Course Outline
• Fundamentals of remote sensing: Exploring satellite imagery and data origins
• Procedures for importing and displaying raster datasets in QGIS
• Pre-processing workflows: Managing band combinations, clipping, and reprojection
• Methods for performing both supervised and unsupervised image classification
• Utilizing NDVI and other spectral indices for vegetation health and land cover assessment
• Evaluating accuracy and validating classification outcomes
• Exporting analysis results and integrating them with other GIS platforms
Requirements
- Completion of the QGIS Beginner course or equivalent proficiency in core QGIS functions, such as layer management and projections
- Understanding the distinctions between raster and vector data
- A foundational grasp of remote sensing principles, including satellite imagery and metrics like NDVI
Testimonials (1)
Learning that the QGIS and a tool that can used by other different professionals such land survey
