ArticleInternational journal of environmental research and public health2022
Past-Present-Future: Urban Spatial Succession and Transition of Rail Transit Station Zones in Japan.
Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- How Can Resource-Exhausted Cities Get Out of "The Valley of Death"? An Evaluation Index System and Obstacle Degree Analysis of Green Sustainable Development.International journal of environmental research and public health · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
In today's environmentally conscious society, advocated by a global point of view, land and building use around rail transit stations have changed in the urbanization process. Promoting urban construction and development centered on rail transit stations not only meets the actual needs of urban sustainable development but is also an important means to guide the development of innovative cities. Therefore, it is meaningful to study the characteristics of urban spatial succession, development rules, and future trends based on this new perspective. We analyzed the relationship between rail transit networks and urban form in Japan using GIS by investigating changes in land and building use around rail transit stations over 30 years in the 1980s, 1990s and 2000s (from 1985-2010) using factor analysis and cluster analysis, and we discussed the impact of land consolidation planning and the setting and site selection of new stations based on urban development to understand the development trends inside and outside station zones and urban spatial succession. The results showed the following: (1) There are certain relationships between the development of urban form and traffic demand, and the rail transit network in Japan has the characteristics of high accessibility and aggregation of a small network; (2) Commercial development with a high plot ratio is dispersed and diverted by high-density rail transit stations in the commercial center of Japan; and (3) Commercial sub-centers form complexes by integrating multi-line transfers and form regional linkages through clustered commercial development. Regional business centers realize the agglomeration and radiation of functions through the compound development of station zones. This case study on rail transit zones and urban spatial succession in Japan has important enlightenment significance for urban construction toward optimizing the location and development of suburban rail transit lines, promoting the compact development of cities, exploring new ways to build more reasonable transport, planning city design and layout for rail transit station zones, and providing decision-making references for urban regeneration and sustainable development.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.