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Publications

The CEGIS publications page is our one-stop collection of all publications from CEGIS authors, past and present.

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Filter Total Items: 181

Reimagining standardization and geospatial interoperability in today’s GeoAI culture Reimagining standardization and geospatial interoperability in today’s GeoAI culture

Integrating Geospatial Artificial Intelligence (GeoAI) into our technological landscape has revolutionized our capacity to understand and engage with the world. However, the burgeoning adoption of GeoAI applications has underscored the imperative of data, format, and conveyance standardization and enhancing geospatial interoperability. This vision paper delves into the intricacies of the...
Authors
Samantha T. Arundel, Wenwen Li, Bryan B Campbell

A guide to creating an effective big data management framework A guide to creating an effective big data management framework

Many agencies and organizations, such as the U.S. Geological Survey, handle massive geospatial datasets and their auxiliary data and are thus faced with challenges in storing data and ingesting it, transferring it between internal programs, and egressing it to external entities. As a result, these agencies and organizations may inadvertently devote unnecessary time and money to convey...
Authors
Samantha T. Arundel, Kevin G. McKeehan, Bryan B Campbell, Andrew N. Bulen, Philip T. Thiem

Transferring deep learning models for hydrographic feature extraction from IfSAR data in Alaska Transferring deep learning models for hydrographic feature extraction from IfSAR data in Alaska

The National Hydrography Dataset (NHD) managed by the U.S. Geological Survey (USGS) is being updated with higher-quality feature representations through efforts that derive hydrography from 3DEP HR elevation datasets. Deriving hydrography from elevation through traditional flow routing and interactive methods is a complex, time-consuming process that must be tailored for different...
Authors
Larry V. Stanislawski, Nattapon Jaroenchai, Shaowen Wang, Ethan J. Shavers, Alexander Duffy, Philip T. Thiem, Zhe Jiang, Adam Camerer

Generalization quality metrics to support multiscale mapping: Hausdorff and average distance between polylines Generalization quality metrics to support multiscale mapping: Hausdorff and average distance between polylines

Large geospatial datasets must often be generalized for analysis and display at reduced scales. Automated methods including artificial intelligence and deep learning are being applied to this problem, but the results are often analyzed on the basis of limited and subjective measures. To better support automation, a project is underway to develop a robust Python toolkit for computing...
Authors
Barry J. Kronenfeld, Lawrence V. Stanislawski, Barbara P. Buttenfield, Ethan J. Shavers

Automated mapping of culverts, bridges, and dams Automated mapping of culverts, bridges, and dams

Accurate maps of built structures around stream channels, such as dams, culverts, and bridges, are vital in monitoring infrastructure, risk management, and hydrologic modeling. Hydrologic modeling is essential for research and decisionmaking related to infrastructure and development planning, emergency management, ecology, and developing hydrographic data. Technological advances in...
Authors
Ethan J. Shavers, Lawrence V. Stanislawski, Joel Schott, Zachary Brosseau

Geomorphometric analysis of the Summit and Ridge classes of the Geographic Names Information System Geomorphometric analysis of the Summit and Ridge classes of the Geographic Names Information System

This research aims to conduct a geosemantic comparison of landforms classified in the Summit and Ridge feature classes in the Geographic Names Information System (GNIS). The comparison is based on a 2D shape analysis of manually delineated polygons produced by USGS staff to correspond to 33,304 Summit and 8,006 Ridge features. Five shape measures were chosen for this specific...
Authors
Gaurav Sinha, Samantha T. Arundel, Romim Somadder, David P. Martin, Kevin G. McKeehan

A 5500-year record of coastal dune evolution along the shores of Lake Michigan in the North American Great Lakes: The relationship of lake-level fluctuations and climate A 5500-year record of coastal dune evolution along the shores of Lake Michigan in the North American Great Lakes: The relationship of lake-level fluctuations and climate

Dune fields line much of the ∼1750-km long shore of Lake Michigan that extends from northwestern Indiana, north along the west coast of Lower Michigan, and west across southern Upper Michigan. Numerous geomorphic studies at specific sites or defined coastal reaches have demonstrated that dune formation began during the Nipissing maximum (∼5500–4500 calendar year Before Present (cal yr BP...
Authors
Alan F. Arbogast, William A. Lovis, Kevin G. McKeehan, G. William Monaghan

The geography and progression of blowouts in the coastal dunes along the eastern shore of Lake Michigan since 1938 The geography and progression of blowouts in the coastal dunes along the eastern shore of Lake Michigan since 1938

Coastal dunes along Lake Michigan's eastern shoreline are a unique system comprising perhaps the largest complex of freshwater coastal dunes in the world. Here, we examine the blowouts in this region and determine how they have evolved since the 1930s. We conducted a spatiotemporal analysis of 435 blowouts by comparing repeat aerial images of the coast beginning in 1938. Using an...
Authors
Kevin G. McKeehan, Alan F. Arbogast

GeoImageNet: A multi-source natural feature benchmark dataset for GeoAI and supervised machine learning GeoImageNet: A multi-source natural feature benchmark dataset for GeoAI and supervised machine learning

The field of GeoAI or Geospatial Artificial Intelligence has undergone rapid development since 2017. It has been widely applied to address environmental and social science problems, from understanding climate change to tracking the spread of infectious disease. A foundational task in advancing GeoAI research is the creation of open, benchmark datasets to train and evaluate the...
Authors
Wenwen Li, Sizhe Wang, Samantha T. Arundel, Chia-Yu Hsu

Open knowledge network roadmap: Powering the next data revolution Open knowledge network roadmap: Powering the next data revolution

Open access to shared information is essential for the development and evolution of artificial intelligence (AI) and AI-powered solutions needed to address the complex challenges facing the nation and the world. The Open Knowledge Network (OKN), an interconnected network of knowledge graphs, would provide an essential public-data infrastructure for enabling an AI-driven future. It would...
Authors
Chaitan Baru, Martin Halbert, Lara Campbell, Tess DeBlanc-Knowles, Jemin George, Wo Chang, Adam Pah, Douglas Maughan, Ilya Zaslavsky, Amanda Stathopoulos, Ellie Young, Kat Albrecht, Amit Sheth, Emanuel Sallinger, Katerine Osatuke, Angela Rizk-Jackson, Eric Jahn, Kenneth Berkowitz, Bandana Kar, Erica Smith, Krzystof Janowicz, Brian Handspicker, Esther Jackson, Lauren Sanders, Chengkai Li, Florence Hudson, Lilit Yeghiazarian, Cogan Shimizu, Glenn Ricart, Louiqa Raschid, Dalia E. Varanka, Greg Seaton, Luis Amaral, Oktie Hassanzadeh, Silviu Cucerzan, Matt Bishop, Ora Lassila, Sharat Israni, Matthew Lange, Pascal Hitzler, Ryan McGranaghan, Michael Cafarella, Paul Wormeli, Todd Bacastow, Sam Klein, Murat Omay, Sergio Baranzini, Ying Ding, Nariman Ammar
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