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| Name | Research data | Research accuracy | Individuals studied | Advantages | Disadvantages |
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| Buffer-based accessibility of public transport stops | Road network data and public transport station data | Range of walking trips | Every bus stop | The actual travel network is considered | Areas not covered are by default unreachable by public transport |
| It is easy to operate | No consideration is given to actual travel conditions |
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| Face-to-face accessibility of public transport based on supply and demand models | Road network data, public transport stop and line network data, jobs data, population data, and traffic analysis areas | Traffic analysis zone (TAZ) | The entire study area | It can reasonably reflect the spatial variability of employment supply and demand, reflecting the temporal and spatial variability in the level of service of the transport network | The values of the accessibility indicators are not scaled and have no specific practical meaning |
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| Public transport network accessibility based on network analysis | Road network data, public transport stop, and line network data | Dividing the study area into grids | The entire study area | It fully reflects the network characteristics of the public transport network and can be used to compare the spatial distribution characteristics of the network in different cities | No consideration is given to the actual need to travel |
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| Public transport accessibility based on a cost-grid approach | Data on the spatial characteristics of the study area (mountains, water bodies, green spaces, etc.), data on the road network, data on public transport stops and lines, and data on jobs | Dividing the study area into raster | One point-based accessibility study | It is mainly used to present the accessibility of points and calculate the cost of travel to points and the availability of jobs or service levels | The requirements for raw data are high; the calculation process is complex and difficult; and the accessibility varies with the given range |
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| Public transport accessibility based on an integrated approach to cost raster and network analysis | Data on the spatial characteristics of the study area (mountains, water bodies, green spaces, etc.), data on the road network, data on public transport stops and lines, and data on jobs | Dividing the study area into raster | One point-based accessibility | A network analysis based on the bus network and a walking cost calculation based on a cost-grid allows a more complete reach based on one point | The requirements for raw data are high; the calculation process is complex and difficult; it is not very operational in the analysis of the accessibility of large areas; and the accessibility of a given area varies with its size |
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| High-precision accessibility of public transport based on a high-performance graphics database | Road network data, public transport stop network data, travel schedules, and building locations | Building to building | The entire study area | The whole process of public transport travel is considered | It is computationally intensive and demanding in terms of data collection |
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| High-accuracy accessibility of public transport based on open map APIs | Open map API to obtain codes and start and finish latitude and longitude coordinates | Building to building | The entire study area | The whole process of public transport travel is considered, and travel costs are obtained more accurately | It requires sifting and processing of a large amount of data crawled |
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