# Walkability Compass--A Space Syntax Solution for Comparative Studies
## 4 Discussion
The St becomes a key index for walkability visualspacemeasurement as a series of known \"here\" and \"there\", and thus becomes related to the recognisable path as the mental City Image, as explained by [PERSON] [79]. The \"compass\" is the main output of our research; it contributes to walkability research and sustainable urban planning practice. Above this, additional discussion requires spatial pattern mapping and analysing methods adopted in our framework. From a technical point of view, zones of high-value concentration are analysed using hot-spot analysis--a GIS technique of spatial grouping aimed to map similarity patterns and anomalous values. The de Getis-Ord statistics [66] accompany the hot-spot analysis [80]; its mathematical formula and analysis pros and cons are discussed by [PERSON] et al. (2019) [81]. In our study, these statistical measures (the Getis-Ord and z-score) were functional, while the tests performed with the hot and cold spots gave a relatively local result. In other words, we could detect more spatial pattern similarities using spatial tessellation thresholding techniques rather than hot-spot techniques. Additional research is necessary to answer whether it resulted from the specificity of space syntax metrics. As such, space syntax metrics also require other comments. The PoP identifies the concentration of walkers and the starting points of walking journeys--the proximity of the walking destinations in numbers of various objects or a mix of land use. The number of objects could be a more precise and straightforward way to measure proximity. At the same time, the land use mix addresses it indirectly based on the premise that more land use functions create more potential travel destinations. It should be noted that the number of destinations should be counted, but walking distance to each of them should be evaluated to improve walkability modelling. Connectivity as a property of street network reflects favourability for walking, which in three reviewed cases of four is counted as the density of crossroads. It should be noted that the plain number of intersections addresses just a density of the street network and potential walking routes but says nothing about the character of urban spaces related to visibility and street facades. Finally, this research method workflow adopts the model validation procedure that compares the segment graph models with POI allocation and public transport stops. This idea is based on the movement economy concept by [PERSON] [56]. The theory states that \"(...) evolving space organisation in settlements first generates the distribution pattern of busier and quieter movement pattern flows, which then influence land-use choices, and these, in turn, generate multiplier effects on movement with further feedback on land-use choices and the local grid as it adapts itself to more intensive development\" [56]. In such a case, allocation and concentration of the more critical urban features such as shops, administrative and cultural buildings, and schools could be seen as a result of the generative field of the street network, and thus used to check if the mathematical simulation model is working well. The \"walkability compass\" could also be applied at a city division scale, thus comparing various neighbourhoods or even urban blocks and presenting universal decision support models for multiple stakeholders of city development: city administration, urban planners, developers, and NGOs. Furthermore, it could be pointed out that because of the simulative nature of the mathematical graph model, the same calculation could be made for a predicted plan, thus expanding the usability of the proposed model. The \"walkability compass\" concept relies on space syntax theory--a knowledge-based solution, thus contributing to the analytical and evidence-based design [82]. In addition to city walkability comparison, the study uses a web-mapping application to share results at the urban space level.