## 3 Study Area and Data
### Explanatory Variables
#### 3.1.2 Socio-Economics  
In the category of socio-economic variables, there are two factors to be considered. The information about when those metro stations were opened was collected from a website named  
\"UrbanRail\" (Source: [[http://www.urbanrail.net/as/cn/shen/shenzhen.htm](http://www.urbanrail.net/as/cn/shen/shenzhen.htm)]([http://www.urbanrail.net/as/cn/shen/shenzhen.htm](http://www.urbanrail.net/as/cn/shen/shenzhen.htm))). With the information, we can calculate the elapsed days since stations were opened to the investigating days (14 October 2013 to 20 October 2013). A higher residential population is assumed to be positively correlated with ridership. Here, we obtained information on population distribution all around Shenzhen in 2013 collected from the website of WorldPop (Source: WorldPop (www.worldpop.org--School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project--Funded by The Bill and Melinda Gates Foundation (OPP1134076). [[https://dx.doi.org/10.5258/SOTON/WP00645](https://dx.doi.org/10.5258/SOTON/WP00645)]([https://dx.doi.org/10.5258/SOTON/WP00645](https://dx.doi.org/10.5258/SOTON/WP00645))). The population data were processed with ArcGIS 10.2 (Environmental Systems Research Institute, Inc (Esri) (2014) Arcgis. URL [[http://desktop.arcgis.com/en/arcmap/](http://desktop.arcgis.com/en/arcmap/)]([http://desktop.arcgis.com/en/arcmap/](http://desktop.arcgis.com/en/arcmap/))). Specifically, the buffers of all stations with a radius of 500 m were generated and the population within the buffers are aggregated, and the population distribution and 500 m buffers are illustrated as Figure 1.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Categories** & **Explanatory** & **Acronym of** & **Source** & **Minimum** & **Mean** & **Maximum** \\  & **Variables** & **Variables** & **Boalu Map** & 0 & 36.86 & 218 \\ \hline \multirow{4}{*}{Land use (The number of *****(land uses)** & Residential units & _Resistance_ & Baidu Map & 0 & 48.52 & 291 \\  & Restaurants & _Restaurant_ & Baidu Map & 0 & 115.18 & 400 \\  & Retailers/shopping & _Shapping_ & Baidu Map & 0 & 5.64 & 64 \\  & Schools & _School_ & Baidu Map & 0 & 18.58 & 298 \\  & Offices & _Offices_ & Baidu Map & 0 & 9.60 & 73 \\  & Banks & _Baidu Map_ & 0 & 1.008 & 10 \\  & Hospitals & _Hotels_ & _Hotel_ & Baidu Map & 0 & 13.24 & 135 \\ \hline \multirow{4}{*}{Network structure} & Distance to the city & \multirow{2}{*}{_Dis\_to\_center_} & \multirow{2}{*}{Calculated} & 0.36 & 9.97 & 27.41 \\  & Center & Degree centrality & _Degra_ & Calculated & 0.017 & 0.037 & 0.068 \\  & Betweenness & _Betweenness_ & Calculated & 0 & 0.11 & 0.31 \\ \hline \multirow{2}{*}{Socio-economics} & Population & _Pop_ & Worldpop & 27.54 & 156.49 & 354.55 \\  & Days since opening & _Days\_open_ & UrbanRail & 839 & 1762 & 3132 \\ \hline \multirow{2}{*}{
\begin{tabular}{c} Intermodal \\ transport \\ accessibility \\ \end{tabular} } & The number of bus & \multirow{2}{*}{_Bus_} & \multirow{2}{*}{Baidu Map} & \multirow{2}{*}{0} & \multirow{2}{*}{7.72} & \multirow{2}{*}{30} \\  & stations within PCA & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 2: Summary of explanatory variables.  
From Figure 1, we can observe that the densely populated areas are mainly surrounding the metro stations. The impact of residential population density on ridership in the buffer zone of each station will be analyzed in further modeling.