Image Georeferencing & Enhancement | Supervised Image Classification in Remote Sensing

Explore the complete workflow of Image Georeferencing, Image Enhancement, and Supervised Image Classification in this hands-on GIS and Remote Sensing tutorial. 🛰️ Learn how to align satellite imagery with real-world coordinates, improve image quality, and classify land use/land cover using supervised techniques.

Perfect for Geography, Environmental Science, GIS, and Remote Sensing students or professionals.

🔍 What You’ll Learn:

Step-by-step Image Georeferencing using Ground Control Points (GCPs)

Digital Image Enhancement (Contrast Stretching, Filtering, Histogram Equalization)

Supervised Classification using training samples

Common classification algorithms (e.g., Maximum Likelihood, SVM)

Land use/land cover mapping from satellite imagery

Tools: QGIS, ERDAS Imagine, ArcGIS

📊 Use Cases: Urban sprawl analysis, forest cover change, agriculture classification, and more.

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Image georeferencing tutorial in GIS

Supervised image classification step-by-step

How to enhance satellite images

Remote sensing classification methods

Georeferencing in QGIS and ArcGIS

Satellite image processing techniques

LULC classification using supervised methods

Image enhancement in remote sensing

Ground control points for georeferencing

Maximum likelihood classification GIS