| Dates | Sept. 3 - October 29, 2024 |
| When | Tuesdays 2-3 pm Arizona Time |
| Where | Weaver Science-Engineering Library Room 212 & Zoom |
| [Registration] | [Zoom] |
| Feeback Form |
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 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 U of A.
The series is FREE and open to all University of Arizona personnel and is tailored for graduate students, postdocs, and early career faculty looking to expand their geospatial skills.
The series is expert-led by educators at the University of Arizona Data Science Institute and Cyverse.
Jeffrey Gillan Ph.D, is a research data scientist with Cyverse and has 15 years of experience in geospatial science. He has expertise in drone-based photogrammetry, LiDAR, and hyperspectral image analysis.
Carlos Lizarraga Ph.D, is a computation and data science educator at The UA Data Science Institute.
We welcome students and professionals from any field of study across the university. A variety of skill levels are also welcome, though each lesson will assume the audience has limited experience on the topic. Basic knowledge of scripting languages (python/R), some prior geospatial experience, and familiarity with command line tools will be helpful. We will be doing gentle live coding during the sessions. Please bring you laptop computer if you plan on attending in-person. Specific software installations and login requirements will be posted for each lesson.
In addition to the live workshops, all of the lesson content will be openly available in the Github repository wiki https://github.com/ua-datalab/Geospatial_Workshops/wiki
| Date | Topic |
|---|---|
| 09/03/24 | Cyverse Geospatial |
| 09/10/24 | Google Earth Engine |
| 09/17/24 | Microsoft Planetary Computer |
| 09/24/24 | Cloud Native Formats: COGs & COPC |
| 10/01/24 | Cloud Native Formats: Zarr & FlatGeoBuf |
| 10/08/24 | DeepForest & Detecto |
| 10/15/24 | Geospatial Pipelines |
| 10/22/24 | SpatioTemporal Asset Catalogs (STAC) |
| 10/29/24 | Geospatial APIs |
| Date | Topic |
|---|---|
| 01/16/24 | Geospatial Data APIs |
| 01/23/24 | Python Data Formats: Raster & Vector |
| 01/30/24 | 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 | Intro to Zarr & Xarray |
| 03/05/24 | Spring break |
| 03/12/24 | SpatioTemporal Asset Catalogs |
| 03/19/24 | |
| 03/26/24 | Google Earth Engine |
| 04/02/24 | Microsoft Planetary Computer |
| 04/09/24 | |
| 04/16/24 | Containerized Pipelines |
| 04/23/24 | Planet Satellite Imagery with Austin Stone |
| 04/30/24 | Drone Image Analysis - Deep Forest |
UArizona DataLab, Data Science Institute, University of Arizona, 2023.
