WHAT MAKES A STREET WALKABLE? A DATA ANALYTIC APPROACH TO INVESTIGATING WALKABILITY FACTORS

Walkability is a hot topic for variety of disciplines, as well everyday walker. It affects the health, environment and liveliness our neighbourhoods. Walkable streets are necessary better lifestyle sustainable planet. The problem with walkability that we still don’t have general understanding concept. Every study differs in way they define walkability, thus making subjective topic. However, subjectivity causes contradiction science. In this study, aim to answer question what makes street walkable by using data analytic approach. features used other studies, new attributes specific were investigated. Street images extract data. was divided into nine categories: Street, Sidewalk, Obstacles, Urban Blocks, Amenities, Transportation, Attractiveness, People, Vehicles. Data collection carried out measuring physical through Remote Sensing QGIS, visually analyzing qualitative Google Maps/View double checking Open Map Overpass Turbo API. Attributes translated scores normalized where possible. Mutual Information Matrix Correlation processes conducted Rapidminer. processed relation overall assessment which defined personal rating. As result, matrices useful figuring relationship dependencies between different attributes. Applying analytics more comprehensive dataset will help identify global factors walkability.