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CanElevation

The CanElevation repository provides comprehensive documentation, examples, and tools for working with Canadian elevation data, including LiDAR point clouds and vertical datum transformations.

Overview

This repository contains:

• Interactive Jupyter Notebooks - Step-by-step tutorials for processing elevation data
• Documentation - Comprehensive guides in both English and French
• Sample Data - Example datasets for testing and learning

Key Features

Point Cloud Processing

• Creating Digital Elevation Models (DEMs) from LiDAR data
• Working with COPC (Cloud Optimized Point Cloud) formats
• Filtering and classifying point cloud data
• Integration with QGIS for visualization

Vertical Transformations

• Converting between Canadian vertical datums (CGVD2013, CGVD28)
• Raster-based transformations
• Point cloud datum and epoch conversions

📖 Documentation

Visit our comprehensive documentation: https://nrcan.github.io/CanElevation/

Quick Start

1. Clone the repository:

   git clone https://github.com/NRCan/CanElevation.git
   cd CanElevation

2. Set up the environment:

   conda env create -n CanElevation --file docs/assets/env/environment.yml
   conda activate CanElevation

3. Launch Jupyter Notebook (Point cloud examples):

   jupyter notebook

4. Open a tutorial notebook from the docs/en/pointclouds/ or docs/fr/pointclouds/ directory

Data Sources

This repository works with Point cloud data and digital elevation models data from the CanElevation Series, which provides high-quality elevation data for Canada.

License

This project is licensed under the Open Government Licence - Canada.

Support

For questions or support:

• 📖 Check the documentation
• 🐛 Report issues on GitHub Issues