# Walkability Compass--A Space Syntax Solution for Comparative Studies
## 3 Results
### The WebGIS Solution for Cities Walkability Comparison  
The results described in Sections 3.1-3.3 use indicators and pattern typology to compare the case study cities, and the walkability compass point is the \"direction\" of explanatory indices' synergy. The pattern map (Figure 5) is substantial to the typology we wanted to investigate and use for city comparison. However, these static maps do not reflect the walkability details at the street or even building-scale level, especially as space syntax offers it. Therefore, the results at the fine-grain city scale are presented using the WebGIS solution. Since scientific data started to be visualised in a dynamic manner and supplied with detailed statistics [68; 69], online maps became part of the research workflow [70]. Online maps meet the expectations of open science; therefore, walkability study results are made available using this technology. An online map application is shared via the following link: [[https://arcg.is/OuOOa1](https://arcg.is/OuOOa1)]([https://arcg.is/OuOOa1](https://arcg.is/OuOOa1)), Cities Walkability Comparison, accessed on 10 January 2022. The application has four map windows; each displays a single explanatory index, herein not aggregated to the hexagon tessellation.  
By changing the display, extent map windows adjust the scale and location to each other. The user can read Gr, Re, St and normalised PoP values of every building using the labelling function at the fine grain scale. The resulting WebGIS solutions interface is described in Figure 9A,B. Importantly, Figure 9B refers to the online dashboard, making the city walkability exploration more detailed by displaying the Gr, Re, St and PoP values within the maps extent. Interactive infographics on the left (Figure 9(B3)) report the averaged and maximum (Figure 9(B4)) index values of map window extent. By sharing the results with society, we enable the inhabitants' and other researchers' feedback on Gr, Re, St, and PoP further interpretations of walkability.  
Figure 7: The walkability compasses for case study walkability comparisons.  
Figure 8: Cities’ walkability explanatory indices pairs clusters.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & **Gr-Re** & **Gr-St** & **Gr-PoP** & **Re-St** & **Re-PoP** & **St-PoP** \\ \hline Bialystok & 0.387 & 0.369 & 0.607 & 0.991 & 0.523 & 0.481 \\ Gdansk & 0.511 & 0.522 & 0.297 & 0.99 & 0.5 & 0.475 \\ Kauss & 0.38 & 0.373 & 0.271 & 0.993 & 0.53 & 0.505 \\ Lublin & 0.469 & 0.456 & 0.439 & 0.994 & 0.532 & 0.508 \\ Malmo & 0.405 & 0.423 & 0.466 & 0.991 & 0.584 & 0.587 \\ Riga & 0.786 & 0.789 & 0.526 & 0.996 & 0.687 & 0.661 \\ Tallinn & 0.388 & 0.373 & 0.374 & 0.995 & 0.594 & 0.57 \\ Vilnius & 0.6 & 0.617 & 0.489 & 0.992 & 0.385 & 0.363 \\ \hline \hline \end{tabular} All correlations are of 0.01 significance, meaning that the chance of the random correlations is equal to 1.  
\end{table}
Table 5: Pearson correlations constitute walkability compasses.  
Figure 9: The WebGIS solutions for comparative analysis of explanatory walkability indexes. (**A**) main  
Web Map interface: (**A1**)--bookmarks facilitating switching between cities; (**A2**)--the legend; (**A3**)--the Gr map, (**A4**)--the Re map, (**A5**)--the St map; (**A6**)--the PoP map; (**A7**)--the hyperlinks to single city online maps with interactive dashboards. (**B**) the Web Map dashboard: (**B1**)--walkability balance graph, (**B2**)--the interactive map window, (**B3**)--the walkability indexes mean values graphs, (**B4**)--the walkability index max values graphs. The application can be freely accessed via [[https://arcg.is/ouoPOa1](https://arcg.is/ouoPOa1)]([https://arcg.is/ouoPOa1](https://arcg.is/ouoPOa1)), Cities Walkability Comparison, accessed on 10 January 2022.