Course Outline
• Foundations of remote sensing: Exploring satellite imagery and data sources
• Techniques for importing and visualizing raster data in QGIS
• Image pre-processing methods: Band combinations, clipping, and reprojection
• Performing supervised and unsupervised image classification
• Utilizing NDVI and other spectral indices for vegetation and land cover assessment
• Evaluating classification accuracy and validating results
• Exporting outputs and integrating them with other GIS tools
Requirements
- Completion of the QGIS Beginner course or equivalent hands-on experience with QGIS (including basic functions, layer management, and projections)
- Working knowledge of the differences between raster and vector data
- A foundational understanding or keen interest in remote sensing concepts, such as satellite imagery and NDVI
Testimonials (1)
Learning that the QGIS and a tool that can used by other different professionals such land survey
