Course Overview
Students will learn how to convert overlapping, photogrammetric images into point-clouds and derive output geospatial data such as 3D models, digital surface and terrain models and orthomosaics. An overview of geo-spatial forest health metrics is provided followed by the basics of how those metrics are computed using raster multi-layer analysis in a GIS system. In the final module, students get practical, hands-on experience with analysing multi-spectral data for the purpose of forest health assessment using GIS.
Prerequisite(s)
- No prerequisites are required for this course.
Credits
1.0
- Not offered this term
- This course is not offered this term. Notify me to receive email notifications when the course opens for registration next term.
Learning Outcomes
Upon successful completion of this course, the student will be able to:
- Demonstrate the ability to process multi-spectral images to create point-clouds, DSM's and orthomosaics.
- Generate various spatial data layers suitable for the quantification of forest health.
- Identify the different types of forest health metrics.
- Describe which type of forest health metric is suitable for analysis using multi-spectral image analysis.
- Understand basics of multi-layer image analysis using QGIS.
- Demonstrate the ability to combine appropriate geo-spatial layers to create a particular forest health metric.
- Reclassify forest health metric into a forest health index map.
- Appraise the validity of forest health maps using ground truth data.
- Apply techniques to generate a multi-spectral forest health index map.
Effective as of Winter 2022
Related Programs
Cloud-based Multi-spectral Image Processing for Forest Stand Health Assessment (XRPA 1300) is offered as a part of the following programs:
School of Construction and the Environment
- Introduction to Forest Health Quantification with RPAS
Microcredential Part-time
Programs and courses are subject to change without notice. Find out more about BCIT course cancellations.