Building an open and collaborative geospatial community depends on creating opportunities to share emerging technologies, interoperable tools, and practical workflows. This session brings together participants of all experience levels to explore new approaches to analysis and data access while encouraging collaboration and idea sharing. Speakers and developers will showcase community-focused tools through approachable demonstrations designed to provide attendees with resources they can immediately apply in their own work. Pre-managed environments such as Google Colab will be used to share live coding examples, web tools, and other resources.
PresentersXiaohua Pan: “AI-Powered Coding: An Atmospheric Scientist’s Journey with ChatGSFC”
Ethan Shavers: "S3 Software for Scale-Specific Sinuosity Analysis"
Abstract: This presentation showcases three open-source tools developed by the U.S. Geological Survey’s Center of Excellence for Geospatial Information Science (CEGIS) that advance geospatial analysis through artificial intelligence, geomorphic characterization, and high-resolution elevation data processing. First, we introduce a GeoAI application that employs transformer-based models to enhance lidar point cloud classification, improving feature differentiation and supporting more efficient downstream geospatial workflows. We also highlight a workflow for surface water feature extraction in Alaska that integrates radar derived elevation and reflectance data to improve the detection of hydrologic features in challenging environments. In addition, we present a new open-source implementation of the Scale Specific Sinuosity (S3) tool, designed to quantify stream bend geometry and its contribution to overall planform sinuosity. These tools demonstrate how open-source approaches can strengthen the reproducibility and scalability of geospatial analysis. The tools are developed for Linux systems, and the code can be accessed through the CEGIS GitLab repository: https://code.usgs.gov/ngtoc-cegis.AudienceGeospatial scientists, educators, students, and data providers interested in learning about newer geospatial tools, workflows, and data formats; open to coding and learning new software
