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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

Landsat Next

Landsat Next's launch in the early 2030s will ensure continuity of the longest space-based record of Earth’s land surfaces. The mission will substantially increase the breadth and quality of Earth observation data available to scientists, land managers, and others responsible for managing Earth's natural resources. Landsat Next’s constellation of three satellites will carry sensors that improve bo

Monitoring polar ice change in the twilight zone

Landsat’s new extended data collection program is mapping Arctic and Antarctic regions year-round, even in polar twilight.
Theodore A. Scambos, Christopher Shuman, Mark Fahnestock, Tasha Snow, Christopher J. Crawford

Remote sensing-based 3D assessment of landslides: A review of the data, methods, and applications

Remote sensing (RS) techniques are essential for studying hazardous landslide events because they capture information and monitor sites at scale. They enable analyzing causes and impacts of ongoing events for disaster management. There has been a plethora of work in the literature mostly discussing (1) applications to detect, monitor, and predict landslides using various instruments and image anal
Hessah Albanwan, Rongjun Qin, Jung-Kuan (Ernie) Liu

Need and vision for global medium-resolution Landsat and Sentinel-2 data products

Global changes in climate and land use are threatening natural ecosystems, biodiversity, and the ecosystem services people rely on. This is why it is necessary to track and monitor spatiotemporal change at a level of detail that can inform science, management, and policy development. The current constellation of multiple Landsat and Sentinel-2 satellites collecting imagery at predominantly ≤30-m s
Volker C. Radeloff, David P. Roy, Mike Wulder, Martha Anderson, Bruce D. Cook, Christopher J. Crawford, Mark Friedl, Feng Gao, Noel Gorelick, Matthew Hansen, Sean Healey, Patrick Hostert, Glynn Hulley, Justin Huntington, Dave Johnson, Christopher Neigh, Alexei Lyapustin, Leo Lymburner, Nima Pahlevan, Jean-Francois Pekel, Theodore A. Scambos, Crystal Schaaf, Peter Strobl, Eric Vermote, Curtis Woodcock, Hankui K. Zhang, Zhe Zhu

GeoAI for spatial image processing

The development of digital image processing, as a subset of digital signal processing, depended upon the maturity of photography and image science, introduction of computers, discovery and advancement of digital recording devices, and the capture of digital images. In addition, government and industry applications in the Earth and medical sciences were paramount to the growth of the technology. Fr
Samantha Arundel, Kevin G McKeehan, Wenwen Li, Zhining Gu

At what scales does a river meander? Scale-specific sinuosity (S3) metric for quantifying stream meander size distribution

Stream bend geometry is linked to terrain features, hydrologic and ecologic conditions, and anthropogenic forces. Knowledge of the distributions of geometric properties of streams advances understanding of changing landscape conditions and associated processes that operate over a range of spatial scales. Statistical decomposition of sinuosity in natural linear features has proven a longstanding ch
Larry Stanislawski, Barry J. Kronenfeld, Barbara P. Buttenfield, Ethan J. Shavers

Space-based Earth observation and ecosystem extent: Exploring opportunities

The purpose of this white paper is to explore and communicate potential new opportunities for using space-based Earth observation (EO) for monitoring biodiversity with a focus on ecosystem extent (the distribution of ecosystems on the Earth). It is part of a new activity of the Committee on Earth Observation Satellites (CEOS), a collaboration of the world’s space agencies that facilitates cross-ag
Gary Geller, Shaun Levick, Sandra Luque, Roger Sayre, Andreas Brink, Nicholas Coops, Sylvie Durrieu, Judith Ewald, Hannes Feilhauer, Jean-Baptiste Feret, Simon Ferrier, Miroslav Honzák, Dino Lenco, Amanda Koltz, Nikhil Lele, Shea Lombardo, Miguel Mahecha, Carsten Meyer, Marc Paganini, Cassidy Rankine, Duccio Rocchini, Amy Rosenthal, Maria J. Santos, Lucie Viciano

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 data without
Samantha Arundel, Kevin G McKeehan, Bryan B Campbell, Andrew N. Bulen, Philip T. Thiem

Developing satellite-estimated precipitation monthly reports for selected locations in the Republic of the Marshall Islands

The Republic of the Marshall Islands (also known as the Marshall Islands) is a nation of more than 30 low-lying atolls and islands, most of which are inhabited, dispersed across an Exclusive Economic Zone over 770,000 square miles in the tropical central north Pacific Ocean. Monitoring environmental conditions for potential drought risk is challenging in such a dispersed island nation, and current
Gabriel B. Senay, David A. Helweg, Stefanie Kagone, John B. Taylor, Thomas Cecere, Tiare Eastmond, Amy Koch, Kurtis Nelson, Lajikit Rufus

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 hydrogeomorphic
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

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 objective metr
Barry J. Kronenfeld, Larry Stanislawski, Barbara P. Buttenfield, Ethan J. Shavers

Calibration and validation for the Surface Biology and Geology (SBG) mission concept: Recommendations for a multi-sensor system for imaging spectroscopy and thermal imagery

The primary objective of the National Aeronautics and Space Administration (NASA) Surface Biology and Geology (SBG) mission is to measure biological, physical, chemical, and mineralogical features of the Earth's surface, realizing a key conceptual component of the envisioned NASA Earth System Observatory (ESO). SBG is planned to launch as a two-platform mission in the late 2020s, the first of the
Kevin R. Turpie, Kimberly Ann Casey, Christopher J. Crawford, Liane S Guild, Hugh H. Kieffer, Guoqing (Gary) Lin, Raymond F. Kokaly, Alok Shrestha, Cody Anderson, Shankar N. Ramaseri Chandra, Robert O. Green, Simon Hook, Constantine Lukashin, Kurt Thome