2: Vector Spatial Data with Python

Due before 9am on April 20

10 points

1. Create a public GitHub repository called gisc605-lab2 in your GitHub account using github/codespaces-jupyter as a template repository: https://github.com/github/codespaces-jupyter

2. Open your repository in a GitHub Codespace

3. In the integrated terminal, use pip to install some dependencies for the lab exercise

   pip install geopandas earthpy

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

   1. Introduction to Vector Format Spatial Data: intro_to_vector.ipynb

   2. Intro to Coordinate Reference Systems in Python: intro_to_crs.ipynb

   3. Geographic vs projected coordinate reference systems: geo_vs_proj.ipynb

   4. Understand EPSG, WKT and Other CRS Definition Styles: epsg.ipynb

   5. Reproject Vector Data: reproject.ipynb

   6. Clip a spatial vector layer in Python using Shapely & GeoPandas: clip_vector.ipynb

   7. How to Dissolve Polygons Using Geopandas: dissolve_polygons.ipynb

   8. How to Join Attributes From One Shapefile to Another: join_attributes.ipynb

   9. Handle missing spatial attribute data: missing_data.ipynb

5. After completing each sub-lesson, make sure to commit the changes to your repository

6. Once you are complete with all the lesson notebooks, navigate to Lab 2 assignment in Canvas

7. Input the url of your gisc605-lab2 GitHub repository then click submit