Introduction to Spatial Raster Data in Open Source Python
Welcome to Week 12!
Welcome to Week 12 of the Earth Analytics Bootcamp course! This week, you will write
Python code in
Jupyter Notebook to work with spatial raster data.
After completing the lessons for Week 12, you will be able to:
- Open and plot raster data using xarray in Python
- Crop raster data using rioxarray
- Manually classify raster data
- Perform basic raster math
Homework & Readings
Click here to view the GitHub Repo with the assignment template.
Earth Data Science Textbook Readings
Please read the following chapters of the Intermediate to Earth Data Science online textbook to support completing this week’s assignment:
Please read and watch the following chapters in the of the Intermediate Earth Data Science online textbook to support completing this week’s assignment:
Example Homework Plots
Below are example versions of the plots you will create for your homework.
# HW plot 6 # PLOT 3: pre/post DTM difference raster histogram bins = [-15, -5, -2, 0, 2, 5, 15] diff_dtm = post_dtm_xr_cl - pre_dtm_xr_cl diff_dsm = post_dsm_xr_cl - pre_dsm_xr_cl f, (ax1, ax2) = plt.subplots(2, 1, figsize=(10, 10), sharey=True) diff_dtm.plot.hist(bins=bins, ax=ax1) ax1.set(title="DTM Difference Histogram") diff_dsm.plot.hist(bins=bins, ax=ax2) ax2.set(title="DSM Difference Histogram") plt.show()