GeoAI and Urban Geography

Pengyuan Liu; Yujun Hou; Binyu Lei; Xiucheng Liang; Filip Biljecki

doi:10.1007/978-3-031-87421-5_18

GeoAI and Urban Geography

Pengyuan Liu
, Yujun Hou
, Binyu Lei
, Xiucheng Liang
, Filip Biljecki^*

^*Corresponding author for this work

Geography

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

Recognising GeoAI as an emerging and rapidly evolving field that has been increasingly adopted in urban geography, this chapter provides an overarching overview of the GeoAI methods for urban analytics. It begins by revisiting the theoretical underpinnings of urban theory and mapping the evolution of urban spatial analytics, tracing the journey from traditional statistical methods to the cutting-edge AI-driven approaches reshaping the discipline today. Beyond examining the current state of GeoAI, the chapter also identifies current trending topics and investigates future directions for developing human-centric methodologies that prioritise the needs and experiences of urban residents. By emphasising the human dimension of urban analytics, the chapter seeks to contribute to the ongoing discourse on how GeoAI can be harnessed to enhance city governance, urban planning, and the overall quality of urban life.

Original language	English
Title of host publication	GeoAI and Human Geography
Subtitle of host publication	The Dawn of a New Spatial Intelligence Era
Editors	Xiao Huang, Siqin Wang, John Wilson, Peter Kedron
Publisher	Springer
Pages	251-266
Number of pages	16
Edition	1
ISBN (Electronic)	9783031874215
ISBN (Print)	9783031874208, 9783031874239
DOIs	https://doi.org/10.1007/978-3-031-87421-5_18
Publication status	Published - 31 Jul 2025

Publication series

Name	Springer Geography
Publisher	Springer
ISSN (Print)	2194-315X
ISSN (Electronic)	2194-3168

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 11 Sustainable Cities and Communities

Keywords

City governance
GeoAI
Human-centric approaches
Spatial analytics
Urban geography

ASJC Scopus subject areas

Geography, Planning and Development
Urban Studies
Nature and Landscape Conservation
Earth and Planetary Sciences (miscellaneous)

Access to Document

10.1007/978-3-031-87421-5_18

Cite this

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title = "GeoAI and Urban Geography",

abstract = "Recognising GeoAI as an emerging and rapidly evolving field that has been increasingly adopted in urban geography, this chapter provides an overarching overview of the GeoAI methods for urban analytics. It begins by revisiting the theoretical underpinnings of urban theory and mapping the evolution of urban spatial analytics, tracing the journey from traditional statistical methods to the cutting-edge AI-driven approaches reshaping the discipline today. Beyond examining the current state of GeoAI, the chapter also identifies current trending topics and investigates future directions for developing human-centric methodologies that prioritise the needs and experiences of urban residents. By emphasising the human dimension of urban analytics, the chapter seeks to contribute to the ongoing discourse on how GeoAI can be harnessed to enhance city governance, urban planning, and the overall quality of urban life.",

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author = "Pengyuan Liu and Yujun Hou and Binyu Lei and Xiucheng Liang and Filip Biljecki",

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AU - Liu, Pengyuan

AU - Hou, Yujun

AU - Lei, Binyu

AU - Liang, Xiucheng

AU - Biljecki, Filip

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

PY - 2025/7/31

Y1 - 2025/7/31

N2 - Recognising GeoAI as an emerging and rapidly evolving field that has been increasingly adopted in urban geography, this chapter provides an overarching overview of the GeoAI methods for urban analytics. It begins by revisiting the theoretical underpinnings of urban theory and mapping the evolution of urban spatial analytics, tracing the journey from traditional statistical methods to the cutting-edge AI-driven approaches reshaping the discipline today. Beyond examining the current state of GeoAI, the chapter also identifies current trending topics and investigates future directions for developing human-centric methodologies that prioritise the needs and experiences of urban residents. By emphasising the human dimension of urban analytics, the chapter seeks to contribute to the ongoing discourse on how GeoAI can be harnessed to enhance city governance, urban planning, and the overall quality of urban life.

AB - Recognising GeoAI as an emerging and rapidly evolving field that has been increasingly adopted in urban geography, this chapter provides an overarching overview of the GeoAI methods for urban analytics. It begins by revisiting the theoretical underpinnings of urban theory and mapping the evolution of urban spatial analytics, tracing the journey from traditional statistical methods to the cutting-edge AI-driven approaches reshaping the discipline today. Beyond examining the current state of GeoAI, the chapter also identifies current trending topics and investigates future directions for developing human-centric methodologies that prioritise the needs and experiences of urban residents. By emphasising the human dimension of urban analytics, the chapter seeks to contribute to the ongoing discourse on how GeoAI can be harnessed to enhance city governance, urban planning, and the overall quality of urban life.

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KW - GeoAI

KW - Human-centric approaches

KW - Spatial analytics

KW - Urban geography

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SN - 9783031874239

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EP - 266

BT - GeoAI and Human Geography

A2 - Huang, Xiao

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A2 - Wilson, John

A2 - Kedron, Peter

PB - Springer

ER -

GeoAI and Urban Geography

Abstract

Publication series

Bibliographical note

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this