Dynamic Grid-Based Spatial Density Visualization and Rail Transit Station Prediction

Dados Bibliográficos

ID22031633
AutoresZhi Cai (0000-0002-6161-1644, Beijing University of Technology), Meilin Ji (Beijing University of Technology), Qing Mi (0000-0001-5063-3189, Beijing University of Technology), Bowen Yang (0009-0007-5608-6260, Beijing University of Technology, autor correspondente), Xing Su (0000-0002-9720-1196, Beijing University of Technology), Limin Guo (0000-0002-3061-4965, Beijing University of Technology), Zhiming Ding (0000-0002-2057-5325, Chinese Academy of Sciences)
Ano2021
Volume10
Fascículo12
Páginas804
Data de publicação2021-11-30
Open AccessSim
TipoARTICLE
PeriódicoISPRS International Journal of Geo-Information (JOURNAL)
Identificadores do periódicoISSN: 2220-9964 • E-ISSN: 2220-9964
EditoraMDPI AG (PUBLISHER • IT)
DOI10.3390/ijgi10120804
OpenAlexW3216755193
IdiomaEN
Referências citadas31

The urban rail transit stations are an important part of an urban transit system. Scientific and reasonable location of rail transit station can greatly alleviate traffic pressure. The number of people in the surrounding area of a rail transit station is an important factor for site selection. However, it is difficult to obtain the spatial distribution of population, which brings great difficulties in terms of site selection. Due to the large-scale popularization of AP (Access Point) in China, the spatial distribution of AP is used instead of population distribution to assist site selection. Therefore, a density visualization method based on a dynamic grid is proposed, which can help decision-makers intuitively see the AP density of the uncovered grid of rail transit stations, and then cluster the AP density of the uncovered area to predict the location of new rail transit stations. The validity of the proposed method is demonstrated by using the AP dataset and rail transit data of Beijing in 2013. The results show that our method has high accuracy in predicting the location of rail transit stations. It can provide data support for urban traffic development and management

Beijing · Cartography · China · Geographic information system · Geography · Grid · Population · Public transport · Rail transit · Site selection · Transport engineering · Urban rail transit · Computer Science · Engineering · Human Mobility and Location-Based Analysis · Transportation Planning and Optimization · Urban Transport and Accessibility