GeoAI for Urban Sustainability Monitoring and Analysis

A special issue of Land (ISSN 2073-445X). This special issue belongs to the section "Land – Observation and Monitoring".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 218

Special Issue Editors

1. Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong
2. College of Geography and Remote Sensing, Hohai University, Nanjing 210098, China
Interests: coastal remote sensing; water resource remote sensing; GeoAI
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Guest Editor
Department of Urban Planning, School of Architecture and Civil Engineering, Xiamen University, Xiamen 361005, China
Interests: transport and land use; travel behavior; urban mobility; urban vibrancy; machine learning; spatial analysis; big data analytics; health
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Special Issue Information

Dear Colleagues,

GeoAI, or geographic artificial intelligence, is a powerful tool used for urban sustainability monitoring, analysis, and prediction by combining innovative artificial intelligence methods from space science, machine learning, deep learning, data mining, and cloud computing from big earth data. GeoAI plays a key role in pushing geographic information science (GIS) and earth observation toward a new stage of development by enhancing traditional geospatial analysis and mapping. By combining remote sensing data and GeoAI, we can classify and map land cover, track temporal changes in land use, and predict future trends regarding urban sustainability for better planning, management, and decision making. In summary, GeoAI exhibits vast potential to contribute to urban sustainability in the future.

In this Special Issue, we seek the submission of groundbreaking research and case studies that demonstrate urban-sustainability-related applications and advances in geographic artificial intelligence. Relevant topics include, but are not limited to, the following:

Geospatial artificial intelligence (geospatial AI or GeoAI) for urban land use and land cover mapping;
GeoAI for urban monitoring, modeling, analysis, and prediction;
AI in geostatistics and spatiotemporal urban-related modeling and simulation;
AI For urban-related geospatial data acquisition, precessing, and analysis;
AI For sustainability monitoring and evaluation in urban areas;
Big data and machine learning for urban studies.

The goal of this Special Issue is to collect papers (original research articles and review papers) that provide insights into GeoAI for urban sustainability monitoring and analysis. This Special Issue welcomes manuscripts that link the following themes:

  • Urban;
  • Sustainability;
  • GeoAI;
  • Remote sensing;
  • Big data;
  • Geography.

We look forward to receiving your original research articles and reviews.

Dr. Nan Xu
Dr. Yifu Ou
Dr. Jixiang Liu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Land is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


  • urban
  • sustainability
  • GeoAI
  • remote sensing
  • big data
  • geography

Published Papers

This special issue is now open for submission.
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