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Spatial disparity of income-weighted accessibility in Brazilian Cities: Application of a Google Maps API
Institution:1. 777 Glades Road, Building SO 44 Room 284, School of Urban and Regional Planning, Florida Atlantic University, United States;2. School of Architecture and Urban Planning, University of Wisconsin – Milwaukee, PO Box 413, Milwaukee, WI 5320, United States;1. Medical Research Departments, Chi-Mei Medical Center, Taiwan;2. Department of Hospital and Health Care Administration, Chia-Nan University of Pharmacy and Science, Tainan, Taiwan;3. Ncphrology Department, Chi-Mei Medical Center, Tainan, Taiwan;4. National Taiwan University School of Medicine, Taiwan
Abstract:Equity in public transit ridership has attracted the attention of planning authorities as a mechanism to tackle social exclusion. The association of accessibility indexing with different income groups is fundamental to analyses of socio-spatial inequalities and identifying gaps in public transit services. However, few studies have addressed accessibility inequalities in medium-sized cities of the global South. This paper aims to identify spatial gaps in public transit service in seven medium-sized Brazilian cities by analyzing the relative accessibility of public transit and private automobiles for travel to central business districts (CBDs), which are primary employment and service centers. Demographic and socioeconomic data on the seven cities were extracted from the country's 2010 population census. To measure accessibility to CBDs, a Google Maps application programming interface was used to produce realistic estimates of travel times for public transit and private automobiles over different time periods. This method is more accurate than traditional accessibility calculation methods and provides real-time information on traffic conditions, such as speed limits, traffic jams, and waiting times. The study found significant intra-regional differences in accessibility to CBDs by public transit and private automobiles, providing a scientific basis to optimize the socio-spatial distribution of public transit services in seven cities in five different regions of Brazil.
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