Course Outline
• Foundations of remote sensing: Sources of satellite imagery and data
• Procedures for importing and visualizing raster data within QGIS
• Image pre-processing techniques: Combining bands, clipping areas, and reprojecting data
• Methods for both supervised and unsupervised image classification
• Utilizing NDVI and other spectral indices for vegetation health and land cover studies
• Evaluating accuracy and validating classification results
• Exporting final results and integrating them with other GIS tools
Requirements
- Completion of the QGIS Beginner level course or equivalent prior experience with QGIS, including basic functions, layer management, and projections.
- Understanding of the differences between raster and vector data.
- A foundational interest in or understanding of remote sensing concepts, such as satellite imagery and NDVI, is beneficial.
Testimonials (1)
Learning that the QGIS and a tool that can used by other different professionals such land survey
