How will AI transform urban observing, sensing, imaging, and mapping?

Qihao Weng, Zhiwei Li, Yinxia Cao, Xiaoyan Lu, Paolo Gamba, Xiaoxiang Zhu, Yonghao Xu, Fan Zhang, Rongjun Qin, Michael Ying Yang, Peifeng Ma, Wei Huang, Tiangang Yin, Qiming Zheng, Yuhan Zhou, Greg Asner

Research output: Contribution to journalArticlepeer-review

1 Citation (SciVal)

Abstract

Advances in artificial intelligence (AI) and Earth observation (EO) have transformed urban studies. This paper provides a commentary on how the AI-EO integration offers advancements in urban studies and applications. We conclude that AI will provide a deeper interpretation and autonomous identification of urban issues and the creation of customized urban designs. Open issues remain, especially in integrating diverse geospatial big data, data security, and developing a general analytical framework.

Original languageEnglish
Article number50
Journalnpj Urban Sustainability
Volume4
Issue number1
Early online date28 Nov 2024
DOIs
Publication statusPublished - 1 Dec 2024

Acknowledgements

The authors are grateful to the editors and reviewers for their constructive comments and suggestions which helped improve the manuscript.

Funding

This research has received funding from Global STEM Professorship, Hong Kong SAR Government (P0039329), Hong Kong RGC (grant reference # 15300923), and Hong Kong Polytechnic University (P0046482 and P0038446). The authors are grateful to the editors and reviewers for their constructive comments and suggestions which helped improve the manuscript.

FundersFunder number
RGC15300923
The Hong Kong Polytechnic UniversityP0046482, P0038446

    Fingerprint

    Dive into the research topics of 'How will AI transform urban observing, sensing, imaging, and mapping?'. Together they form a unique fingerprint.

    Cite this