Geo-IT and artificial intelligence - The next stage of the digital revolution?; [Geo-IT und künstliche intelligenz - die nächste stufe der digitalen revolution?]

Abstract

This article examines the use of artificial intelligence to improve the efficiency of interpreting three-dimensional geospatial data. Modern surveying and mapping technologies can produce large volumes of 3D information, including point clouds and detailed surface representations. Manually interpreting these datasets can require substantial time and specialist knowledge. Artificial intelligence and machine-learning methods offer opportunities to automate parts of the interpretation process by identifying patterns, objects, and structures within complex spatial datasets. The article considers how intelligent methods can support the classification and analysis of 3D information and potentially improve the speed of geospatial workflows. AI-based interpretation can be useful in areas such as surveying, mapping, infrastructure documentation, urban modelling, and environmental analysis. However, automated results depend strongly on the quality and diversity of the data used to develop and evaluate the algorithms. Human expertise remains important for checking results and understanding cases that are difficult to classify automatically. The article therefore presents AI as a supporting technology that can complement professional geospatial workflows rather than simply replace them. The combination of 3D data, machine learning, and GIS can create new possibilities for extracting useful information from increasingly detailed digital representations of the physical environment.