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2025 CEGIS Annual Research Meeting

July 22-24, 2025, virtual event by invitation only

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Center of Excellence for Geospatial Information Science (CEGIS)

CEGIS researchers are Federal scientists in the USGS that lead collaborative research projects.

Research

Explore CEGIS science themes

Explore science

Science theme topics

Each topic is part of a broader science theme for you to explore

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Completed projects

Peruse through completed projects

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Publications

Explore CEGIS publications

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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).

2025 CEGIS Annual Research Meeting

Scheduled for July 22-24, 2025, the virtual calendar event is hosted by the USGS Community for Data Integration (CDI) in collaboration with CEGIS and 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.

See the agenda

Research

Image Collage of Landsat, pollinator, and volcanologist

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.

Explore science

Completed projects

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Peruse through completed projects

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Publications

Transfer learning with convolutional neural networks for hydrological streamline delineation Transfer learning with convolutional neural networks for hydrological streamline delineation

Hydrological streamline delineation is critical for effective environmental management, influencing agriculture sustainability, river dynamics, watershed planning, and more. This study develops a novel approach to combining transfer learning with convolutional neural networks that capitalize on image-based pre-trained models to improve the accuracy and transferability of streamline...
Authors
Nattapon Jaroenchai, Shaowen Wang, Larry Stanislawski, Ethan J. Shavers, Zhe Jiang, Vasit Sagan, E. Lynn Usery
By
Core Science Systems Mission Area, Center of Excellence for Geospatial Information Science (CEGIS)

GeoAI for science and the science of GeoAI GeoAI for science and the science of GeoAI

This paper reviews trends in GeoAI research and discusses cutting-edge ad- vances in GeoAI and its roles in accelerating environmental and social sciences. It ad- dresses ongoing attempts to improve the predictability of GeoAI models and recent re- search aimed at increasing model explainability and reproducibility to ensure trustworthy geospatial findings. The paper also provides...
Authors
Wenwen Li, Samantha Arundel, Song Gao, Michael F. Goodchild, Yingjie Hu, Shaowen Wang, Alexander Zipf
By
Core Science Systems Mission Area, Center of Excellence for Geospatial Information Science (CEGIS)

Grammar To Graph, an approach for semantic transformation of annotations to triples Grammar To Graph, an approach for semantic transformation of annotations to triples

Linguistic representation of geographic knowledge is semantically complex and particularly challenging when employing geographic information technology to automate interpreted analysis dealing with unstructured knowledge. This study describes an approach called GrammarToGraph (G2G) that applies dependency grammar rules through natural language processing to transform annotation data into...
Authors
Dalia E. Varanka, Emily Abbott
By
Core Science Systems Mission Area, Center of Excellence for Geospatial Information Science (CEGIS)
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Science

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2025 CEGIS Annual Research Meeting

The Center of Excellence for Geospatial Information Science (CEGIS) is proud to host the 2025 U.S. Geological Survey’s Center of Excellence for Geospatial Information Science (CEGIS) Annual Research Meeting July 22-24, 2025. The virtual calendar event is being hosted by the USGS Community for Data Integration (CDI) in collaboration with CEGIS and is invitation only. The annual research meeting is...
By
Core Science Systems Mission Area, National Geospatial Program, Center of Excellence for Geospatial Information Science (CEGIS), 3D Elevation Program, 3D Hydrography Program, 3D National Topography Model, National Geospatial Technical Operations Center
2025 CEGIS Annual Research Meeting

2025 CEGIS Annual Research Meeting

The Center of Excellence for Geospatial Information Science (CEGIS) is proud to host the 2025 U.S. Geological Survey’s Center of Excellence for Geospatial Information Science (CEGIS) Annual Research Meeting July 22-24, 2025. The virtual calendar event is being hosted by the USGS Community for Data Integration (CDI) in collaboration with CEGIS and is invitation only. The annual research meeting is...
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3D National Topography Model Graphic Slide

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.
By
Center of Excellence for Geospatial Information Science (CEGIS)
Image processing

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.
Learn More
Elevation derived hydrography example

Hydrography/hypsography integration

Hydrography/Hypsography integration, aka Hydro/hypso, involves combining information about water (hydro) and elevation (hypso) to study how water moves across different landscapes. It helps scientists understand where water flows, accumulates, and how it shapes the land. This helps scientists figure out how to manage water resources and predict flooding or erosion.
By
Center of Excellence for Geospatial Information Science (CEGIS)
Hydrography/hypsography integration

Hydrography/hypsography integration

Hydrography/Hypsography integration, aka Hydro/hypso, involves combining information about water (hydro) and elevation (hypso) to study how water moves across different landscapes. It helps scientists understand where water flows, accumulates, and how it shapes the land. This helps scientists figure out how to manage water resources and predict flooding or erosion.
Learn More
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Multimedia

Overhead image of blue water features with a hilly terrain in the background.
3D Hydrography Program Product Specification
3D Hydrography Program Product Specification
Screenshot of automatically generated terrain objects. See description for details.
Automatically generated terrain objects
Automatically generated terrain objects
Lidar-derived digital elevation model and NHD stream lines
Lidar-derived digital elevation model and NHD stream lines
Lidar-derived digital elevation model and NHD stream lines
Screenshot of lidar-derived digital surface elevation models of a stream channel
Lidar-derived digital surface and elevation models of a stream channel
Lidar-derived digital surface and elevation models of a stream channel
100m resolution elevation model with hydro
100m resolution elevation model with hydro
100m resolution elevation model with hydro
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