Future access to essential services in a growing smart city: The case of Surrey, British Columbia

Mayaud, Jerome R.; Tran, Martino; Pereira, Rafael Henrique Moraes; Nuttall, Rohan

doi:10.1016/j.compenvurbsys.2018.07.005

Cited by 48 publications

(28 citation statements)

References 46 publications

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“…Previous studies have attempted to link urban accessibility patterns to demographic and socioeconomic factors at various scales. These range from global accessibility towards urban centres [24], to accessibility to sporting infrastructure at the megacity scale [25] and access to essential services at the neighbourhood scale [26]. A common approach in these studies is to derive statistical relationships between the basic characteristics of catchment populations.…”

Section: Introductionmentioning

confidence: 99%

Insights from Self-Organizing Maps for Predicting Accessibility Demand for Healthcare Infrastructure

Mayaud

Anderson²,

Tran

et al. 2019

Urban Science

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As urban populations grow worldwide, it becomes increasingly important to critically analyse accessibility—the ease with which residents can reach key places or opportunities. The combination of ‘big data’ and advances in computational techniques such as machine learning (ML) could be a boon for urban accessibility studies, yet their application in this field remains limited. In this study, we provided detailed predictions of healthcare accessibility across a rapidly growing city and related them to socio-economic factors using a combination of classical and modern data analysis methods. Using the City of Surrey (Canada) as a case study, we clustered high-resolution income data for 2016 and 2022 using principal component analysis (PCA) and a powerful ML clustering tool, the self-organising map (SOM). We then combined this with door-to-door travel times to hospitals and clinics, calculated using a simple open-source tool. Focusing our analysis on senior populations (65+ years), we found that higher income clusters are projected to become more prevalent across Surrey over our study period. Low income clusters have on average better accessibility to healthcare facilities than high income clusters in both 2016 and 2022. Population growth will be the biggest accessibility challenge in neighbourhoods with good existing access to healthcare, whereas income change (both positive and negative) will be most challenging in poorly connected neighbourhoods. A dual accessibility problem may arise in Surrey: first, large senior populations will reside in areas with access to numerous and close-by, clinics, putting pressure on existing facilities for specialised services. Second, lower-income seniors will increasingly reside in areas poorly connected to healthcare services, which may impact accessibility equity. We demonstrate that combining PCA and SOM clustering techniques results in novel insights for predicting accessibility at the neighbourhood level. This allows for robust planning policy recommendations to be drawn from large multivariate datasets.

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Section: Introductionmentioning

confidence: 99%

Insights from Self-Organizing Maps for Predicting Accessibility Demand for Healthcare Infrastructure

Mayaud

Anderson²,

Tran

et al. 2019

Urban Science

Self Cite

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“…Com o aumento do poder computacional, das ferramentas de análise e da disponibilidade dos dados, essa barreira foi diminuindo. Hoje, a disponibilidade de dados padronizados da oferta de transporte público como o GTFS fomentou a criação de ferramentas dedicadas que analisam e aplicam algoritmos de escolha de rota sobre a rede (módulos dedicados do ArcGis e OpenTrip-Planner, por exemplo), gerando tempos de viagem entre pares origem-destino que subsidiam o cálculo de indicadores de acessibilidade por transporte público (OWEN; LEVINSON, 2015;MAYAUD et al, 2018;EL-GENEIDY et al, 2016). O indicador mais utilizado é o indicador de acesso cumulativo de oportunidades, que calcula a quantidade de oportunidades acessíveis dado um tempo de viagem (PEREIRA, 2019).…”

Section: Sumário 1 Introduçãounclassified

Big Data de Transporte Público na Análise da Variabilidade de Indicadores da Acessibilidade às Oportunidades de Trabalho e Educação

Braga¹

2019

Preprint

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Accessibility, defined as the potential of opportunities for interaction, is a key concept in urban planning. Traditionally, the measurement of accessibility relied on methods that used simplified information on transit networks. Recent developments of public transport structured data through Global Transit Feed Specification (GTFS) fostered the creation and standardization of many tools to estimate travel times between origin-destination pairs, feeding the calculation of accessibility indicators. However, researchers are beginning to better understand to what extent differences between scheduled GTFS data and real services can affect accessibility estimates. The aim ofthis dissertation is to analyze the variability of accessibility indicators by public transport to work and education opportunities using location data and smart card data in a large transportation system. This variability of accessibility is investigated through three main hypotheses: 1) there is a difference between measuring it with Scheduled GTFS versus Empiric GTFS; 2) there is a difference between measuring it with Empiric GTFS based on median observed travel times versus based on a dispersion measure of observed travel times on the network; 3) there is a difference between measuring it to different departure times within peak hour. Initially, the proposed method consolidates and integrates one month of big data database, preparing them to the GTFS reconstruction approach. Using geoprocessing techniques, it starts by transforming raw GPS points to a structured transit timetable. The timetable times are then aggregated by 15 minutes intervals and segments between stops, determining the median and 85 percentile travel time to produce two empiric GTFS files. These files, alongside the Scheduled GTFS, are then used to estimate travel time between origin-destination pairs, making possible to estimate accessibility indicators based on scheduled and real-time data at different departure times within peak hour. Smart card data is used to estimate time thresholds to calculate cumulative indicators. The results corroborate the three hypotheses of variability on the spatial distribution of accessibility indicator by work and education activities. This variability is higher for access to jobs opportunities given its strong concentration on the central area of Fortaleza. These results suggest that decision makers take this variability into consideration when they assess the accessibility impacts of future interventions.

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“…In this context, accessibility must be addressed to consider the following elements: people (human behavior), production (economics), places (land use), and plexus (the network) [20].During the past two decades, considerable progress has been made in academic literature on accessibility [21,22]. The topic has been an important element in studies that address (i) transportation/land-use interactions [23][24][25][26][27], (ii) travel demand [28][29][30][31], (iii) relation of transportation projects with equity and territorial development [32,33], and (iv) location problems for urban facilities [34][35][36]. With the development of information geoprocessing technologies, models have become more robust, allowing for spatial analysis and the introduction of new assessment tools, such as socioeconomic variables and friction factors, among others [17,37,38].…”

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confidence: 99%

A Spatial Fuzzy Multicriteria Analysis of Accessibility: A Case Study in Brazil

et al. 2019

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Accessibility is a well-established concept in sustainable transportation literature; however, it is often measured through accessibility models that are still being developed. This article presents an accessibility evaluation model that applies multiple attributes, fuzzy functions, and spatial analysis tools. The model determines indices that reflect an average level of attractiveness for each potential destination (deemed a location of interest-LI). Each destination has different weights based on its degree of importance. Moreover, the model was developed in two phases: The first considered cost-distance metrics, and the second incorporated ground friction factors. The application of the model provides great contribution to the region under study (Campos do Jordão, a city located in a mountainous region of the state of São Paulo), thus presenting some implications for sustainable urban planning and mobility policies, especially in segregated areas with mixed inhabitant populations between tourists and local residents. The results have shown that special attention should be paid to planning new school facilities and city transportation systems. Most of these services are currently concentrated in the city's downtown area, making access to urban facilities inefficient and unfair. Using the results in urban projects, the allocation of future urban facilities or the reallocation of current urban facilities contributes to reduced impacts on urban mobility caused by individual motorized transportation in daily activities.increasing quality of life as well as sustainable development, while also influencing the relationship of the spatial position of the dwelling in relation to the opportunities. The ability, quantity, and diversity of possibilities to access activities, services, places, information, and other people is an essential issue in the quality of urban space, serving as a counterpoint to the fragmentation and dispersion found in many contemporary cities [3].The value of accessibility as an integrative device, particularly in its ability to establish a connection between transportation and land use, has recently gained ground in institutions that can effectively wield it as a planning tool [4,5]. Murawskia and Church [6] introduced a model that can be used to maximize access to health facilities by making selected improvements to the road system. Paez et al. [7] illustrated how positive and normative accessibility indicators can be used in tandem, testing the extent to which the behavioral experiences of individuals conform to an existing policy or suggested norm. The pedestrian scale accessibility was studied by Foti and Waddell [8] through a hierarchical graph of tradeoffs between modes and integration of micro-scale land-use data to measure the full range of alternative destinations in the city. Campbell et al. [9] showed that place-based accessibility is comparatively better in contour and gravity measures. However, the wealthiest areas have very low levels of place-based accessibility for all modes, whi...

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Future access to essential services in a growing smart city: The case of Surrey, British Columbia

Cited by 48 publications

References 46 publications

Insights from Self-Organizing Maps for Predicting Accessibility Demand for Healthcare Infrastructure

Insights from Self-Organizing Maps for Predicting Accessibility Demand for Healthcare Infrastructure

Big Data de Transporte Público na Análise da Variabilidade de Indicadores da Acessibilidade às Oportunidades de Trabalho e Educação

A Spatial Fuzzy Multicriteria Analysis of Accessibility: A Case Study in Brazil

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