# A GIS-Based Analysis of the Light Rail Transit Systems in Spain
## 4 Materials and Methods  
The study was carried out by following the steps below (Figure 3):  
1. Analysis of previous studies and background. A bibliographic search was made in the main internet sites related to LRT on these topics: advantages and individual LRT in Spain, groups of LRTs in other countries, parametric and geographic analyses of metropolitan public transportation systems, and GIS as a tool for transportation systems.
2. Analysis of the sample. The LRTs to be evaluated were determined and divided into subgroups by whether or not there were conventional subway systems in the city itself.
3. Data and parameters to be evaluated in the study were defined: the sources cited in the literature review section were checked, and a list was determined (Table 1): Annual service users; line length; number of lines, number of stations, number of shared stations; capture area; potential users; daily users; users per station; acceptance rate; density of capture area; mean distance between stations; passengers per unit line.
4. Data processing with QGIS.
5. Geometrical data (LRT lines and stations) were drawn.
6. A shape with data from official census was included. Some lab work was carried out in order to obtain the population density in each census section.
7. Catchment areas around the station were drawn. For that, a buffer zone with 500 m radius was stated (Figures 4 and 5).
8. Finally, some parameters values were obtained: Line length; number of lines, number of stations, number of shared stations; capture area; potential users; mean distance between stations; passengers per unit line. The population affected in each catchment area was determined under the assumption that the population in each census area (minimum area for which there are census data) is uniformly distributed within each area. Furthermore, the population data was taken from the official 2017 census.
9. Results are defined in different tables.
1. Beyond the data referred in the previous step, annual service users' data were taken from the operators' 2017 annual reports (Table 2). Finally, documents of the Polytechnic University of Madrid Mobility Observatory were checked [53].
2. Ratios were defined after the aforementioned data: daily users; users per station; acceptance rate; density of capture area; passengers per unit line.
10. Discussion and conclusions. The values found were analyzed, and the main conclusions of the study were outlined.  
\begin{table}
\begin{tabular}{c c c} \hline \hline  & & **Description** \\ \hline
1 & Annual service users (million pax) & \\
2 & Line length (km) & \\
3 & Number of lines (units) & \\
4 & Number of stations (units) & \\
5 & Number of shared stations (units) & \\
6 & Capture area (km\({}^{2}\)) & Urban area within 500 m of a station \\
7 & Potential users (pop) & Population of the capture area \\
8 & Daily users (pax) & \(\frac{annual\ users}{280}\) \\
9 & Users per station (pax) & \(\frac{daily\ users}{ stations}\) (pax) \\
10 & Acceptance rate & _daily users_ (passengers) \\
11 & Density of capture area \(\left(\frac{\text{max}}{\text{km}^{2}}\right)\) & _potential users_ (passengers) \\
12 & Mean distance between stations (m) & _capturing area_ (km\({}^{2}\)) \\
13 & Passengers per unit line \(\left(\frac{\text{max}}{\text{km}^{2}}\right)\) & _passengers_ (pax) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Parameters and ratios of the study.  
\begin{table}
\begin{tabular}{c c c} \hline \hline  
Figure 3: Method.  
Figure 4: Cities in Group 2. Left-hand column: Barcelona; Barcelona; Bilbao; Seville. Right-hand column: Madrid, Madrid, Madrid; Valencia.