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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).

Publications

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

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

Automated deep learning-based point cloud classification on USGS 3DEP lidar data using transformer

The goal of the U.S. Geological Survey’s (USGS) 3D Elevation Program (3DEP) is to facilitate the acquisition of nationwide lidar data. Although data meet USGS lidar specifications, some point cloud tiles include noisy and incorrectly classified points. The enhanced accuracy of classified point clouds can improve support for many downstream applications such as hydrologic analysis, urban...
Authors
Jung-Kuan (Ernie) Liu, Rongjun Qin, Shuang Song

Science

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.
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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.
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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.
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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.
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Feature mapping

Feature mapping is about identifying specific elements like roads, buildings, and natural features on maps to understand landscapes better. This helps planners make decisions about development and conservation. CEGIS uses feature mapping to study how landscapes change over time, which helps them plan for things like managing forests and predicting floods.
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Feature mapping

Feature mapping is about identifying specific elements like roads, buildings, and natural features on maps to understand landscapes better. This helps planners make decisions about development and conservation. CEGIS uses feature mapping to study how landscapes change over time, which helps them plan for things like managing forests and predicting floods.
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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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