Revealing intra-urban hierarchical spatial structure through representation learning by combining road network abstraction model and taxi trajectory data

Revealing intra-urban hierarchical spatial structure through representation learning by combining road network abstraction model and taxi trajectory data

10.1080/19475683.2023.2241526

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Bibliographic Details
Main Authors: Sheng Hu, Song Gao, Wei Luo, Liang Wu, Tianqi Li, Yongyang Xu, Ziwei Zhang
Other Authors: GEOGRAPHY
Format: Article
Published: Taylor & Francis 2023
Online Access:https://scholarbank.nus.edu.sg/handle/10635/246442
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Institution: National University of Singapore
id sg-nus-scholar.10635-246442
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spelling sg-nus-scholar.10635-2464422024-11-11T17:23:39Z Revealing intra-urban hierarchical spatial structure through representation learning by combining road network abstraction model and taxi trajectory data Sheng Hu Song Gao Wei Luo Liang Wu Tianqi Li Yongyang Xu Ziwei Zhang GEOGRAPHY 10.1080/19475683.2023.2241526 Annals of GIS 29 04 499-516 2023-12-12T01:19:10Z 2023-12-12T01:19:10Z 2023-07-31 Article Sheng Hu, Song Gao, Wei Luo, Liang Wu, Tianqi Li, Yongyang Xu, Ziwei Zhang (2023-07-31). Revealing intra-urban hierarchical spatial structure through representation learning by combining road network abstraction model and taxi trajectory data. Annals of GIS 29 (04) : 499-516. ScholarBank@NUS Repository. https://doi.org/10.1080/19475683.2023.2241526 1947-5683 https://scholarbank.nus.edu.sg/handle/10635/246442 Taylor & Francis Taylor & Francis
institution National University of Singapore
building NUS Library
continent Asia
country Singapore
Singapore
content_provider NUS Library
collection ScholarBank@NUS
description 10.1080/19475683.2023.2241526
author2 GEOGRAPHY
author_facet GEOGRAPHY
Sheng Hu
Song Gao
Wei Luo
Liang Wu
Tianqi Li
Yongyang Xu
Ziwei Zhang
format Article
author Sheng Hu
Song Gao
Wei Luo
Liang Wu
Tianqi Li
Yongyang Xu
Ziwei Zhang
spellingShingle Sheng Hu
Song Gao
Wei Luo
Liang Wu
Tianqi Li
Yongyang Xu
Ziwei Zhang
Revealing intra-urban hierarchical spatial structure through representation learning by combining road network abstraction model and taxi trajectory data
author_sort Sheng Hu
title Revealing intra-urban hierarchical spatial structure through representation learning by combining road network abstraction model and taxi trajectory data
title_short Revealing intra-urban hierarchical spatial structure through representation learning by combining road network abstraction model and taxi trajectory data
title_full Revealing intra-urban hierarchical spatial structure through representation learning by combining road network abstraction model and taxi trajectory data
title_fullStr Revealing intra-urban hierarchical spatial structure through representation learning by combining road network abstraction model and taxi trajectory data
title_full_unstemmed Revealing intra-urban hierarchical spatial structure through representation learning by combining road network abstraction model and taxi trajectory data
title_sort revealing intra-urban hierarchical spatial structure through representation learning by combining road network abstraction model and taxi trajectory data
publisher Taylor & Francis
publishDate 2023
url https://scholarbank.nus.edu.sg/handle/10635/246442
_version_ 1821198153716596736

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