Evaluating Urban Transport Oil Vulnerability of Asia Pacific Cities
Notice bibliographique
Résumé
The purpose of this thesis is to advance understanding of oil vulnerability1 of transport in Asia Pacific cities. This is achieved by the development of a multiscalar methodology which leads to nine published/submitted papers. This thesis is motivated by the concern of uncertain oil prices and the uneven dependence of oil in transport due to different urban designs and available modes to transport users. To achieve this purpose, a literature review (Chapter 2) is conducted, revealing prior oil vulnerability studies can be distinguished as being inter-city, intra-urban and disaggregate (household or personal) based. A conceptual framework based on prevailing vulnerability components is developed, defining oil vulnerability with the tripartite components of exposure, sensitivity and adaptive capacity. This conceptual framework helps to interpret previous and current research methodologies and approaches. The methodological approach of this thesis is based on these conceptualisations, as outlined in Chapter 3. A broad international comparison study is first presented in Chapter 4. Eleven major cities across the Asia Pacific are analysed, showing that compact cities like Hong Kong and Singapore are the least vulnerable. Australasian cities are highly vulnerable due to high car use, yet this vulnerability is offset by the relatively high income and wealth of their populations. New ways to research oil vulnerability are introduced. Data Envelopment Analysis (DEA) method is first used to benchmark the level of fuel stress, which refers to the proportion of fuel expenditure to disposable income. This is a direct measure of oil vulnerability, instead of proxy measures that were largely used in previous efforts. Oil resilience is also measured by how fuel stress could be offset by public and active transport usage. Chapter 5 used this method to examine Australian major cities, and Chapter 6 takes the DEA method to an international level, which internal divisions between Australia and Taiwan are compared. The thesis then narrows down to areas within cities (intra-urban). Presented in Chapter 7 is an improved vulnerability mapping method covering South-East Queensland (SEQ). This involves the use of previously unused adaptive capacity measures. The resultant spatial analysis provides a more nuanced socio-spatial understanding of oil vulnerability across urban spaces. Chapter 8 takes this approach and uses it in what is likely to be the first international spatial mapping comparison of intraurban oil vulnerability - Hong Kong is compared with Brisbane. The results show stark contrast of oil vulnerability of Hong Kong and Brisbane, where in the latter, the car is the dominant mode in most parts of the city. A comparative study of urban transport policy follows in Chapter 9. This involves a discursive analysis of urban transport policy of both Hong Kong and Brisbane and revealed the different levels of interest in oil vulnerability and the associated policy responses. Lastly, an analysis of Gold Coast’s recent light rail commencement is provided in Chapter 10 demonstrating the effect on vehicle travel distance on households between 2009 and 2015. The thesis contributes to transport and urban policy research by presenting likely the first international comparison of multi-level oil vulnerability, both quantitatively and qualitatively, inter-city and intra-urban. Insights drawn from the results will help to shape the debates on preparing for post-petroleum cities and to reduce automobile dependence for a more sustainable future.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,004 | 0,006 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».