Remote Sensing and Artificial Intelligence for Urban Monitoring and Digital Twins

Dear Colleagues,

Urban environments are continuously evolving under the combined effects of urbanization, climate change, population growth, infrastructure ageing, and increasing exposure to natural and anthropogenic hazards. Monitoring these dynamics requires timely and accurate approaches, where multi-scale information support several operations like planning, maintenance, environmental assessment, emergency management, and long-term decision making.

Recent advances in remote sensing have considerably expanded the capability to observe these environments. Satellites, UAV platforms, airborne and terrestrial LiDAR, mobile mapping systems, SAR, thermal and hyperspectral sensors now provide complementary information at different spatial and temporal resolutions. At the same time, the increasing availability of these datasets poses new challenges for data integration, interpretation, uncertainty assessment, and operational use.

In this context, Artificial Intelligence is becoming a fundamental part of the workflow by supporting the extraction of meaningful information from complex geospatial data. Recent technologies based on Machine and Deep learning and Computer Vision are increasingly employed for tasks such as semantic segmentation, object detection, change detection, infrastructure inspection, environmental monitoring, and data fusion. Combined with physically based models, GIS, and multi-source remote sensing data, these approaches are highly supporting the development of urban Digital Twins that integrate heterogeneous geospatial datasets into dynamic and continuously updatable representations of a built environment.

This Special Issue aims to collate original research on methodologies and applications combining remote sensing and Artificial Intelligence for urban monitoring and Digital Twins. This Special Issue covers the complete workflow of observation, from data acquisition and processing to information extraction, modelling, monitoring, and decision support. Particular attention will be given to studies integrating multisensor systems and data sources, advanced AI techniques, and geospatial data to improve the understanding and management of urban environments.

This Special Issue aims to contribute to the broader mission of Remote Sensing in advancing the science and technology of remote sensing applications.

For this Special Issue, we welcome the submission of original research articles, review papers and case studies related, but not limited, to the following topics:

• Satellite, UAV and airborne remote sensing for urban monitoring;
• LiDAR, mobile mapping and 3D city modelling;
• Artificial Intelligence and Geospatial AI;
• Machine Learning and Deep Learning for remote sensing;
• Foundation Models for Earth Observation;
• Vision-Language Models and multimodal learning;
• Image segmentation, object detection and change detection;
• Urban Digital Twins;
• Infrastructure monitoring and asset management;
• Environmental monitoring in urban areas;
• Multi-sensor data fusion;
• Semantic understanding of urban environments;
• Smart cities and resilient urban systems;
• Remote sensing for disaster prevention and emergency management;
• Explainable AI for geospatial applications.

Dr. Fabiana Di Ciaccio
Dr. Erica Isabella Parisi
Guest Editors

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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized 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.

• remote sensing
• artificial intelligence
• urban monitoring
• digital twins
• geospatial AI
• earth observation
• UAV
• smart cities
• deep learning
• multimodal data fusion