City Future: The Innovative Fusion of Artificial Intelligence and Multi-Source Remote Sensing Data
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Urban Remote Sensing".
Deadline for manuscript submissions: 16 April 2026
Special Issue Editors
Interests: remote sensing; multi-modal data; data fusion; land-use classification; change detection
Interests: urban big data; remote sensing; deep learning; data fusion; environmental monitoring
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing; digital photogrammetry; urban ecology studies; 3D modeling
Interests: multi-source data fusion; remote sensing; generative model; deep learning; data augmentation; super-resolution; land cover mapping; onboard AI
Special Issue Information
Dear Colleagues,
The rapid evolution of artificial intelligence (AI), coupled with the explosive growth of multi-source remote sensing data, is profoundly transforming the way we perceive, analyze, and manage cities. In recent years, the integration of data from optical, SAR, LiDAR, hyperspectral, and social sensing platforms has provided unprecedented opportunities to monitor urban dynamics across multiple spatial and temporal scales. Meanwhile, breakthroughs in deep learning, self-supervised learning, and foundation models have enabled machines to extract complex spatial patterns and semantic knowledge from massive heterogeneous data sources, bridging the gap between observation and intelligent interpretation. As global cities face growing challenges such as climate change, resource scarcity, and population expansion, the fusion of AI and remote sensing offers a powerful path toward intelligent urban governance, sustainable development, and resilient city design.
This Special Issue aims to provide an international forum for sharing innovative theories, methodologies, and applications that harness AI to unlock the full potential of multi-source remote sensing data for future cities. We welcome original research focusing on the synergy between AI and remote sensing for urban studies. Topics of interest include, but are not limited to, the following:
- AI-driven fusion and interpretation of multi-source data such as optical, SAR, LiDAR, hyperspectral, and social sensing data;
- Foundation models and self-supervised learning for large-scale urban analysis;
- Urban land use and land cover mapping, change detection, and 3D reconstruction;
- Data reliability assessment and uncertainty modeling in heterogeneous urban datasets;
- Dynamic monitoring of urban infrastructure, transportation, and environment;
- Intelligent urban planning, risk assessment, and sustainable development supported by remote sensing.
Dr. Maofan Zhao
Dr. Shouhang Du
Prof. Dr. Jancsó Tamás
Dr. Abhishek Singh
Guest Editors
Dr. Jiahao Wu
Guest Editor Assistant
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com 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. Remote Sensing is an international peer-reviewed open access semimonthly 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 2700 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.
Keywords
- artificial intelligence
- urban remote sensing
- multi-source remote sensing
- foundation models
- land use and change detection
- 3D reconstruction
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