A Data-Driven Framework for Walkability Measurement with Open Data: A Case Study of Triple Cities, New York

Abstract

Walking is the most common, environment-friendly, and inexpensive type of physical activity. To perform in-depth walkability analysis, one option is to objectively evaluate different aspects of built environment related to walkability. In this study, we proposed a computational framework for walkability measurement using open data. Three major steps of this framework include the web scrapping of publicly available online data, determining varying weights of variables, and generating a synthetic walkability index. The results suggest three major conclusions. First, the proposed framework provides an explicit mechanism for walkability measurement. Second, the synthetic walkability index from this framework is comparable to Walk Score, and it tends to have a slightly higher sensitivity, especially in highly walkable areas in urban core. Third, this framework was effectively applied in a metropolitan area that contains three small cities that together represent a small, old shrinking region, which extends the topical area in the literature. This framework has the potential to quantify walkability in any city, especially cities with a small population where walkability has rarely been studied, or those having no quantification indicator. For such areas, researchers can calculate the synthetic walkability index based on this framework, to assist urban planners, community leaders, health officials, and policymakers in their practices to improve the walking environment of their communities.

Tourist walkability and sustainable community-based tourism: conceptual framework and strategic model

“…Therefore, it is important to distinguish the state and federal government policies and how this drive or impede tourist walkability, thereafter, impacting the triple bottom line costs and benefits. Several authors postulate that city (Deng et al, 2020), country (Perluss, 2022), state and municipalities (Brown, Carlson, Kumar, and Fulton, 2018) and town centre (Antunes, D’Agostino, Albano & LePage, 2019) efforts and their calls for actions in promoting walking and walkable communities to drive small business receipts are vital and, in this paper, it will be named as state-level policies. These state-level policies will assume as an antecedent driver or obstacle to tourist walkability.…”

Evaluasi Kinerja Koridor Ruas Jalan Dr. Ir. H. Soekarno, Surabaya Berdasarkan Elemen Rancang Complete Street

“…Pengguna jalan adalah orang yang menggunakan jalan untuk berlalu lintas, dimana aktivitas lalu lintas adalah gerak kendaraan dan orang di ruang lalu lintas jalan [4]. Pengguna jalan dari hierarki tertinggi hingga terendah berdasarkan moda transportasinya dapat dikategorikan menjadi pejalan kaki, pesepeda, pengguna transportasi publik, kendaraan layanan darurat, dan kendaraan pribadi [5]. Yang jelas, suatu transportasi dikatakan dengan baik apabila waktu perjalanan cukup cepat dan tidak mengalami kecelakaan, frekuensi e-mail: erli.martha@urplan.its.ac.id pelayanan cukup, serta aman (bebas dari kemungkinan kecelakaan) dan kondisi pelayanan yang nyaman [6], dimana untuk mencapai kondisi yang ideal seperti ini, sangat ditentukan oleh berbagai faktor yang menjadi komponen transportasi ini, yaitu kondisi prasarana (jalan), sistem jaringan jalan, kondisi sarana (kendaraan), dan sikap mental pemakai fasilitas transportasi tersebut [7], yang berarti pengguna jalan dapat dikatakan sangat memiliki pengaruh terhadap kondisi lalu lintas, termasuk salah satunya keamanan dan keselamatan.…”

Does neighborhood walkability affect ethnic diversity in Berlin? Insights from a spatial modelling approach

“…More complex operationalization walkability measurement approaches at macrolevel have been also investigated. For instance, Weiss et al (2010) involved a scale rating system in their Objective Walkability Index (OWI), Bartzokas-Tsiompras & Photis (2017) used the Borda count method to define walkability weights from a national-wide questionnaire, while Habibian & Hosseinzadeh (2018) and Deng et al (2020) suggested a statistical weighting and aggregation scheme based on Principal Components Analysis (PCA). Interestingly, Su et al (2019), proposed a 13-item walkability index that applies the catastrophe theory model and accordingly reduces the uncertainty and subjectivity of other conventional, often arbitrary, weighting and aggregation schemes.…”