GIS Day at Colorado State University 2025
GIS Day: GIS Day: AI Applications in GIS
To help us plan for food, registration is kindly requested. Register here >>
Date: Tuesday, November 18
Location: CSU Morgan Library (Room 173)
Lunch & Networking: 12:00 PM – 1:00 PM
Presentations: 1:00 PM – 4:00 PM (30 min each including Q&A)
12:00 – 1:00 PM | Lunch & Networking
Join us for lunch and informal networking before the presentations begin.
1:00 – 1:30 PM | Morgan Garner — PlanIT Geoᵀᴹ
Rooted in Data: AI and Innovations in Canopy Assessments
Discover how AI and GIS are transforming urban forest assessments. Learn how machine-learning models classify trees and land cover to create high-resolution canopy data that supports urban planning and environmental studies.
1:30 – 2:00 PM | Katherine Moore Powell
AI & ML for Precipitation Classification
Mountain Rain and Snow (MRoS), combining citizen-submitted observations with remote-sensing data to improve models predicting rain, snow, or mixed precipitation in mountainous regions. Includes comparisons of neural networks, random forests, and XGBoost.
2:00 – 2:30 PM | Katherine Haynes — CIRA (CSU)
Utilizing AI for creating synthetic imagery and nowcasts to aid in weather forecasting
This talk explores three deep learning applications advancing weather forecasting using geostationary satellite data. From generating 10-minute synthetic imagery for tropical cyclones to producing short-term cloud nowcasts and predicting oceanic wave heights, these AI approaches enhance forecast accuracy and timeliness.
2:30 – 3:00 PM | Sarah Gaulke — Fish, Wildlife & Conservation Biology (CSU)
Getting the Bands Back Together: 100 Years of Bat Banding Data
Using AI-based optical character recognition to digitize over 100,000 bat banding records, revealing new insights into bat movement, population dynamics, and conservation implications across North America.
3:00 – 3:30 PM | Kevin Worthington — Geospatial Centroid (CSU)
From Manual Entry to Machine Intelligence: Automating Surf Zone Fatality Tracking with LLMs
A Python + LLM workflow that automatically extracts surf-zone fatality information from news articles, produces GIS shapefiles, and publishes feature services to NOAA’s ArcGIS Online — reducing manual entry and improving consistency.
3:30 – 4:00 PM | Austin Stone & Terry Giles — Esri
GeoAI and AI Assistants within the Esri Ecosystem