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Course Outline
• Introduction to remote sensing: Satellite imagery and data sources
• Importing and visualizing raster data in QGIS
• Image pre-processing: Band combinations, clipping, and reprojection
• Supervised and unsupervised image classification
• NDVI and other spectral indices for vegetation and land cover analysis
• Accuracy assessment and classification validation
• Exporting results and integration with other GIS tools
Requirements
- Completion of QGIS Beginner level or prior experience using QGIS (basic functions, working with layers, projections)
- Familiarity with raster vs vector data
- Interest or basic understanding of remote sensing concepts (e.g. satellite images, NDVI) is helpful
7 Hours
Testimonials (1)
All the topics which he covered including examples. And also explained how they are helpful in our daily job.
