This project was done for a Aggregate Intellect workshop on Earth & Environmental Data Science and in collaboration with Fynn Davis.
This project focuses on using machine learning to classify NRCAN 2015 Canada land cover using Sentinel-2 data.
This repo contains all the base testing including:
- Pipeline comparisons
- Different models
- Different extents
- Optimization
- Feature Importance
- Calculated Layers
- Normalization Techniques
Fynn Davis's repo contains:
- Prediction Maps
- Feature Selection from the image
- Filtering
- K-means clustering
- Edge Detection
- Geocoordinates
- Overlapping Model Predictions