The Application of Artificial Intelligence in Geomatics

Dear Colleagues,

Artificial intelligence has become a very important and modern technology in the development of geomatics, offering advanced automation, accuracy, and scalability in spatial data processing. The rapid growth of geospatial datasets from satellites, unmanned aerial vehicles, and sensor networks, in general, has created a demand for intelligent systems capable of efficiently extracting meaningful information. Artificial intelligence addresses this challenge with machine learning and deep learning algorithms that enable automatic classification, feature extraction, and predictive modeling. In remote sensing, convolutional neural networks achieve high accuracy in land cover mapping, object detection, and change analysis, outperforming traditional pixel-based approaches. However, there are still many problems, and it is advisable to focus not only on object recognition in RGB data, but especially on remote sensing on merging with multispectral and hyperspectral data. Similarly, photogrammetry uses artificial intelligence to search for objects in images and models, and artificial intelligence can improve 3D modeling and reduce manual intervention. An important issue currently being addressed is the search for information in point clouds generated by both photogrammetry and laser scanning techniques.

In addition to image analysis in general, artificial intelligence plays an important role in interpreting data from LiDAR scanning devices, where segmentation and clustering algorithms can identify terrain features, vegetation, and built structures with remarkable accuracy. The integration of artificial intelligence with geographic information systems supports anomaly detection, spatial relationship recognition, and dynamic map generation, enabling real-time decision-making in urban planning, environmental monitoring, and disaster response. In addition, artificial intelligence-based predictive analytics leverage spatiotemporal correlations to forecast natural hazards and optimize resource allocation.

Synergies between artificial intelligence and emerging technologies such as cloud computing, edge processing, and autonomous platforms further enhance these capabilities. Unmanned aerial vehicles equipped with artificial intelligence-based navigation and object recognition streamline field data collection, while cloud-based artificial intelligence services facilitate large-scale geospatial analysis. Thanks to these advances, artificial intelligence is becoming not just a supporting tool but also a transformative force driving a new generation of geomatics, where automation, adaptability, and intelligence come together to address global challenges in sustainability, resilience, and smart infrastructure development. Although not appropriate for dignified science, artificial intelligence has long been used in military applications, and as history shows, over time, these techniques have been successfully used for civilian, scientific, and economic purposes. There is, therefore, much to explore and publish for these exact purposes.

Prof. Dr. Karel Pavelka
Guest Editor

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• artificial intelligence
• geomatics
• remote sensing
• photogrammetry
• LiDAR
• GIS
• machine learning
• deep learning
• UAV
• spatial analysis