Implementation of Database-Supported Analysis for Spatio-Temporal Digital Terrain Models

Abstract. Digital Terrain Models (DTMs) have consistently been a focus of research in a wide range of fields that require observation and analysis of Earth's surface elevation. However, spatio-temporal changes of DTMs are particularly important as they can provide critical insights into phenomena such as natural hazards and urban development. Analysing these spatio-temporal changes in DTMs usually involves large volumes of data. Therefore, a geodatabase is essential for organizing and managing theses DTM datasets, enabling spatio-temporal retrieval for subsequent analysis. The exemplary implementation of analytical methods for spatio-temporal DTM datasets is the key focus of this paper. We present an event-based time-stamping data model for the management of spatio-temporal DTMs. We also conduct regional statistical analysis across different regions as well as elevation change analysis within the same region over time. Various resampling algorithms are described to harmonize different resolutions of DTMs for elevation change analysis. Finally, we visualize the results of our spatio-temporal analysis in the web-based environment. In the future, further research will also integrate AI methods to enhance spatio-temporal analysis of big DTM datasets.