spaces with relatively large landscape differences and relatively large similarities around the stations.

[0095] In this embodiment, the similarity relationships are summarized and statistically analyzed to calculate the total similarity index for each site. The reciprocal of this index is taken as the index for measuring the feature style. Through the clustering algorithm, the computer statistically analyzes the street view image features of each site and the similarity relationships of all sites to cluster the site features. The results can be divided into 6 categories of feature styles, and the main features of each category include: the feature style dominated by high-rise buildings, the urban suburban feature style with wide roads and low development intensity, the urban park feature style with good greening and few buildings, the feature style dominated by science and technology parks, the feature style dominated by historical and cultural buildings and blocks, and the feature style dominated by modern commercial office buildings.

[0096] Step 4) Calculate the first-level index values of the walking isochrone corresponding to each rail transit station:

[0097] 41) Linearly normalize the second-level index values of each rail transit station in Step 3) to calculate the scores of each second-level index;

[0098] 42) Use the analytic hierarchy process to determine the weights of the second-level evaluation indexes in the corresponding first-level evaluation indexes;

[0099] 43) Perform weighted calculation on the scores and the corresponding weights to obtain the first-level index values corresponding to the first-level evaluation indexes of each rail transit station.

[0100] Step 5) Integrate all the first-level index values onto the corresponding rail transit stations, and input the data into the geographic spatial information system for summarization to form a database of the built environment characteristics around urban rail transit stations;

[0101] Step 6) Use the comprehensive graphical method to superimpose and represent the analysis results of each sub-item evaluation index, and draw a development status map of the environment around the rail transit station, as Figure 6-1 , Figure 6-2 , Figure 6-3 , Figure 6-4 shown, to achieve the visual expression of the development characteristics of the built environment around the rail transit station, which is convenient for subsequent proposing planning adjustment strategies for the evaluation index scores of each rail transit station.

[0102] The above are only some embodiments of the present invention. For those of ordinary skill in the art, without departing from the inventive concept of the present invention, several modifications and improvements can still be made, and these all belong to the protection scope of the present invention.

Claims

1. An evaluation method for the built environment around rail transit stations based on the TOD development model, characterized in that: It includes the following steps: Step 1) Construct a built environment evaluation index system; the built environment evaluation index system includes primary evaluation indicators and secondary evaluation indicators; the primary evaluation indicators include convenience, comfort, vitality and style characteristics; among the secondary evaluation indicators, the convenience includes transfer convenience, slow-moving accessibility, facility diversity and land use complexity; the comfort includes openness, greening, lighting, street furniture, sense of security and aesthetics; the vitality includes commercial attractiveness and the richness of informal operations; the style characteristics include style type and style similarity; The sub-item evaluation indicators of transfer convenience include the number of subway lines and exits, and the number of connecting bus lines and stations; The sub-item evaluation indicators of slow travel accessibility include walking coverage and cycling coverage; The sub-item evaluation indicators of facility diversity include the number of catering, hotels, sports and fitness, and leisure and entertainment facilities; The sub-item evaluation indicators of the land use complexity include the number of enterprises and residential areas contained in the walking time zone, and the ranking comprehensive score of supporting facilities; The openness is the proportion of sky calculated based on the street view; The green area is the green area ratio calculated based on the street view; The lighting is the number of street lamps calculated based on the street scene; The street furniture is the number of seats calculated based on the street view; The sense of security is an environmental sense of security evaluation value obtained based on a machine learning scoring model; The aesthetic feeling is an environmental aesthetic evaluation value obtained based on a machine learning scoring model; The sub-item evaluation indicators of commercial attractiveness include population heat value, pedestrian distribution and circle structure, bicycle usage heat and motor vehicle usage heat; The sub-evaluation indicators of the informal business richness include the number of small vendors; The style type is style similarity; The uniqueness of the style and features is the style and features characteristic index; Step 2) Calculate the walking isochrone of each rail transit station: 21) Calculate the walking time between any two geographical locations with the help of the data interface of the Internet map service provider; 22) Taking each rail transit station as the object, the geographical location of the time to reach the same rail transit station within the set time range is marked to form an area range, and the set time walking isochronous circle of each rail transit station is drawn; Step 3) calculating the secondary index value of the walking isochronous circle corresponding to each rail transit station on each secondary evaluation index; Step 4) calculating the first-level index value of the walking isochronous circle corresponding to each rail transit station on each first-level evaluation index; Step 5) All primary indicator values ​​are integrated into the corresponding rail transit stations, and the data are entered into the geographic spatial information system for aggregation to form a database of built environment characteristics around urban rail transit stations; Step 6) Use a comprehensive graphical method to overlay the results of each sub-item evaluation indicator and draw a development status map of the surrounding environment of the rail transit station.

2. The evaluation method for the built environment around rail transit stations based on the TOD development model according to claim 1, characterized in that: In the step 3), the secondary indicator value corresponding to each secondary evaluation indicator is the average value of each sub-item evaluation indicator under each secondary evaluation indicator.

3. The evaluation method for the built environment around rail transit stations based on the TOD development model according to claim 2, characterized in that: The step 4) comprises: 41) Linearly normalizing the secondary index value of each rail transit station in step 3) to calculate the score of each secondary evaluation index; 42) Use the analytic hierarchy process to determine the weight of the secondary evaluation indicators in the corresponding primary evaluation indicators; 43) Perform weighted calculation on the scores and the corresponding weights to obtain the primary index values corresponding to the primary evaluation indicators of each rail transit station.

4. The evaluation method for the built environment around rail transit stations based on the TOD development model according to claim 1, characterized in that: The set time is 5 to 15 minutes.

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