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 learning detection and recognition of spot elevations on historic topographic maps
Some information contained in historical topographic maps has yet to be captured digitally, which limits the ability to automatically query such data. For example, U.S. Geological Survey’s historical topographic map collection (HTMC) displays millions of spot elevations at locations that were carefully chosen to best represent the terrain at the time. Although research has attempted to reproduce t
Authors
Samantha Arundel, Trenton P. Morgan, Philip T. Thiem
Conterminous United States land-cover change (1985-2016): New insights from annual time series
Sample-based estimates augmented by complete coverage land-cover maps were used to estimate area and describe patterns of annual land-cover change across the conterminous United States (CONUS) between 1985 and 2016. Most of the CONUS land cover remained stable in terms of net class change over this time, but a substantial gross change dynamic was captured by the annual and cumulative time interval
Authors
Roger F. Auch, Danika Fay Wellington, Janis L. Taylor, Stephen V. Stehman, Heather J. Tollerud, Jesslyn F. Brown, Thomas Loveland, Bruce Pengra, Josephine Horton, Zhe Zhu, Alemayehu Midekisa, Kristi Sayler, George Z. Xian, Christopher Barnes, Ryan R. Reker
Colorado and Landsat
Colorado’s geography seems designed to impress. Although the Rocky Mountains takes up only one-half of the State, more than 50 of its peaks rise at least 14,000 feet above sea level—far more “fourteeners” than any other State. Many of these mountains receive hundreds of inches of snow annually. The Rocky Mountains provide the Continental Divide, or watershed boundary, for North America. Three of t
Authors
Weakly supervised spatial deep learning for Earth image segmentation based on imperfect polyline labels
In recent years, deep learning has achieved tremendous success in image segmentation for computer vision applications. The performance of these models heavily relies on the availability of large-scale high-quality training labels (e.g., PASCAL VOC 2012). Unfortunately, such large-scale high-quality training data are often unavailable in many real-world spatial or spatiotemporal problems in earth s
Authors
Zhe Jiang, Wenchong He, M. S. Kirby, Arpan Man Sainju, Shaowen Wang, Larry Stanislawski, Ethan J. Shavers, E. Lynn Usery
Monitoring and characterizing multi-decadal variations of urban thermal condition using time-series thermal remote sensing and dynamic land cover data
Urban development and associated land cover and land use change alter the thermal, hydrological, and physical properties of the land surface. Assessments of surface urban heat island (UHI) usually focused on using remote sensing and land cover data to quantify UHI intensity and spatial distribution within a certain period. However, the mechanisms and complex interactions in landscape dynamics and
Authors
George Z. Xian, Hua Shi, Qiang Zhou, Roger F. Auch, Kevin Gallo, Zhuoting Wu, Michael Kolian
A global ecological classification of coastal segment units to complement marine biodiversity observation network assessments
A new data layer provides Coastal and Marine Ecological Classification Standard (CMECS) labels for global coastal segments at 1 km or shorter resolution. These characteristics are summarized for six US Marine Biodiversity Observation Network (MBON) sites and one MBON Pole to Pole of the Americas site in Argentina. The global coastlines CMECS classifications were produced from a partitioning of a 3
Authors
Roger Sayre, Kevin Butler, Keith Van Graafeiland, Sean Breyer, Dawn Wright, Charlie Frye, Deniz Karagulle, Madeline T. Martin, Jill Janene Cress, Tom Allen, Rebecca Allee, Rost Parsons, Bjorn Nyberg, Mark Costello, Peter Harris, Frank Muller-Karger
Mapping world terrestrial ecosystems - GIS and cartographic approaches
No abstract available.
Authors
Roger Sayre, Madeline T. Martin, Deniz Karagulle, Charlie Frye, Timothy Boucher, Nicholas Wolff
The evolution of geospatial reasoning, analytics, and modeling
The field of geospatial analytics and modeling has a long history coinciding with the physical and cultural evolution of humans. This history is analyzed relative to the four scientific paradigms: (1) empirical analysis through description, (2) theoretical explorations using models and generalizations, (3) simulating complex phenomena and (4) data exploration. Correlations among developments in ge
Authors
Samantha Arundel, Wenwen Li
Validation of the U.S. Geological Survey’s Land Change Monitoring, Assessment and Projection (LCMAP) collection 1.0 annual land cover products 1985–2017
The U.S. Geological Survey Land Change Monitoring, Assessment and Projection (USGS LCMAP) has released a suite of annual land cover and land cover change products for the conterminous United States (CONUS). The accuracy of these products was assessed using an independently collected land cover reference sample dataset produced by analysts interpreting Landsat data, high-resolution aerial photograp
Authors
Stephen V. Stehman, Bruce Pengra, Josephine Horton, Danika F. Wellington
Earth's coastlines
With approximately half the world’s population living less than 65 miles from the ocean, coastal ecosystems are arguably Earth’s most critical real estate. Yet coastlines are among the more difficult features to accurately map; until now, no comprehensive high-resolution geospatial dataset existed. This chapter presents a new map and ecological inventory of global coastlines developed by Esri, the
Authors
Roger Sayre, Madeline T. Martin, Jill Janene Cress, Kevin Butler, Keith Van Graafeiland, Sean Breyer, Dawn Wright, Charlie Frye, Deniz Karagulle, Tom Allen, Rebecca Allee, Rost Parsons, Bjorn Nyberg, Mark J. Costello, Frank Muller-Karger, Peter Harris
Extensibility of U-net neural network model for hydrographic feature extraction and implications for hydrologic modeling
Accurate maps of regional surface water features are integral for advancing ecologic, atmospheric and land development studies. The only comprehensive surface water feature map of Alaska is the National Hydrography Dataset (NHD). NHD features are often digitized representations of historic topographic map blue lines and may be outdated. Here we test deep learning methods to automatically extract s
Authors
Larry V. Stanislawski, Ethan J. Shavers, Shaowen Wang, Zhe Jiang, E. Lynn Usery, Evan Moak, Alexander Duffy, Joel Schott
Watersheds and drainage networks
This topic is an overview of basic concepts about how the distribution of water on the Earth, with specific regard to watersheds, stream and river networks, and waterbodies are represented by geographic data. The flowing and non-flowing bodies of water on the earth’s surface vary in extent largely due to seasonal and annual changes in climate and precipitation. Consequently, modeling the detailed
Authors
Larry Stanislawski, Ethan J. Shavers