GEOG 470/770/CMSC 401: Algorithms for Geospatial Computing
Usually offered in the Spring semester
Course Description:
- Introduction to fundamental geometric algorithms for spatio- temporal data processing and analysis.
- Managing and clustering point clouds for processing and analysis of LiDAR data.
- Terrain modeling: representations, query algorithms, visibility and morphological analysis.
- Applications: terrain reconstruction, urban modeling, forest management and coastal data management and analysis
- Algorithms for road network analysis and reconstruction.
- Scalable algorithms and representations for big geospatial data.
Course Learning Objectives
Upon a successful completion of the course the students will be able to:
- Acquire in-depth knowledge of fundamentals of algorithms for geospatial data science.
- Learn techniques for efficiently encoding, manipulating and querying geospatial data.
- Gain substantial understanding of how geospatial data are actually processed in modern geographical information systems. •
- Learn how to design, use and implement algorithms dealing with geospatial data, with emphasis on point data processing and analysis, on terrain modeling and on road network analysis.
- Apply algorithms for discrete and continuous geospatial data to LiDAR data processing and analysis, and algorithms for road network routing and reconstruction to real-world data sets
- Learn how to use open-source software to solve geospatial data analysis problems