Geospatial Big Data and Remote Sensing for Urban Analysis
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing for Geospatial Science".
Deadline for manuscript submissions: 30 January 2026 | Viewed by 10
Special Issue Editors
Interests: geospatial big data; high-performance computation; human behavior analysis
Interests: remote sensing; urban environment; change detection; time-series analysis
Interests: planning support methods; big data analytics; urban computing
Special Issue Information
Dear Colleagues,
The integration of geospatial big data and remote sensing is essential for addressing the complex challenges of modern urban analysis amid rapid global urbanization, where 68% of the world’s population is predicted to live in cities by 2050. Traditional static datasets fail to capture the dynamic, multi-scale complexities of urban systems—such as real-time mobility patterns, land-use changes, and climate vulnerabilities—whereas geospatial big data (e.g., mobile phone data, GPS trajectories, and IoT sensor networks) provide granular, real-time insights into human activities, and remote sensing (satellite/UAV imagery) offers synoptic views of urban structure and environmental dynamics at regional and global scales. In an era of unprecedented urban change, their combination is not optional but vital for transforming fragmented data into actionable, adaptive solutions that balance growth, livability, and climate resilience.
This Special Issue focuses on advancing research at the intersection of geospatial big data and remote sensing technologies, exploring how their integration enables unprecedented insights into urban structure, function, and evolution.
This Special Issue highlights synergies between multi-source geospatial big data (mobile phone data, GPS trajectories, IoT sensors, OpenStreetMap, and social media geotags) and high-resolution remote sensing (satellite/UAV imagery and LiDAR). This Special Issue welcomes contributions on the following topics:
- Novel methods for fusing geospatial big data and remote sensing in urban modeling.
- AI/ML applications for urban feature extraction, change detection, and trend prediction.
- Spatio-temporal analysis of urban mobility, land use, and resilience.
- Decision support systems, digital twins, and visual analytics for urban planning.
We look forward to receiving your contributions.
Dr. Chen Zhou
Dr. Chao Sun
Dr. Shanqi Zhang
Prof. Dr. Manchun Li
Guest Editors
Manuscript Submission Information
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Keywords
- geospatial big data
- remote sensing
- multi-source geographical data fusion
- urban planning
- AI-driven modeling
- decision support
- real-time monitoring
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