Neighbourhood Walkability Evaluation by Using Walk- score Method, Case Study: Park Laleh and Eyvanak Neighbourhood

Nowadays, walkability is out of motto in the world. Considering to the benefits of environmental, social, cultural, economic, environmental perception and improve safety and security, walkability has become a basical issue in urbanism topics. The design of streets and houses and the establishment of facilities and services should be in a manner that naturally induce people to physical and social mobility during neighborhood daily life in a pedestrian-oriented neighborhood. Attention to understanding the factors that affect from the point of view of residents in evaluation walkability rate of a district, is an important issues that must be considered. Therefore, the present study has tried to introduce American walk-score method after introducing and exploring some different ways of walkability in urban areas.
Walk-score determined the rate of walkability in a specified direction with checking the physical characteristics of the path and also scoring the user absorbing to walk with considering the distance from the source. Walk Score includes walking routes and distances to amenities, road connectivity metrics, customizable amenity categories, weights, and distance decay functions. Walk-score uses Open Street Map for all road network data. We are able to calculate intersection density, link/node ratio, and average block length based on open street.
Map graph of the road network.Walk Score calculates a score by mapping out the walking distance to the closest amenity locations of 9 different amenity categories. Different numbers of amenities are counted in each category (for instance the first 10 restaurants and bars are counted, while only 1 park is counted), which are referred to as counts. Each category receives different weights as well, which shows that category’s important compared to other categories. The distance to a location, the counts and the weights determine a base score of an address, which is then linearly expanded to range from 0 to 100. After this, an address may receive a penalty for having poor pedestrian friendliness metrics, such as having long blocks or low intersection density.
For the objective of this research, walkability in two districts of Tehran is measured and compared in this article. One of these neighborhoods is Eyvanak neighborhood in Shahrake Gharb based on American method and the other one is Park Laleh neighborhood in the context of the neighborhood in the middle of the city. The results of walkability evaluation with using walk-score in these two neighborhoods indicate that Park Laleh neighborhood’s walk-score is higher than Eyvanak neighborhood’s walk-score and thus arcumstance of walkability in Park Laleh neighborhood is much better than Eyvanak neighborhood.
Unlike developing countries like Iran, In developed countries home buyers have more value for homes which have high walk-score. On average, home buyers attach greater value to walkable homes relative to other housing units in the same metropolitan area, controlling for other observable characteristics. These results provide a strong basis for concluding that improved walkability create real economic value for city residents. The apparent value that consumers attach to walkability likely stems from many sources. Consumers in more walkable neighborhoods may save money on driving (and transit) by virtue of the closer proximity of many destinations.
Walk Score was not positively and significantly correlated with housing values in our study. The relationship between Walk Score and housing prices was significant and negative. Our study shows that walkability doesn’t improve housing values. Housing values are not positively and significantly correlated with walkability in our neighborhoods. However, according to our study, it was observed that in our country, walkability doesn’t own a place in the value of homes and places of residence, and in a neighborhood with very high walk-score, the value of the property is lower than the neighborhood with low walk-score.
But Walk Score’s method has some limitations. While the algorithm is based on recent research around walkability, it does not account for these factors that also affect the propensity to walk. Street design, details like sidewalk presence or width, speed limits and actual automobile speeds, tree cover, street furniture are not included. Safety data, crime and crash data are not included although safety issues present significant barriers to the walkability of a neighborhood. Regarding to pedestrian-friendly community design, the algorithm lacks input on urban design features like building setbacks, clustering of destinations, parking placement, and frequency of storefronts that make a place more desirable for walking. Topography, no data on street or sidewalk slopes is included, which is also an inhibitor of walking. Weather, neither current conditions nor yearlong climate patterns are included. Because of these limitations, Walk Score cannot be relied upon as a comprehensive indicator of walkability and should be used with these caveats in mind.