GIS 401 Introduction to LiDAR Remote Sensing and Applications: The aim of this course is to combine vector and raster GIS data and new remotely sensed data source, LiDAR, with geospatial tools to make spatial decisions. Students will master basic skills of LiDAR needed to leverage the commercial LiDAR sources and information products in a broad range of applications, including vegetation characterization, 3D modeling of urban infrastructure, volumetric analysis for underground parking garage excavation and wetland boundary delineation. Further, students will be given a brief introduction to Open Source software for LiDAR data processing.
Prerequisites: GIS 302
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standard statementCourse Details| Total number of weeks | 7.5 |
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| Total Credits | |
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| Total Hours | 45 |
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Typical hours per week breakdown| Lecture | 6 |
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Outcomes
Upon successful completion of this course, the learner will be able to:
- infer the principles of LiDAR remote sensing including different sensors and platforms;
- compare different coordinate systems – horizontal and vertical datum;
- download data from Open Data Catalogues of different provinces in Canada and familiar with their metadata;
- convert industry specialized file formats to ArcGIS compatible formats using Open Source software (laszip);
- describe basic steps for visualizing, quality checking and analyzing LiDAR data using Open Source software (FugroViewer and Fusion);
- derive 3D surfaces – Digital Elevation Models (DEM), Digital Surface Models (DSM), canopy height models, Triangular Irregular Network (TIN) and Terrain datasets;
- integrate vector and raster data with LiDAR; and
- apply acquired knowledge and critical thinking skills to solve real-world problems with appropriate LiDAR data processing and analysis methods.
Grading Table
Academic and Career
See the Academic Calendar for General Information including how to withdraw from course(s) and other regulations.
Disclaimer
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