Computing travel time when the exact address is unknown: a comparison of point and polygon ZIP code approximation methods

Berke, Ethan M.; Shi, Xianming

doi:10.1186/1476-072x-8-23

Cited by 64 publications

(46 citation statements)

References 18 publications

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“…A GIS layer representing road Berke and Shi (2009) and modified based on the author's knowledge of speed limits in the immediate study area. Second, the edges of the network were split into lixels of approximately one-tenth mile (0.16 km) for the purposes of computing the density estimates, and minimum travel time for each lixel was computed based on its length and assigned maximum velocity.…”

Section: Discussionmentioning

confidence: 99%

Probabilistic potential path trees for visualizing and analyzing vehicle tracking data

Downs

Horner

2012

Journal of Transport Geography

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Section: Discussionmentioning

confidence: 99%

Probabilistic potential path trees for visualizing and analyzing vehicle tracking data

Downs

Horner

2012

Journal of Transport Geography

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“…Onega et al 2008Onega et al , 2010aOnega et al , 2010bOnega et al , 2011Onega, Duell, Shi, Demidenko, Gottlieb, et al 2009;Celaya et al 2010). Berke and Shi (2009) found that when simply using geometric centroids of zip code polygons, which was adopted by many health-care studies, the error of the estimated average travel time can go above 10%; when more detailed population data are incorporated, the average error can go below 3%. With RCMC, rather than using centroids (however defined) or service area belts to measure aggregate travel distance or travel time, one can make individual measurements based on the disaggregated locations, which avoids the imprecision problem and its consequences.…”

Section: Health-care Access Assessmentmentioning

confidence: 99%

Computational and data sciences for health-GIS

Shi

Wang

2015

Annals of GIS

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Computational and data sciences are transforming the entire science enterprise. In the arena of GIS, this is represented by the emergence of cyberGIS. We provide an overview of applying the cyberGIS approach to spatial analysis for health studies. We emphasize that cyberGIS is not just a service to traditional spatial analyses, but itself is an alternative approach to problem solving. Some fundamental and profound distinctions of cyberGIS approaches in health-GIS include the following: (1) they may greatly reduce the reliance on models or assumptions, and instead seek actual empirical evidence through mining a large amount of data or virtual empirical evidence generated through computation; (2) they tend to be non-parametric and tend to generate local solution; (3) they are scalable to high-resolution and less aggregated data; (4) they tend to be stochastic rather than deterministic; and (5) with these approaches, the large amount of data may not be only from input data-sets, but also from analytical workflows. We described the kernel ratio estimation for local intensity estimation, the restricted and controlled Monte Carlo for data disaggregation, and unrestricted and controlled Monte Carlo for statistical significance evaluation as examples of the cyberGIS approaches in health-GIS.

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“…2011 for an overview). Using metric distances seems obsolete since the new GIS technologies makes possible to calculate, with a relatively high precision, the temporal distances (Berke and Shi 2009;Salonen et al;Shaw 2006) or the economic ones (cf. Combes and Lafourcade 2005).…”

Section: Preliminary Analysismentioning

confidence: 99%

A geographical methodology for assessing nodality of a road network. Case study on the western Moldavia

Tudora¹,

Eva²

2014

AGS

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The study tests the concept of nodality in a three-dimensional space, both as a projection of the physical-geographical support and an expression of topological centrality, which is insufficiently employed in papers attempting to evaluate the geographical or potential accessibility. The junctions of the reticular systems will be positioned differently within the network depending on the acquired nodality values, which may influence through their importance the potential for development of the polarized territory. By focusing on a methodology specific to nomothetic epistemology, aimed at highlighting the vulnerabilities induced by the dysfunctions within the road network and obtaining nodal hierarchies, the study allows for the extraction of legitimate relationships, which can be extrapolated beyond the particular space matrix selected for demonstration purposes only.

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Computing travel time when the exact address is unknown: a comparison of point and polygon ZIP code approximation methods

Abstract: Background: Travel time is an important metric of geographic access to health care. We compared strategies of estimating travel times when only subject ZIP code data were available.

Cited by 64 publications

References 18 publications

Probabilistic potential path trees for visualizing and analyzing vehicle tracking data

Probabilistic potential path trees for visualizing and analyzing vehicle tracking data

Computational and data sciences for health-GIS

A geographical methodology for assessing nodality of a road network. Case study on the western Moldavia

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