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1858 results.

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Page 13, results 301 - 325

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Publication Extents

Not all publications have extents, not all extents are completely accurate
Isolating anthropogenic wetland loss by concurrently tracking inundation and land cover disturbance across the Mid-Atlantic Region, U.S.
Melanie K. Vanderhoof, Jay R. Christensen, Yen-Ju G. Beal, Ben DeVries, Megan W. Lang, Nora Hwang, Christine Mazzarella, John Jones
2020, Remote Sensing (12)
Global trends in wetland degradation and loss have created an urgency to monitor wetland extent, as well as track the distribution and causes of wetland loss. Satellite imagery can be used to monitor wetlands over time, but few efforts have attempted to distinguish anthropogenic wetland loss from climate-driven variability in...
Effect of spatial resolution of satellite images on estimating the greenness and evapotranspiration of urban green spaces
Hamideh Nouri, Pamela L. Nagler, Sattar Chavoshi Borujeni, Armando Barreto Munez, Sina Alaghmand, Behnaz Noori, Alejandro Galindo, Kamel Didan
2020, Hydrological Processes (34) 3183-3199
Urban green spaces (UGS), like most managed land covers, are getting progressively affected by water scarcity and drought. Preserving, restoring and expanding UGS require sustainable management of green and blue water resources to fulfil evapotranspiration (ET) demand for green plant cover. The heterogeneity of UGS with high variation in their...
Quantifying drought’s influence on moist soil seed vegetation in California’s Central Valley through time-series remote sensing
Kristin B. Byrd, Austen Lorenz, James Anderson, Cynthia Wallace, Kara Moore-O'Leary, Jennifer Isola, Ricardo Ortega, Matt Reiter
2020, Ecological Applications (30)
Californias Central Valley, USA is a critical component of the Pacific Flyway despite loss of more than 90% of its wetlands. Moist soil seed (MSS) wetland plants are now produced by mimicking seasonal flooding in managed wetlands to provide an essential food resource for waterfowl. Managers need MSS plant area...
The Landsat Burned Area algorithm and products for the conterminous United States
Todd Hawbaker, Melanie K. Vanderhoof, Gail L. Schmidt, Yen-Ju G. Beal, Joshua J. Picotte, Joshua Takacs, Jeff T. Falgout, John L. Dwyer
2020, Remote Sensing of Environment (244)
Complete and accurate burned area map data are needed to document spatial and temporal patterns of fires, to quantify their drivers, and to assess the impacts on human and natural systems. In this study, we developed the Landsat Burned Area (BA) algorithm, an update from the Landsat Burned Area Essential...
Gap fill of Land surface temperature and reflectance products in Analysis Ready Data
Qiang Zhou, George Z. Xian, Hua Shi
2020, Remote Sensing (12)
The recently released Landsat Analysis Ready Data (ARD) over the United States provides the opportunity to investigate landscape dynamics using dense time series observations at 30-m resolution. However, the dataset often contains data gaps (or missing data) because of cloud contamination or data acquisition strategy. We present a new algorithm...
Vegetation‐groundwater dynamics at a former uranium mill site following invasion of a biocontrol agent: A time series analysis of Landsat normalized difference vegetation index data
Christopher J. Jarchow, William J. Waugh, Kamel Didan, Armando Barreto-Munoz, Stefanie M. Herrmann, Pamela L. Nagler
2020, Hydrological Processes (34) 2739-2749
Because groundwater recharge in dry regions is generally low, arid and semiarid environments have been considered well‐suited for long‐term isolation of hazardous materials (e.g., radioactive waste). In these dry regions, water lost (transpired) by plants and evaporated from the soil surface, collectively termed evapotranspiration (ET), is usually the primary discharge...
Implementation of a surface water extent model in Cambodia using cloud-based remote sensing
Christopher E. Soulard, Jessica J. Walker, Roy E. Petrakis
2020, Remote Sensing (12)
Mapping surface water over time provides the spatially explicit information essential for hydroclimatic research focused on droughts and flooding. Hazard risk assessments and water management planning also rely on accurate, long-term measurements describing hydrologic fluctuations. Stream gages are a common measurement tool used to better understand flow and inundation dynamics,...
A within-season approach for detecting early crop stage of corn and soybean using high temporal and spatial resolution imagery
Feng Gao, Martha Anderson, Craig S. T. Daughtry, Arnon Karnieli, W. Dean Hively, William P. Kustas
2020, Remote Sensing of Environment (242)
Crop emergence is a critical stage for crop development and crop growth modeling. Mapping crop emergence using remote sensing data is challenging. Previous remote sensing phenology algorithms showed that crop stages could be detected around the V3-V4 (3 to 4 established leaves) vegetative stage. Traditional approaches have a strong assumption...
Conterminous United States land cover change patterns 2001–2016 from the 2016 National Land Cover Database
Collin G. Homer, Jon Dewitz, Suming Jin, George Z. Xian, Catherine Costello, Patrick Danielson, Leila Gass, Michelle Funk, James Wickham, Steven Stehman, Roger F. Auch, Kurt H. Riitters
2020, ISPRS Journal of Photogrammetry and Remote Sensing (162) 184-199
The 2016 National Land Cover Database (NLCD) product suite (available on www.mrlc.gov), includes Landsat-based, 30 m resolution products over the conterminous (CONUS) United States (U.S.) for land cover, urban imperviousness, and tree, shrub, herbaceous and bare ground fractional percentages. The release of NLCD 2016 provides important new information on land...
Quality control and assessment of interpreter consistency of annual land cover reference data in an operational national monitoring program
Bruce Pengra, Stephen V. Stehman, Josephine Horton, Daryn Dockter, Todd A. Schroeder, Zhiqiang Yang, Warren B Cohen, Sean P. Healey, Thomas Loveland
2020, Remote Sensing of Environment (238)
The U.S. Geological Survey Land Change Monitoring, Assessment and Projection (USGS LCMAP) initiative is working toward a comprehensive capability to characterize land cover and land cover change using dense Landsat time series data. A suite of products including annual land cover maps and annual land cover change maps will be...
Transitioning from change detection to monitoring with remote sensing: A paradigm shift
Curtis E. Woodcock, Thomas Loveland, Martin Herold, Marvin E. Bauer
2020, Remote Sensing of Environment (238)
The use of time series analysis with moderate resolution satellite imagery is increasingly common, particularly since the advent of freely available Landsat data. Dense time series analysis is providing new information on the timing of landscape changes, as well as improving the quality and accuracy of information being derived from...
Characterizing land surface phenology and exotic annual grasses in dryland ecosystems using Landsat and Sentinel-2 data in harmony
Neal Pastick, Devendra Dahal, Bruce K. Wylie, Sujan Parajuli, Stephen P. Boyte, Zhuoting Wu
2020, Remote Sensing (12)
Invasive annual grasses, such as cheatgrass (Bromus tectorum L.), have proliferated in dryland ecosystems of the western United States, promoting increased fire activity and reduced biodiversity that can be detrimental to socio-environmental systems. Monitoring exotic annual grass cover and dynamics over large areas requires the use of remote sensing that...
Training data selection for annual land cover classification for the LCMAP initiative
Qiang Zhou, Heather J. Tollerud, Christopher P. Barber, Kelcy Smith, Daniel J. Zelenak
2020, Remote Sensing (12)
The U.S. Geological Survey’s Land Change Monitoring, Assessment, and Projection (LCMAP) initiative characterizes changes in land cover, use, and condition with the goal of producing land change information that improves understanding of the earth system and provides insight into the impacts of land change on society. For LCMAP, all available...
Determining the drivers of suspended sediment dynamics in tidal marsh-influenced estuaries using high-resolution ocean color remote sensing
Xiaohe Zhang, Cedric Fichot, Carly Baracco, Ruizhe Guo, Sydney Neugebauer, Zachary Bengtsson, Neil K. Ganju, Sergio Fagherazzi
2020, Remote Sensing (240)
Sediment budgets are a critical metric to assess coastal marsh vulnerability to sea-level rise and declining riverine sediment inputs. However, calculating accurate sediment budgets is challenging in tidal marsh-influenced estuaries where suspended sediment concentrations (SSC) typically vary on scales of hours and meters, and where SSC dynamics are driven by...
Multi-decadal patterns of vegetation succession after tundra fire on the Yukon-Kuskokwim Delta, Alaska
Gerald Frost, Rachel A. Loehman, Lisa Saperstein, Matthew J. Macander, Peter Nelson, David Paradis, Sue M. Natali
2020, Environmental Research Letters
Alaska’s Yukon-Kuskokwim Delta (YKD) is one of the warmest parts of the Arctic tundra biome and tundra fires are common in its upland areas. Here we combine field measurements, Landsat observations, and quantitative cover maps for tundra plant functional types (PFTs) to characterize multi-decadal succession and landscape change after fire in lichen-dominated upland tundra...
Evaluation of hydrologic impact of an irrigation curtailment program in the Upper Klamath Lake Basin using Landsat satellite data
Naga Manohar Velpuri, Gabriel Senay, Matthew Schauer, C. Amanda Garcia, Ramesh Singh, MacKenzie Friedrichs, Stefanie Bohms, Jonathan V. Haynes, Terrence D. Conlon
2020, Hydrological Processes (34) 1697-1713
Upper Klamath Lake (UKL) is the source of the Klamath river that flows through southern Oregon and northern California. The UKL basin is home to two endangered species and provides water for 81,000+ ha (200,000+ acres) of irrigation on the United States Bureau of Reclamation (USBR) Klamath Project located downstream...
Quantifying western U.S. rangelands as fractional components with multi-resolution remote sensing and in situ data
Matthew Rigge, Collin Homer, Lauren Cleeves, Deb Meyer, Brett Bunde, Hua Shi, George Z. Xian, Matthew R Bobo
2020, Remote Sensing (12)
Quantifying western U.S. rangelands as a series of fractional components with remote sensing provides a new way to understand these changing ecosystems. Nine rangeland ecosystem components, including percent shrub, sagebrush (Artemisia), big sagebrush, herbaceous, annual herbaceous, litter, and bare ground cover, along with sagebrush and shrub heights, were...
Potential underestimation of satellite fire radiative power retrievals over gas flares and wildland fires
Sanath S. Kumar, John Edward Hult, Joshua J. Picotte, Birgit Peterson
2020, Remote Sensing (12)
Fire Radiative Power (FRP) is related to fire combustion rates and is used to quantify the atmospheric emissions of greenhouse gases and aerosols. FRP over gas flares and wildfires can be retrieved remotely using satellites that observe in shortwave infrared (SWIR) to middle infrared (MIR) wavelengths. Heritage techniques to retrieve...
Effect of an environmental flow on vegetation growth and health using ground and remote sensing metrics
Martha M. Gomez-Sapiens, Christopher Jarchow, Karl W. Flessa, Patrick B. Shafroth, Edward P. Glenn, Pamela L. Nagler
2020, Hydrological Processes (34) 1682-1696
Understanding the effectiveness of environmental flow deliveries along rivers requires monitoring vegetation. Monitoring data are often collected at multiple spatial scales. For riparian vegetation, optical remote sensing methods can estimate growth responses at the riparian corridor scale, and field‐based measures can quantify species composition; however, the extent to which these...
Agricultural cropland extent and areas of South Asia derived using Landsat satellite 30-m time-series big-data using random forest machine learning algorithms on the Google Earth Engine cloud
Murali Krishna Gumma, Prasad Thenkabail, Pardhasaradhi Teluguntla, Adam Oliphant
2020, GIScience and Remote Sensing (57) 302-322
The South Asia (India, Pakistan, Bangladesh, Nepal, Sri Lanka and Bhutan) has a staggering 900 million people (~43% of the population) who face food insecurity or severe food insecurity as per United Nations, Food and Agriculture Organization’s (FAO) the Food Insecurity Experience Scale (FIES). The existing coarse-resolution (>250-m) cropland maps...
Using full and partial unmixing algorithms to estimate the inundation extent of small, isolated stock ponds in an arid landscape
Christopher Jarchow, Brent H. Sigafus, Erin L. Muths, Blake R. Hossack
2020, Wetlands (40) 563-575
Many natural wetlands around the world have disappeared or been replaced, resulting in the dependence of many wildlife species on small, artificial earthen stock ponds. These ponds provide critical wildlife habitat, such that the accurate detection of water and assessment of inundation extent is required. We applied a full (linear...
Earth as art 6
U.S. Geological Survey
2019, General Information Product 194
Earth has a stunning variety of landscapes. The colors, patterns, textures, and shapes all make for intriguing artwork as seen from the perspective of space.Earth As Art shows not only what satellites capture in the visible wavelengths of light you and I can see, but also what’s hiding in the...
Validating a landsat time-series of fractional component cover across western U.S. Rangelands
Matthew B. Rigge, Collin G. Homer, Hua Shi, Debra K. Meyer
2019, Remote Sensing (11)
Western U.S. rangelands have been quantified as six fractional cover (0%–100%) components over the Landsat archive (1985–2018) at a 30 m resolution, termed the “Back-in-Time” (BIT) dataset. Robust validation through space and time is needed to quantify product accuracy. Here, we used field data collected concurrently with high-resolution satellite (HRS) images...
Overall methodology design for the United States National Land Cover Database 2016 products
Suming Jin, Collin Homer, Limin Yang, Patrick Danielson, Jon Dewitz, Congcong Li, Zhe Zhu, George Z. Xian, Danny Howard
2019, Remote Sensing (11)
The National Land Cover Database (NLCD) 2016 provides a suite of data products, including land cover and land cover change of the conterminous United States from 2001 to 2016, at two- to three-year intervals. The development of this product is part of an effort to meet the growing demand...
Phenology patterns indicate recovery trajectories of ponderosa pine forests after high-severity fires
Jessica J. Walker, Christopher E. Soulard
2019, Remote Sensing (11)
Post-fire recovery trajectories in ponderosa pine (Pinus ponderosa Laws.) forests of the US Southwest are increasingly shifting away from pre-burn vegetation communities. This study investigated whether phenological metrics derived from a multi-decade remotely sensed imagery time-series could differentiate among grass, evergreen shrub, deciduous, or conifer-dominated replacement pathways. We...