Walkability is the measure of walking comfortably in the urban environment, based on numerous parameters, including traversability, compactness, attractiveness, and safety. Recently, walkability has become a significant key to well-being quality in the urban environment through enhancement of the walking environment, including filling spaces with life, promoting sustainability, and attracting people for exercise. The walkable environment’s design and planning have been focused of attention because of its numerous benefits in various aspects, such as improvement of social life, sustainability, public health, and economy. Therefore, there is a crucial need to do more research to increase the understanding of walkability in the urban environment. There are different factors that affect the level of walkability in the built environment. Subsequently, using a geographic information system (GIS) together with multi-criteria decision-making and analysis (MCDA) is an efficient method for walkability analysis. Space syntax and its application can also serve as a critical factor in walkability assessment by evaluating the number of connections for each route. The validity of this analysis model was tested in two study cases. These cases covered two municipalities in Sweden that differ in many aspects, including size, number of roads, and public density; these are Gävle and Uppsala. Furthermore, the MCDA model was integrated with the analytic hierarchy process (AHP), and eight factors were selected based on their relative importance to the walkability assessment. The generated factor maps were set based on the widely implemented criteria of walkability, otherwise known as the 5Cs, which is developed by Transport for London (TFL). The 5Cs consists of connectivity, comfort, convenience, conviviality, and conspicuousness. The density of connections for each route was derived using natural streets based on the space syntax approach. The natural street map was used as the main map that incorporated all factors, after their derivation and normalization of their values. The final produced AHP-based maps were classified into three walkability classes representing routes with low to high levels of walkability. The One Factor At-time sensitivity analysis technique (OAT) was also applied to the GIS-MCDA model to analyse the uncertainty that can occur based on different reasons such as human error and weighting uncertainty.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:hig-36752 |
| Date | January 2021 |
| Creators | Nasef, Omar |
| Publisher | Högskolan i Gävle, Samhällsbyggnad |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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