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Temporal greenness trends in stable natural land cover and relationships with climatic variability across the conterminous United States

Assessment of temporal trends in vegetation greenness and related influences aids understanding of recent change in terrestrial ecosystems and feedbacks from weather, climate, and environment. We analyzed 1-km normalized difference vegetation index (NDVI) timeseries data (1989–2016) derived from the Advanced Very High Resolution Radiometer (AVHRR) and developed growing season time-integrated NDVI
Lei Ji, Jesslyn F. Brown

Exploring VIIRS continuity with MODIS in an expedited capability for monitoring drought-related vegetation conditions

Vegetation has been effectively monitored using remote sensing time-series vegetation index (VI) data for several decades. Drought monitoring has been a common application with algorithms tuned to capturing anomalous temporal and spatial vegetation patterns. Drought stress models, such as the Vegetation Drought Response Index (VegDRI), often use VIs like the Normalized Difference Vegetation Index
Trenton D Benedict, Jesslyn F. Brown, Stephen P. Boyte, Daniel Howard, Brian Fuchs, Brian D. Wardlow, Tsegaye Tadesse, Kirk Evenson

Exploring relationships of spring green-up to moisture and temperature across Wyoming, U.S.A

Vegetation green-up signals the timing of available nutritious plants and shrubs providing high-quality forage for ungulates. In this study, we characterized spatial and temporal patterns of spring phenology and explored how they were related to preceding temperature and moisture conditions. We tested correlations between late winter weather and indicators of the onset and the length of the spring
Jesslyn F. Brown, Lei Ji, Alisa L. Gallant, Matthew Kauffman

Optimizing a remote sensing production efficiency model for macro-scale GPP and yield estimation in agroecosystems

Earth observation data are increasingly used to provide consistent eco-physiological information over large areas through time. Production efficiency models (PEMs) estimate Gross Primary Production (GPP) as a function of the fraction of photosynthetically active radiation absorbed by the canopy, which is derived from Earth observation. GPP can be summed over the growing season and adjusted by a cr
Michael Marshall, Kevin Tu, Jesslyn F. Brown

Multi-year data from satellite- and ground-based sensors show details and scale matter in assessing climate’s effects on wetland surface water, amphibians, and landscape conditions

Long-term, interdisciplinary studies of relations between climate and ecological conditions on wetland-upland landscapes have been lacking, especially studies integrated across scales meaningful for adaptive resource management. We collected data in situ at individual wetlands, and via satellite for surrounding 4-km2 landscape blocks, to assess relations between annual weather dynamics, snow durat
Walter Sadinski, Alisa L. Gallant, Mark Roth, Jesslyn F. Brown, Gabriel Senay, Wayne L. Brininger, Perry M. Jones, Jason M. Stoker

Challenges in complementing data from ground-based sensors with satellite-derived products to measure ecological changes in relation to climate – lessons from temperate wetland-upland landscapes

Assessing climate-related ecological changes across spatiotemporal scales meaningful to resource managers is challenging because no one method reliably produces essential data at both fine and broad scales. We recently confronted such challenges while integrating data from ground- and satellite-based sensors for an assessment of four wetland-rich study areas in the U.S. Midwest. We examined relati
Alisa L. Gallant, Walter J. Sadinski, Jesslyn F. Brown, Gabriel B. Senay, Mark F. Roth

Effect of NOAA satellite orbital drift on AVHRR-derived phenological metrics

The U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center routinely produces and distributes a remote sensing phenology (RSP) dataset derived from the Advanced Very High Resolution Radiometer (AVHRR) 1-km data compiled from a series of National Oceanic and Atmospheric Administration (NOAA) satellites (NOAA-11, −14, −16, −17, −18, and −19). Each NOAA satellite experien
Lei Ji, Jesslyn F. Brown

Exploring drought controls on spring phenology

The timing of spring phenology can be influenced by several drivers. Many studies have shown the effect of temperature on spring vegetation growth, but the role of moisture is complex and not as well researched. We explored drivers for aspen spring phenology in the mountains of the western U.S. While temperature exerted control over the timing of aspen green-up in the spring, snow moisture as meas
Jesslyn F. Brown, Gretchen Meier

The integration of geophysical and enhanced Moderate Resolution Imaging Spectroradiometer Normalized Difference Vegetation Index data into a rule-based, piecewise regression-tree model to estimate cheatgrass beginning of spring growth

Cheatgrass exhibits spatial and temporal phenological variability across the Great Basin as described by ecological models formed using remote sensing and other spatial data-sets. We developed a rule-based, piecewise regression-tree model trained on 99 points that used three data-sets – latitude, elevation, and start of season time based on remote sensing input data – to estimate cheatgrass beginn
Stephen P. Boyte, Bruce K. Wylie, Donald J. Major, Jesslyn F. Brown

Application-ready expedited MODIS data for operational land surface monitoring of vegetation condition

Monitoring systems benefit from high temporal frequency image data collected from the Moderate Resolution Imaging Spectroradiometer (MODIS) system. Because of near-daily global coverage, MODIS data are beneficial to applications that require timely information about vegetation condition related to drought, flooding, or fire danger. Rapid satellite data streams in operational applications have clea
Jesslyn F. Brown, Daniel M. Howard, Bruce K. Wylie, Aaron M. Friesz, Lei Ji, Carolyn Gacke

Phenology and climate relationships in aspen (Populus tremuloides Michx.) forest and woodland communities of southwestern Colorado

Trembling aspen (Populus tremuloides Michx.) occurs over wide geographical, latitudinal, elevational, and environmental gradients, making it a favorable candidate for a study of phenology and climate relationships. Aspen forests and woodlands provide numerous ecosystem services, such as high primary productivity and biodiversity, retention and storage of environmental variables (precipitation, tem
Gretchen A. Meier, Jesslyn F. Brown, Ross J. Evelsizer, James E. Vogelmann

Remote sensing of land surface phenology

Remote sensing of land-surface phenology is an important method for studying the patterns of plant and animal growth cycles. Phenological events are sensitive to climate variation; therefore phenology data provide important baseline information documenting trends in ecology and detecting the impacts of climate change on multiple scales. The USGS Remote sensing of land surface phenology program pro
G.A. Meier, Jesslyn F. Brown