Skip to main content

Algorithms for Geospatial Computing

College of Behavioral & Social SciencesGeographical Sciences
CreditsN/A
·
Semester offeredN/A

Description

An introduction to fundamental geospatial objects and geometric algorithms for spatio-temporal data processing and analysis. Point data representation and analysis: spatial data models and data structures, algorithms for spatial queries, point clustering algorithms. Surface and scalar field modeling, such as terrains: raster and triangle-based models (TINs), algorithms for building and querying TINs. Algorithms for natural and urban terrain analysis: morphology computation and visibility analysis. Applications to processing and analysis of LiDAR (Light Detection And Ranging) data in the context of terrain reconstruction, urban modeling, forest management and bathymetry reconstruction for coastal data management. Road network computation and analysis: algorithms for route computation in road networks, and for road network reconstruction from GPS and satellite data. Prerequisite: GEOG276; or a minimum grade of C- in

Course outline
Checking availability…

Preview the 5 closest equivalencies already indexed in our system

GEOG 470 has possible credit equivalents including GEOG202 at McGill University.

CourseUniversityQwest Score
GEOG202
Statistics and Spatial Analysis
McGill University69
GEOG314
Geospatial Analysis
McGill University69