Advances in Remote Sensing and Geospatial Artificial Intelligence (GeoAI) for Geomorphological and Archaeological Research

Dear Colleagues,

Recent advances in remote sensing technologies, Geographic Information Systems (GIS), and Geospatial Artificial Intelligence (GeoAI) have fundamentally transformed geomorphological and archaeological research. The rapid evolution of Earth observation technologies—including high-resolution satellite imagery, unmanned aerial vehicles (UAVs), LiDAR, synthetic aperture radar (SAR), hyperspectral and thermal sensors, and cloud-based geospatial platforms—has significantly enhanced our ability to observe, map, monitor, and model Earth's dynamic surface processes and archaeological landscapes. At the same time, the emergence of Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), and Explainable Artificial Intelligence (XAI) has created unprecedented opportunities for extracting knowledge from large and complex geospatial datasets, enabling more accurate, efficient, transparent, and reproducible analyses.

This Special Issue aims to provide an international platform for publishing high-quality research on innovative applications of remote sensing and Geospatial Artificial Intelligence in geomorphological and archaeological investigations. We welcome original research articles, comprehensive review papers, technical notes, and methodological studies that advance our understanding of landscape evolution, geomorphic processes, geoarchaeology, archaeological prospection, cultural heritage documentation, environmental change, and the sustainable management of natural and cultural resources.

Emphasis is placed on interdisciplinary research integrating Earth observation, GIS, spatial analysis, GeoAI, computer vision, digital photogrammetry, and field investigations to address contemporary scientific challenges. Contributions employing Explainable Artificial Intelligence (XAI), foundation models, vision-language models, digital twins, cloud computing, multi-source data fusion, and advanced spatial analytics are especially encouraged.

The Special Issue seeks to highlight innovative methodologies and practical applications that improve the interpretation of geomorphological processes, archaeological landscapes, cultural heritage preservation, and human–environment interactions across multiple spatial and temporal scales.

Topics include, but are not limited to:

• Satellite remote sensing for geomorphological mapping and monitoring
• Earth observation for geomorphological change detection and landscape evolution
• Thermal infrared remote sensing for archaeological prospection and investigation
• Radar, SAR, and InSAR remote sensing for archaeology, geoarchaeology, and Paleolandscape reconstruction
• Geospatial intelligence for coastal, fluvial, desert, mountain, and karst geomorphology
• Geoarchaeology and archaeological landscape analysis
• Archaeological site detection, mapping, monitoring, and preservation
• Remote sensing for settlement pattern analysis and landscape archaeology
• Cultural heritage documentation, conservation, monitoring, and risk assessment
• Egyptological applications of remote sensing, GIS, and Geospatial Artificial Intelligence (GeoAI)
• Geospatial Artificial Intelligence (GeoAI) and Earth observation for geomorphological and archaeological research
• Machine learning, deep learning, computer vision, and Explainable Artificial Intelligence (XAI) in remote sensing
• GIS-based spatial analysis, predictive modelling, and spatial statistics
• UAV (drone)-based photogrammetry and remote sensing
• LiDAR applications in geomorphology, geoarchaeology, and archaeology
• SAR, multispectral, hyperspectral, thermal, and very-high-resolution remote sensing
• Digital Elevation Models (DEMs), terrain analysis, and geomorphometry for geomorphological applications
• Multi-source, multi-sensor, and multi-temporal data fusion
• Big geospatial data analytics and cloud computing platforms (e.g., Google Earth Engine)
• Foundation models, vision-language models, and geospatial large language models (GeoLLMs) for Earth observation
• Digital twins, 3D geospatial modelling, and virtual landscape reconstruction
• AI-assisted digital heritage, 3D modelling, and virtual reconstruction of archaeological sites
• AI-assisted analysis of material culture, inscriptions, epigraphy, and archaeological documentation
• Paleo landscape reconstruction and environmental change
• Climate change impacts on geomorphological processes and archaeological heritage
• Geohazards, environmental monitoring, and disaster risk assessment
• Human–environment interactions and anthropogenic landscape evolution
• Spatial decision support systems for environmental and cultural heritage management

This Special Issue seeks to promote interdisciplinary collaboration among researchers in remote sensing, geomorphology, geoarchaeology, archaeology, geography, GIScience, Earth observation, environmental sciences, computer science, artificial intelligence, and geospatial data science. By bringing together cutting-edge methodological developments and real-world applications, this Special Issue aims to demonstrate the expanding role of remote sensing and Geospatial Artificial Intelligence in advancing our understanding of past and present landscapes while supporting sustainable environmental management, archaeological exploration, and cultural heritage preservation.

Prof. Dr. Scot Smith
Dr. Kamal Darwish
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.

• artificial intelligence
• archaeology
• geology
• geomorphology
• remote sensing
• geo-hazards