Course Outline
• Foundations of remote sensing: Exploring satellite imagery and data sources
• Techniques for importing and visualizing raster data within QGIS
• Image pre-processing workflows: Band combinations, spatial clipping, and reprojection
• Implementing supervised and unsupervised image classification methods
• Analyzing vegetation and land cover using NDVI and other spectral indices
• Evaluating accuracy and validating classification results
• Exporting final outputs and integrating findings with other GIS tools
Requirements
- Completion of the QGIS Beginner course or equivalent prior experience with QGIS fundamentals, including basic functions, layer management, and projections
- Working knowledge of the distinctions between raster and vector data
- A basic understanding of or interest in remote sensing principles, such as satellite imaging and NDVI, is advantageous
Testimonials (1)
Learning that the QGIS and a tool that can used by other different professionals such land survey
