Multidimensional Evaluation of Public Transport Accessibility

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27350%2F18%3A10241347" target="_blank" >RIV/61989100:27350/18:10241347 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989592:15310/17:73585361

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007/978-3-319-61297-3_11" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-319-61297-3_11</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-61297-3_11" target="_blank" >10.1007/978-3-319-61297-3_11</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Multidimensional Evaluation of Public Transport Accessibility

Popis výsledku v původním jazyce

Public transport conditions are analysed using simulated commuting to important employers and recording data about significant features of all simulated trips. Two forms of overall public transport accessibility evaluation are comparedrule based and multivariate based classifications. Rule based classification was developed in several variants integrating two or four indicators, average and non-aggregated values. More valuable results were obtained using extended set of indicators for non-aggregated trips. The multivariate classification utilizes a novel approach to K-means cluster analysis using decile values. The comparison of both classifications shows a primary role of expert based classification. K-means cluster analysis based on deciles or median values are suitable for establishing more common typology but not for a local accessibility evaluation.

Název v anglickém jazyce

Multidimensional Evaluation of Public Transport Accessibility

Popis výsledku anglicky

Public transport conditions are analysed using simulated commuting to important employers and recording data about significant features of all simulated trips. Two forms of overall public transport accessibility evaluation are comparedrule based and multivariate based classifications. Rule based classification was developed in several variants integrating two or four indicators, average and non-aggregated values. More valuable results were obtained using extended set of indicators for non-aggregated trips. The multivariate classification utilizes a novel approach to K-means cluster analysis using decile values. The comparison of both classifications shows a primary role of expert based classification. K-means cluster analysis based on deciles or median values are suitable for establishing more common typology but not for a local accessibility evaluation.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

50703 - Transport planning and social aspects of transport (transport engineering to be 2.1)

Projekt

<a href="/cs/project/GA14-26831S" target="_blank" >GA14-26831S: Prostorové simulační modelování dostupnosti</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Lecture notes in geoinformation and cartography. Volume 1

ISBN

978-3-319-61296-6

ISSN

1863-2246

e-ISSN

1863-2351

Počet stran výsledku

16

Strana od-do

149-164

Název nakladatele

Springer

Místo vydání

Cham

Místo konání akce

Ostrava

Datum konání akce

22. 3. 2017

Typ akce podle státní příslušnosti

CST - Celostátní akce

Kód UT WoS článku

000457178200011