Introduction to Geospatial Raster and Vector Data with Python (#maptimeDavis & D-PUG)

Description: This will be a hands-on, live-coding workshop focused on teaching the fundamental geospatial python packages for working with raster and vector data. Participants will learn how to open, work with, and plot vector and raster-format spatial data in Python, as well as how to access cloud hosted datasets. Participants are encouraged to use their own computers and to ensure the proper setup of tools. Please make sure to download the data and install everything before working through this lesson. See the setup page for instructions: https://carpentries-incubator.github.io/geospatial-python/setup.html

Learning Objective: Be able to load and work with Raster and Vector spatial data in Python.

Prerequisites: It's assumed participants have exposure to Python and feel comfortable with the material taught here: https://swcarpentry.github.io/python-novice-gapminder/index.html. If participants feel less familiar with concepts like variable assignment, functions, libraries, and dataframes in python, we encourage them to run through this lesson on their own.    

Software: See setup instructions: https://carpentries-incubator.github.io/geospatial-python/setup.html     

Instructor: Ryan Avery  

Instructor Biography: Ryan is a Machine Learning Engineer at Development Seed and instructor for the Carpentries. At work he uses Python to develop machine learning models to detect land-use and land cover change in satellite imagery. He is passionate about helping organizations make sound decisions that improve environmental outcomes and livelihoods.