python for geospatial analysis - Analyze floods using ONLY Python! (aka spatial data science)

🚀 Ready to move beyond desktop GIS? Step into the Spatial Lab: a global community for ambitious geospatial professionals who want to break out of outdated workflows and join the top 5% of the field. 👉 Join Spatial Lab: https://forrest.nyc/spatial-lab/ 🎓 Want structured, career-changing learning? 🚀 Modern GIS Accelerator: https://forrest.nyc/accelerator/ — master Python, Spatial SQL & cloud workflows in 2 weeks 🧭 Career Compass: https://forrest.nyc/career-compass/ — fast, practical steps to land the GIS role you want 🪄 AI Copilot for GIS: https://forrest.nyc/ai-copilot-for-gis/ — learn to integrate AI into your geospatial workflows & boost your productivity 📰 Weekly modern GIS insights: https://forrest.nyc ⚡️ Spots for the next live cohort and mentorship cycle are closing soon, join now to lock in your place and momentum. Analyzing climate change and potential flooding is incredibly important as our world changes, and one way to do this is to use Python and GIS data known as digital elevation models. In this tutorial, we will create a relative elevation model, or model the data relative to the height of a body of water, in this case, the Mississippi River near Cape Girardeau, MO. 0:00 Intro 1:12 What are relative elevation models? 5:42 Downloading USGS data 8:59 Xarray, Rasterio, other libraries, and data prep 11:54 Geocode river using OSMnx 13:53 Create the river elevation model with Xarray and rioxarray 20:09 Visualize with Datashader and wrap-up Download the data in the tutorials here: ➡️ USGS DEM File: https://www.sciencebase.gov/catalog/item/63c78c1ed34e06fef14edbbd ➡️ Notebook and Files on GitHub: https://github.com/mbforr/youtube-examples 📝 Original Notebook: https://github.com/DahnJ/REM-xarray/blob/master/rem-in-xarray-tutorial.ipynb 🏞️ More info on REMs: https://dancoecarto.com/creating-rems-in-qgis-the-idw-method ✅ Check out my Notion Productivity Template here: https://mbforr.gumroad.com/l/notion-productivity Check out some other posts and resources here: Learn Spatial SQL: https://forrest.nyc/learn-spatial-sql/ 40+ Resources for Spatial SQL: https://forrest.nyc/40-spatial-sql-resources-and-guides/ 75+ Geospatial Python and Spatial Data Science Resources and Guides: https://forrest.nyc/75-geospatial-python-and-spatial-data-science-resources-and-guides/ Other courses to get started with GIS, spatial data science, and data science (affiliate links): Geographic Information Systems (GIS) Specialization from UC Davis: https://imp.i384100.net/n1Kyxo Spatial Data Science and Applications from Yonsei University: https://imp.i384100.net/9W6E6W Python for Everybody from University of Michigan: https://imp.i384100.net/BX3P31 Remote Sensing Image Acquisition, Analysis and Applications: https://imp.i384100.net/Xxe4Ay CONNECT WITH ME 📸 Instagram: https://www.instagram.com/matt_forrest/ 💼 LinkedIn: https://www.linkedin.com/in/mbforr/ 📧 Newsletter: https://forrest.nyc 🌐 Website: https://forrest.nyc #gis #hydrology #python