6: Spectral indices with Python

Due before 11:59pm on May 18

10 points

1. Create a GitHub repository called gisc606-lab6 in your GitHub account using github/codespaces-jupyter as a template repository

2. Open your repository in a GitHub Codespace

3. Create a Jupyter Notebook for and complete each of the following lessons from Earth Lab CU Boulder's Intermediate Earth Data Science textbook

   1. An Overview of the Cold Springs Wildfire: coldsprings_overview.ipynb

   2. Field Methods to Study Wildfire: field_methods.ipynb

   3. Remote Sensing to Study Wildfire: remote_sensing.ipynb

   4. Work with MODIS Remote Sensing Data using Open Source Python: modis.ipynb

   5. Find and Download MODIS Data From the USGS Earth Explorer Website: get_modis.ipynb

   6. Calculate Vegetation Indices in Python: veg_indices.ipynb

   7. Calculate NDVI Using NAIP Remote Sensing Data: ndvi.ipynb

   8. Calculate and Plot Difference Normalized Burn Ratio (dNBR) using Landsat 8 data: nbr.ipynb

4. Commit the changes to your repository

5. Once you are complete with all the lesson notebooks, navigate to Lab 6 assignment in Canvas

6. Input the url of your gisc606-lab6 GitHub repository then click submit