UArizona DataLab Series
When
Step out of conventional GIS frameworks and discover the latest trends in geospatial data science where open tools, cloud technologies, and the proliferation of sensor data are innovating earth observation and environmental monitoring.
Emphasizing open science and reproducible methods, this immersive hands-on workshop series will:
* Guide you through essential geospatial python libraries
* Introduce you to cloud-native formats
* Show you how to harness cloud computing platforms
* Mentor you in open-source drone imagery analysis
* Help you build geospatial analysis pipelines
Each UArizona DataLab workshop session is designed to be a discrete lesson where students will walk away with specific knowledge on a tool and resources to explore deeper. Our goal is to cover material that is not currently being taught in credited classes at UArizona. The series is open to all University of Arizona personnel and is tailored for graduate students, postdocs, and early career faculty looking to expand their geospatial skills.
Course content and more details can be found on this Workshop Wiki page.
RESOURCES AND NOTES:
Date / Topic / YouTube link
01/16/24: Geospatial Data APIs
1/23/24: Python Data Formats: Raster & Vector
1/30/24: Python Visualization Libraries
02/06/24: Intro to Cloud Native
02/13/24: Cloud Optimized Geotiffs
02/20/24: Cloud Optimized Point Clouds
02/27/24: Xarray & Zarr
03/05/24: Spring Break
03/12/24: SpatioTemporal Asset Catalogs
03/26/24: Google Earth Engine
04/02/24: Microsoft Planetary Computer
04/09/24: OpenDrone
04/16/24: Containerized Pipelines
04/23/24: Planet Satellite Imagery with Austin Stone
04/30/24: Drone Imagery Analysis: DeepForest