Spatial Assessment of Commuting Patterns in India's National Capital Region
Autor(en): |
Manisha Jain
Robert Hecht |
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Medium: | Fachartikel |
Sprache(n): | Englisch |
Veröffentlicht in: | Built Environment, 1 Dezember 2019, n. 4, v. 45 |
Seite(n): | 507-522 |
DOI: | 10.2148/benv.45.4.507 |
Abstrakt: |
Contemporary urbanization as experienced in India is characterized by urban sprawl, which increases commuting distances and promotes private individual transport. This article takes India's largest region as a case study and uses data from the Census of India on commuting, the population, socio-economic and infrastructural factors as well as spatial data on urban and rural administrative boundaries to understand commuting patterns. This article has two major objectives: first, to map spatially commuting patterns (distances to work and modes of travel); second, to estimate the effect of people-based (minorities, illiteracy rate, household facilities) variables and place-based (basic amenities, road and rail network densities, etc.) variables on commuting. The research findings are as follows: short trips are prevalent in urban areas, while intermediate and long trips are prevalent in rural areas. Short trips are common in areas with a high share of minorities as well as illiteracy rates. Long trips are undertaken by public transport such as trains and buses, intermediate trips by two-wheelers and buses, and short trips on foot and by bicycle. Areas with high prevalence of long trips have a better provision of basic amenities. The paper recommends the following measures to reduce motorization and long commuting distances: (i) government initiatives to reduce private transport and promote transitbased transportation; (ii) the integration of rural and urban areas through public transport; (iii) the establishment of a unified regional transportation authority to integrate regional transportation; and (iv) the introduction of subsidies to reduce private transportation and the implementation of transportation policy proposals. |
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Datenseite - Reference-ID
10396142 - Veröffentlicht am:
05.12.2019 - Geändert am:
05.12.2019