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Publications

Here you will find publications, reports and articles produced by Core Science System scientists. For a comprehensive listing of all USGS publications please click the button below.

Filter Total Items: 249

Deep convolutional neural networks for map-type classification

Maps are an important medium that enable people to comprehensively understand the configuration of cultural activities and natural elements over different times and places. Although a massive number of maps are available in the digital era, how to effectively and accurately locate and access the desired map on the Internet remains a challenge today. Previous works partially related to map-type cla
Authors
Xiran Zhou, Wenwen Li, Samantha Arundel, Jun Liu

Streams do work: Measuring the work of low-order streams on the landscape using point clouds

The mutable nature of low-order streams makes regular updating of surface water maps necessary for accurate representation. Low-order streams make up roughly half the streams in the conterminous United States by length, and small inaccuracies in stream head location can result in significant error in stream reach, order, and density. Reliable maps of stream features are vital for hydrologic modeli
Authors
Ethan J. Shavers, Larry V. Stanislawski

Community for Data Integration fiscal year 2017 funded project report

The U.S. Geological Survey Community for Data Integration annually funds small projects focusing on data integration for interdisciplinary research, innovative data management, and demonstration of new technologies. This report provides a summary of the 11 projects funded in fiscal year 2017, outlining their goals, activities, and outputs.
Authors
Leslie Hsu, Kate E. Allstadt, Tara M. Bell, Erin E. Boydston, Richard A. Erickson, A. Lance Everette, Erika Lentz, Jeff Peters, Brian Reichert, Sarah Nagorsen, Jason T. Sherba, Richard P. Signell, Mark T. Wiltermuth, John A. Young

Validating the use of object-based image analysis to map commonly-recognized landform features in the United States

The U.S. Geological Survey (USGS) National Geospatial Program (NGP) seeks to i) create semantically-accessible terrain features from the pixel-based 3D Elevation Program (3DEP) data, and ii) enhance the usability of the USGS Geographic Names Information System (GNIS) by associating boundaries with GNIS features whose spatial representation is currently limited to 2D point locations. Geographic obj
Authors
Samantha Arundel, Gaurav Sinha

Automated road breaching to enhance extraction of natural drainage networks from elevation models through deep learning

High-resolution (HR) digital elevation models (DEMs), such as those at resolutions of 1 and 3 meters, have increasingly become more widely available, along with lidar point cloud data. In a natural environment, a detailed surface water drainage network can be extracted from a HR DEM using flow-direction and flow-accumulation modeling. However, elevation details captured in HR DEMs, such as roads a
Authors
Larry Stanislawski, Tyler Brockmeyer, Ethan J. Shavers

Area-preserving simplification of polygon features

Developing simplified representations of a two-dimensional polyline is an important problem in cartographic data analytics where datasets must be integrated across spatial resolutions. This problem is generally referred to as line simplification, and is increasingly driven by preservation of specific analytic properties such as positional accuracy and high-frequency detail. However, the distinctio
Authors
Barry J. Kronenfeld, Larry V. Stanislawski, Tyler Brockmeyer, Barbara P. Buttenfield

Similarity assessment of linear hydrographic features using high performance computing

This work discusses a current open source implementation of a line similarity assessment workflow to compare elevation-derived drainage lines with the high-resolution National Hydrography Dataset (NHD) surface-water flow network. The process identifies matching and mismatching lines in each dataset to help focus subsequent validation procedures to areas of the NHD that more critically need updates
Authors
Larry V. Stanislawski, Jeffrey Wendel, Ethan J. Shavers, Ting Li

Classifying physiographic regimes on terrain and hydrologic factors for adaptive generalization of stream networks

Automated generalization software must accommodate multi-scale representations of hydrographic networks across a variety of geographic landscapes, because scale-related hydrography differences are known to vary in different physical conditions. While generalization algorithms have been tailored to specific regions and landscape conditions by several researchers in recent years, the selection and c
Authors
Larry V. Stanislawski, Michael P. Finn, Barbara P. Buttenfield

A new high-resolution map of world mountains and an online tool for visualizing and comparing characterizations of global mountain distributions

Answers to the seemingly straightforward questions “what is a mountain?” and “where are the mountains of the world?” are in fact quite complex, and there have been few attempts to map the mountains of the earth in a consistent and rigorous fashion. However, knowing exactly where mountain ecosystems are distributed on the planet is a precursor to conserving them, as called for in Sustainable Develo
Authors
Roger Sayre, Charlie Frye, Deniz Karagulle, Jürg Krauer, Sean Breyer, Peter Aniello, Dawn J. Wright, Davnah Payne, Carolina Adler, Harumi Warner, D. Paco Van Sistine, Jill Janene Cress

Monitoring mountains in a changing world: New horizons for the Global Network for Observations and Information on Mountain Environments (GEO-GNOME)

Mountains are globally distributed environments that provide significant societal benefits, a function that is increasingly compromised by climatic change, environmental stress, political and socioeconomic transformations, and unsustainable use of natural resources. Gaps in our understanding of these processes and their interactions limit our capacity to inform decisions, where both generalities o
Authors
Carolina Adler, Elisa Palazzi, Aino Kulonen, Jörg Balsiger, Guido Colangeli, Douglas Cripe, Nathan Forsythe, Grace Goss-Durant, Yaniss Guigoz, Jürg Krauer, Davnah Payne, Nicholas Pepin, Manuel Peralvo, José Romero, Roger Sayre, Maria Shahgedanova, Rolf Weingartner, Marc Zebisch

Stratifying ocean sampling globally and with depth to account for environmental variability

With increasing depth, the ocean is less sampled for physical, chemical and biological variables. Using the Global Marine Environmental Datasets (GMED) and Ecological Marine Units (EMUs), we show that spatial variation in environmental variables decreases with depth. This is also the case over temporal scales because seasonal change, surface weather conditions, and biological activity are highest
Authors
Mark John Costello, Zeenatul Basher, Roger Sayre, Sean P. Breyer, Dawn J. Wright

Temporal evaluation of estrogenic endocrine disruption markers in smallmouth bass (Micropterus dolomieu) reveals seasonal variability in intersex

A reconnaissance project completed in 2009 identified intersex and elevated plasma vitellogenin in male smallmouth bass inhabiting the Missisquoi River, VT. In an attempt to identify the presence and seasonality of putative endocrine disrupting chemicals or other factors associated with these observations, a comprehensive reevaluation was conducted between September 2012 and June 2014. Here, we co
Authors
Luke R. Iwanowicz, A.E. Pinkney, C.P. Guy, A.M. Major, K. Munney, Vicki S. Blazer, David Alvarez, Heather L. Walsh, Adam J. Sperry, Lakyn R. Sanders, D. R. Smith