2026 18th CEGIS Annual Research Meeting
June 23-25, 2026, virtual event by invitation only
June 23-25, 2026, virtual event by invitation only
Center of Excellence for Geospatial Information Science (CEGIS)
CEGIS researchers are Federal scientists in the USGS that lead collaborative research projects.
CEGIS researchers are Federal scientists in the USGS that lead collaborative research projects.
Center of Excellence for Geospatial Information Science (CEGIS)
The CEGIS vision is to conduct, lead, and influence the research and innovative solutions required by the National Spatial Data Infrastructure (NSDI) and the emerging GeoSpatial and GeoSemantic Web.
CEGIS is a virtual organization with Federal and academic affiliate scientists conducting research in support of The National Map and the Three-Dimensional Elevation Program (3DEP).
2026 18th CEGIS Annual Research Meeting
2026 18th CEGIS Annual Research Meeting
Scheduled for June 23-25, 2026, in Denver, Colorado, the 18th CEGIS Annual Research Meeting is invitation only.
We will celebrate our accomplishments, explore ongoing projects, foster collaboration for future endeavors, and entertain a broad range of presentations from researchers and their collaborators.
Research
Research
Each subject is a science theme with associated subtopics. You'll find research information, projects, images, and publications available by topic and by general search.
News
2026 USGS Center of Excellence for Geospatial Information Science (CEGIS) Annual Research Meeting
2026 USGS Center of Excellence for Geospatial Information Science (CEGIS) Annual Research Meeting
Publications
Authoritative knowledge infrastructure for GeoAI: Implications for scientific spatial data providers Authoritative knowledge infrastructure for GeoAI: Implications for scientific spatial data providers
Geospatial Artificial Intelligence (GeoAI) increasingly relies on automated analysis of authoritative geospatial data, exposing limitations in data infrastructures originally designed for simple dissemination rather than for knowledge-driven use. From the perspective of scientific spatial data providers, the challenge is enabling GeoAI responsibly while retaining semantic clarity...
Geospatial Agentic Services: A framework for interoperable geospatial intelligence Geospatial Agentic Services: A framework for interoperable geospatial intelligence
Autonomous GIS uses large language models as its reasoning core to automate spatial data collection, analysis, modeling, and visualization for solving spatial problems with minimal human intervention. Often implemented through autonomous geospatial agents that work independently or collaboratively, it represents a shift from GIS as a passive software environment requiring expert...
Linking scale-specific sinuosity to hydrogeomorphic domains in Alaska watersheds Linking scale-specific sinuosity to hydrogeomorphic domains in Alaska watersheds
River meander patterns arise from geomorphological processes influenced by climate, geology, terrain, and hydrology. These processes produce a wide spectrum of sinuous channel and meander forms, and understanding them is essential for land management practices, such as natural channel restoration (Dominguez et al., 2018), flood and erosion control, bank stabilization (U.S. Department of...
Science
2026 18th CEGIS Annual Research Meeting
The Center of Excellence for Geospatial Information Science (CEGIS) is proud to host the 2026 18th CEGIS Annual Research Meeting June 23-25, 2026, in Denver, Colorado. The annual research meeting is a special occasion to celebrate our accomplishments, explore ongoing projects, and foster collaboration for future endeavors. This year's gathering featured a broad range of presentations from our...
2025 CEGIS Annual Research Meeting
The Center of Excellence for Geospatial Information Science (CEGIS) was proud to host the 2025 CEGIS Annual Research Meeting July 22-24, 2025. The annual research meeting is a special occasion to celebrate our accomplishments, explore ongoing projects, and foster collaboration for future endeavors. This year's gathering featured a broad range of presentations from our researchers and their...
Image processing
Image processing helps us study and understand different types of landscapes. We use algorithms and software to analyze satellite and airborne images to make detailed maps of the land and its features. By using automated techniques such as feature extraction and building of 3D models, image processing helps scientists learn more about the land and how it changes over time.
