Publications
Below is a list of the most recent EROS peer-reviewed scientific papers, reports, fact sheets, and other publications. You can search all our publication holdings by type, topic, year, and order.
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Filter Total Items: 2456
Radiometric calibration of the Landsat MSS sensor series
Multispectral remote sensing of the Earth using Landsat sensors was ushered on July 23, 1972, with the launch of Landsat-1. Following that success, four more Landsat satellites were launched, and each of these carried the Multispectral Scanner System (MSS). These five sensors provided the only consistent multispectral space-based imagery of the Earth's surface from 1972 to 1982. This work focuses
Authors
Dennis L. Helder, Sadhana Karki, Rajendra Bhatt, Esad Micijevik, David Aaron, Benjamin Jasinski
Landsat: building a strong future
Conceived in the 1960s, the Landsat program has experienced six successful missions that have contributed to an unprecedented 39-year record of Earth Observations that capture global land conditions and dynamics. Incremental improvements in imaging capabilities continue to improve the quality of Landsat science data, while ensuring continuity over the full instrument record. Landsats 5 and 7 are s
Authors
Thomas R. Loveland, John L. Dwyer
Future scenarios of land-use and land-cover change in the United States--the Marine West Coast Forests Ecoregion
Detecting, quantifying, and projecting historical and future changes in land use and land cover (LULC) has emerged as a core research area for the U.S. Geological Survey (USGS). Changes in LULC are important drivers of changes to biogeochemical cycles, the exchange of energy between the Earth’s surface and atmosphere, biodiversity, water quality, and climate change. To quantify the rates of recent
Authors
Tamara S. Wilson, Benjamin M. Sleeter, Terry L. Sohl, Glenn Griffith, William Acevedo, Stacie Bennett, Michelle Bouchard, Ryan R. Reker, Christy Ryan, Kristi Sayler, Rachel Sleeter, Christopher E. Soulard
Canadian SAR remote sensing for the Terrestrial Wetland Global Change Research Network (TWGCRN)
The Canada Centre for Remote Sensing (CCRS) has more than 30 years of experience investigating the use of SAR remote sensing for many applications related to terrestrial water resources. Recently, CCRS scientists began contributing to the Terrestrial Wetland Global Change Research Network (TWGCRN), a bi-national research network dedicated to assessing impacts of global change on interconnected wet
Authors
Shannon Kaya, Brian Brisco, Andrew Cull, Alisa L. Gallant, Walter J. Sadinski, Dean Thompson
Factors influencing geographic patterns in diversity of forest bird communities of eastern Connecticut, USA
At regional scales, the most important variables associated with diversity are latitudinally-based temperature and net primary productivity, although diversity is also influenced by habitat. We examined bird species richness, community density and community evenness in forests of eastern Connecticut to determine whether: 1) spatial and seasonal patterns exist in diversity, 2) energy explains the g
Authors
Robert J. Craig, Robert W. Klaver
Role of remote sensing for land-use and land-cover change modeling
No abstract available.
Authors
Terry Sohl, Benjamin Sleeter
Predator evasion by white-tailed deer fawns
Despite their importance for understanding predator–prey interactions, factors that affect predator evasion behaviours of offspring of large ungulates are poorly understood. Our objective was to characterize the influence of selection and availability of escape cover and maternal presence on predator evasion by white-tailed deer, Odocoileus virginianus, fawns in the northern Great Plains, U.S.A. W
Authors
Troy W. Grovenburg, Kevin L. Monteith, Robert W. Klaver, Jonathan A. Jenks
Land change variability and human-environment dynamics in the United States Great Plains
Land use and land cover changes have complex linkages to climate variability and change, biophysical resources, and socioeconomic driving forces. To assess these land change dynamics and their causes in the Great Plains, we compare and contrast contemporary changes across 16 ecoregions using Landsat satellite data and statistical analysis. Large-area change analysis of agricultural regions is ofte
Bias-adjusted satellite-based rainfall estimates for predicting floods: Narayani Basin
In Nepal, as the spatial distribution of rain gauges is not sufficient to provide detailed perspective on the highly varied spatial nature of rainfall, satellite-based rainfall estimates provides the opportunity for timely estimation. This paper presents the flood prediction of Narayani Basin at the Devghat hydrometric station (32 000 km2) using bias-adjusted satellite rainfall estimates and the G
Authors
Guleid A. Artan, S.A. Tokar, D.K. Gautam, S.R. Bajracharya, M.S. Shrestha
Using regional-scale pre- and post Hurricane Katrina lidar for monitoring and modeling: Chapter 30
Hurricane Katrina was one of the largest natural disasters in U.S. history. Due to the sheer
size of the affected areas, an unprecedented regional analysis at very high resolution and
accuracy was needed to properly quantify and understand the effects of the hurricane and
the storm tide. Many disparate sources of lidar data were acquired and processed for
varying environmental reasons by pre- and
Authors
Jason M. Stoker, D. Phil Turnipseed, Kenneth V. Wilson
Characterizing the performance of ecosystem models across time scales: A spectral analysis of the North American Carbon Program site‐level synthesis
[1] Ecosystem models are important tools for diagnosing the carbon cycle and projecting its behavior across space and time. Despite the fact that ecosystems respond to drivers at multiple time scales, most assessments of model performance do not discriminate different time scales. Spectral methods, such as wavelet analyses, present an alternative approach that enables the identification of the dom
Authors
Michael C. Dietze, Rodrigo Vargas, Andrew D. Richardson, Paul C. Stoy, Ryan Anderson, M. A. Arain, I. Baker, T. Andrew Black, Jing M. Chen, Philippe Ciais, Lawrence B. Flanagan, Christopher M. Gough, Robert Grant, David Hollinger, R. C. Izaurralde, C.J. Kucharik, P. Lafleur, Shuguang Liu, E. Lokupitiya, Y. Luo, J.W. Munger, Changhui Peng, Benjamin Poulter, David T. Price, D. Ricciuto, William J. Riley, A. Sahoo, Kevin Schaefer, Andrew E. Suyker, Hanqin Tian, Christina Tonitto, Hans Verbeeck, Shashi B. Verma, W. Wang, Ensheng Weng
LandsatLook images
LandsatLook images are full resolution JPEG files derived from Landsat Level 1 data products. The images are compressed and stretched to create an image optimized for image selection and visual interpretation; it is not recommended that they be used in digital analysis.
Authors