## 4 Research Case
### Data Sources and Data Processing
#### 4.2.2 Independent Variable Data Sources and Processing  
Based on previous studies [25; 26], we established an 800-m radius buffer zone around the rail transit station. This study collected POI data within 800-m buffer areas centred at metro stations, using ArcGIS for spatial statistics and analysis of independent variables affecting the dependent variable. Considering Shenzhen's urban public transportation patterns and its polycentric built environment development characteristics, we selected 15 built environment factors as independent variables following existing research framework. These variables fall into three categories: socioeconomic variables, built environment variables, and \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
\begin{tabular}{c} Shenzhen \\ Metro Line 2 \\ \end{tabular} & 16 June 2019, 08:41 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Shenzhen rail transit card data. station characteristic variables [27]. The data sources and processing procedures are detailed below:  
1. Socioeconomic variables  
The larger the population size, the greater the transportation pressure borne by rail transit. Consequently, population is one of the significant factors influencing ridership at rail transit stations. Reasonable housing prices contribute to optimising urban resource allocation, enhancing land use efficiency, and improving the built environment, which, in turn, affect ridership at stations. 2. Building Environment Variables  
Points of interest (POI) within land use types represent crucial components of the built environment. In this study, POI data for Shenzhen, China, were systematically obtained using Python programming language through the open platform interface of Gaode Maps (AMAP). Gaode Maps categorises POI data into 23 primary categories. Based on these POI types, and in conjunction with urban land use classification standards [28], we classified land use into six major categories: commercial services, scenic spots, public services, government and corporate offices, residential land, and transportation facilities. The floor area ratio (FAR) is a key indicator measuring the intensity of land use development. It reflects to some extent the level of economic development and the density of resident activities within a region, serving as one of the important variables in describing built environment characteristics. The mixed diversity of land use can impact residents' travel patterns. The land use mix index, which indicates land use conditions, is often represented using the Shannon-Wiener Index and is also considered a built environment variable. Road network density is a significant indicator measuring the external accessibility of rail transit stations, directly reflecting the convenience of road travel for residents. The road network density complements and competes with the rail transit system, indirectly affecting ridership at rail transit stations, and is also included as a built environment variable. 3. Station Characterisation Variables  
The number of entries and exits, accessibility (specifically, the average travel time for residents to reach a target station from other stations within the rail transit network in this context), bus route layout, and bus stop configuration constitute the primary characteristics of rail stations. These factors significantly influence the transfer and connectivity between stations and their external environment, including other rail transit stations and other public transport modes. They describe the station features and affect the ridership at rail transit stations, thus serving as station characteristic variables. In this study, open-source data platforms such as AMAP open platform and OpenStreetMap (2021) [29; 30] were utilised to obtain raw data covering various aspects, including points of interest (POI), urban road networks, bus routes, and urban land use. Leveraging the powerful spatial geographic analysis capabilities of ArcGIS, we calculated the specific values of each relevant variable within an 800-m buffer zone.