A bimodal accessibility analysis of Australia’s statistical areas
The map presented in this paper summarises the combined land- and airside accessibility within Australia. To this end, we calculate a bimodal accessibility index at the scale of statistical units by aggregating the (shortest) travel time for three route segments: (1) road travel from the origin to a...
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doaj-d79f2e317ef340c7aefa5365cfcea4012020-11-25T02:17:07ZengTaylor & Francis GroupJournal of Maps1744-56472019-01-01151778310.1080/17445647.2019.16085981608598A bimodal accessibility analysis of Australia’s statistical areasSarah Meire0Ben Derudder1Kristien Ooms2Ghent UniversityGhent UniversityGhent UniversityThe map presented in this paper summarises the combined land- and airside accessibility within Australia. To this end, we calculate a bimodal accessibility index at the scale of statistical units by aggregating the (shortest) travel time for three route segments: (1) road travel from the origin to a departure airport, (2) air travel, and (3) road travel from an arrival airport to the destination. The average travel time from a statistical unit to all other statistical units is calculated for the units’ population centroids, after which an accessibility surface is interpolated using kriging. The map shows that southeastern Australia is generally characterised by a high accessibility index with the most populated cities being hotspots of accessibility. Central and northern Australia are – with few exceptions – far less accessible. In addition to this largely-expected pattern, the map also reveals a number of specific and perhaps more surprising geographical patterns.http://dx.doi.org/10.1080/17445647.2019.1608598bimodal accessibilityair transportroad transportweb-based databig data |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Sarah Meire Ben Derudder Kristien Ooms |
spellingShingle |
Sarah Meire Ben Derudder Kristien Ooms A bimodal accessibility analysis of Australia’s statistical areas Journal of Maps bimodal accessibility air transport road transport web-based data big data |
author_facet |
Sarah Meire Ben Derudder Kristien Ooms |
author_sort |
Sarah Meire |
title |
A bimodal accessibility analysis of Australia’s statistical areas |
title_short |
A bimodal accessibility analysis of Australia’s statistical areas |
title_full |
A bimodal accessibility analysis of Australia’s statistical areas |
title_fullStr |
A bimodal accessibility analysis of Australia’s statistical areas |
title_full_unstemmed |
A bimodal accessibility analysis of Australia’s statistical areas |
title_sort |
bimodal accessibility analysis of australia’s statistical areas |
publisher |
Taylor & Francis Group |
series |
Journal of Maps |
issn |
1744-5647 |
publishDate |
2019-01-01 |
description |
The map presented in this paper summarises the combined land- and airside accessibility within Australia. To this end, we calculate a bimodal accessibility index at the scale of statistical units by aggregating the (shortest) travel time for three route segments: (1) road travel from the origin to a departure airport, (2) air travel, and (3) road travel from an arrival airport to the destination. The average travel time from a statistical unit to all other statistical units is calculated for the units’ population centroids, after which an accessibility surface is interpolated using kriging. The map shows that southeastern Australia is generally characterised by a high accessibility index with the most populated cities being hotspots of accessibility. Central and northern Australia are – with few exceptions – far less accessible. In addition to this largely-expected pattern, the map also reveals a number of specific and perhaps more surprising geographical patterns. |
topic |
bimodal accessibility air transport road transport web-based data big data |
url |
http://dx.doi.org/10.1080/17445647.2019.1608598 |
work_keys_str_mv |
AT sarahmeire abimodalaccessibilityanalysisofaustraliasstatisticalareas AT benderudder abimodalaccessibilityanalysisofaustraliasstatisticalareas AT kristienooms abimodalaccessibilityanalysisofaustraliasstatisticalareas AT sarahmeire bimodalaccessibilityanalysisofaustraliasstatisticalareas AT benderudder bimodalaccessibilityanalysisofaustraliasstatisticalareas AT kristienooms bimodalaccessibilityanalysisofaustraliasstatisticalareas |
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1724888045306511360 |