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; Micheal. Y. Yang; Peifeng Ma; Wei Huang; Tiangang Yin; Qiming Zheng; Yuhan Zhou; Greg Asner

doi:10.1038/s42949-024-00188-3

npj Urban Sustainability (Nov 2024)

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,
Micheal. Y. Yang,
Peifeng Ma,
Wei Huang,
Tiangang Yin,
Qiming Zheng,
Yuhan Zhou,
Greg Asner

Affiliations

Qihao Weng: JC STEM Lab of Earth Observations, Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University
Zhiwei Li: JC STEM Lab of Earth Observations, Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University
Yinxia Cao: JC STEM Lab of Earth Observations, Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University
Xiaoyan Lu: JC STEM Lab of Earth Observations, Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University
Paolo Gamba: Department of Electrical, Biomedical and Computer Engineering, University of Pavia
Xiaoxiang Zhu: Data Science in Earth Observation, Technical University of Munich
Yonghao Xu: Department of Electrical Engineering, Linköping University
Fan Zhang: Institute of Remote Sensing and Geographical Information System, School of Earth and Space Sciences, Peking University
Rongjun Qin: Department of Civil, Environmental and Geodetic Engineering, The Ohio State University
Micheal. Y. Yang: Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente
Peifeng Ma: Department of Geography and Resource Management, Institute of Space and Earth Information Science, Shenzhen Research Institute, The Chinese University of Hong Kong
Wei Huang: College of Surveying and Geo-informatics, Tongji University
Tiangang Yin: JC STEM Lab of Earth Observations, Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University
Qiming Zheng: JC STEM Lab of Earth Observations, Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University
Yuhan Zhou: JC STEM Lab of Earth Observations, Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University
Greg Asner: Center for Global Discovery and Conservation Science, Arizona State University

DOI: https://doi.org/10.1038/s42949-024-00188-3
Journal volume & issue: Vol. 4, no. 1
pp. 1 – 9

Abstract

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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.

Published in npj Urban Sustainability

ISSN: 2661-8001 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Social Sciences: Communities. Classes. Races: Urban groups. The city. Urban sociology: Urbanization. City and country; Social Sciences: Communities. Classes. Races: Urban groups. The city. Urban sociology: City planning
Website: https://www.nature.com/npjurbansustain

About the journal