Urban visual-spatial intelligence: linking human and sensor perception for sustainable urban development

Qihao Weng; Qianbao Hou; Zhixing Chen; Jón Atli Benediktsson; Paolo Gamba; Devis Tuia; Fan Zhang; Yonghao Xu; Meiliu Wu; Na Li; Michael Batty

doi:10.1038/s42949-025-00256-2

Urban visual-spatial intelligence: linking human and sensor perception for sustainable urban development

Qihao Weng^*, Qianbao Hou, Zhixing Chen, Jón Atli Benediktsson, Paolo Gamba, Devis Tuia, Fan Zhang, Yonghao Xu, Meiliu Wu, Na Li, Michael Batty^*

^*Corresponding author for this work

Research output: Contribution to journal › Comment/debate

1 Citation (Scopus)

Abstract

Understanding urban perception enhances urban intelligence research, aiding sustainable development and smart city. Urban Visual-Spatial Intelligence (UVSI) integrates human and sensor perception. This Perspective explores UVSI’s potential for sustainable development, identifies research gaps, and outlines future priorities. Advances in AI, high-performance computing, real-time data processing, and citizen science could significantly impact UVSI. Key research areas include spatiotemporal data integration, visual analytics, ethical frameworks, and inclusive methodologies for AI-driven urban management.

Original language	English
Article number	65
Journal	npj Urban Sustainability
Volume	5
Issue number	1
DOIs	https://doi.org/10.1038/s42949-025-00256-2
Publication status	Published - Dec 2025
Externally published	Yes

Bibliographical note

Publisher Copyright:
© The Author(s) 2025.

UN SDGs

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

SDG 11 Sustainable Cities and Communities

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10.1038/s42949-025-00256-2

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title = "Urban visual-spatial intelligence: linking human and sensor perception for sustainable urban development",

abstract = "Understanding urban perception enhances urban intelligence research, aiding sustainable development and smart city. Urban Visual-Spatial Intelligence (UVSI) integrates human and sensor perception. This Perspective explores UVSI{\textquoteright}s potential for sustainable development, identifies research gaps, and outlines future priorities. Advances in AI, high-performance computing, real-time data processing, and citizen science could significantly impact UVSI. Key research areas include spatiotemporal data integration, visual analytics, ethical frameworks, and inclusive methodologies for AI-driven urban management.",

author = "Qihao Weng and Qianbao Hou and Zhixing Chen and Benediktsson, \{J{\'o}n Atli\} and Paolo Gamba and Devis Tuia and Fan Zhang and Yonghao Xu and Meiliu Wu and Na Li and Michael Batty",

note = "Publisher Copyright: {\textcopyright} The Author(s) 2025.",

year = "2025",

month = dec,

doi = "10.1038/s42949-025-00256-2",

language = "English",

volume = "5",

journal = "npj Urban Sustainability",

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TY - JOUR

T1 - Urban visual-spatial intelligence

T2 - linking human and sensor perception for sustainable urban development

AU - Weng, Qihao

AU - Hou, Qianbao

AU - Chen, Zhixing

AU - Benediktsson, Jón Atli

AU - Gamba, Paolo

AU - Tuia, Devis

AU - Zhang, Fan

AU - Xu, Yonghao

AU - Wu, Meiliu

AU - Li, Na

AU - Batty, Michael

PY - 2025/12

Y1 - 2025/12

N2 - Understanding urban perception enhances urban intelligence research, aiding sustainable development and smart city. Urban Visual-Spatial Intelligence (UVSI) integrates human and sensor perception. This Perspective explores UVSI’s potential for sustainable development, identifies research gaps, and outlines future priorities. Advances in AI, high-performance computing, real-time data processing, and citizen science could significantly impact UVSI. Key research areas include spatiotemporal data integration, visual analytics, ethical frameworks, and inclusive methodologies for AI-driven urban management.

AB - Understanding urban perception enhances urban intelligence research, aiding sustainable development and smart city. Urban Visual-Spatial Intelligence (UVSI) integrates human and sensor perception. This Perspective explores UVSI’s potential for sustainable development, identifies research gaps, and outlines future priorities. Advances in AI, high-performance computing, real-time data processing, and citizen science could significantly impact UVSI. Key research areas include spatiotemporal data integration, visual analytics, ethical frameworks, and inclusive methodologies for AI-driven urban management.

UR - https://www.webofscience.com/wos/woscc/full-record/WOS:001549804300001

UR - https://www.scopus.com/pages/publications/105013238834

U2 - 10.1038/s42949-025-00256-2

DO - 10.1038/s42949-025-00256-2

M3 - Comment/debate

AN - SCOPUS:105013238834

SN - 2661-8001

VL - 5

JO - npj Urban Sustainability

JF - npj Urban Sustainability

IS - 1

M1 - 65

ER -

Urban visual-spatial intelligence: linking human and sensor perception for sustainable urban development

Abstract

Bibliographical note

UN SDGs

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