Deep Understanding of Urban Dynamics from Imprint Urban Toponymic Data Using a Spatial–Temporal–Semantic Analysis Approach

Urban land use is constantly changing via human activities. These changes are recorded by imprint data. Traditionally, urban dynamics studies focus on two-dimensional spatiotemporal analysis. Based on our best knowledge, there is no study in the literature that uses imprint data for better understan...

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Bibliographic Details
Main Authors: Yurong Chen, Feng Zhang, Xinba Li, Chuanrong Zhang, Ninghua Chen, Zhenhong Du, Renyi Liu, Bo Wang
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:ISPRS International Journal of Geo-Information
Subjects:
Online Access:https://www.mdpi.com/2220-9964/10/5/278
Description
Summary:Urban land use is constantly changing via human activities. These changes are recorded by imprint data. Traditionally, urban dynamics studies focus on two-dimensional spatiotemporal analysis. Based on our best knowledge, there is no study in the literature that uses imprint data for better understanding urban dynamics. In this research, we propose a spatial–temporal–semantic triple analytical framework to better understand urban dynamics by making full use of the imprint data, toponyms. The framework includes a text classification method and geographical analysis methods to understand urban dynamics in depth. Based on the inherent temporal and spatial information, we enrich semantic information with street names to explain urban dynamics in multiple dimensions. Taking Hangzhou city as an example, we used street names to reproduce the city changes over the past century. The results obtained through analysis of street names may accurately reflect the real development process of Hangzhou. This research demonstrates that imprint data left by urban development may play a pivotal role in better understanding urban dynamics.
ISSN:2220-9964