Filters: partyWithName: Earth Resources Observation and Science (EROS) Center (X) > partyWithName: Stephen P Boyte (X)
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High interannual variability of forage production in semi-arid grasslands leads to uncertainties when livestock producers make decisions such as buying additional feed, relocating animals, or using flexible stocking. Within-season predictions of annual forage production (i.e., yearly production) can provide specific boundaries for producers to make these decisions with more information and possibly with higher confidence. We use a recently developed forage production model, ForageAhead, that uses environmental and seasonal climate variables to estimate the annual forage production approximated by remotely sensed vegetation data. The model uses observed seasonal climate data from winter and spring as an input together...
Integrating spatially explicit biogeophysical and remotely sensed data into regression-tree models enables the spatial extrapolation of training data over large geographic spaces, enhancing a more complete understanding of broad-scale ecosystem processes. This data release presents maps of estimates of annual gross primary production (GPP) and annual ecosystem respiration (RE) that were derived from weekly summaries of gross photosynthesis (Pg) and ecosytem respiration (Re). To conduct this study we used carbon data from flux towers that are scattered strategically across the conterminous United States (CONUS). We also calculate and present a map of average annual net ecosystem production (NEP). We present and analyze...
Phenological dynamics of terrestrial ecosystems reflect the response of the Earth's vegetation canopy to changes in climate and hydrology and are thus important to monitor operationally. The Exotic Annual Grass (EAG) phenology in the western U.S. rangeland based on 30m near seamless Harmonized Landsat and Sentinel-2 (HLS) Normalized Difference Vegetation Index (NDVI) weekly composites between 2016 and 2021 (Dahal et al., 2022) were processed using these 3 methods: (1) NDVI threshold-based method, (2) manual phenological metrics, and (3) modeling and mapping. The EAG phenology model produced two metrics identifying the sustainable growth characteristics of 16 EAG species throughout level III Commission for Environmental...
Phenological dynamics of terrestrial ecosystems reflect the response of the Earth's vegetation canopy to changes in climate and hydrology and are thus important to monitor operationally. Researchers at the U.S. Geological Survey (USGS), Earth Resources Observation and Science (EROS) Center have developed methods for documenting the seasonal dynamics of vegetation in an operational fashion from satellite time-series data. The USGS made the decision to develop 2023 CONUS phenology metrics using S-NPP Visible Infrared Imaging Radiometer Suite (VIIRS) because of the decommissioning of Aqua C6 MODIS sensor in the near future. The readily available and consistently processed smoothed EROS VIIRS (eVIIRS) maximum Normalized...
Phenological dynamics of terrestrial ecosystems reflect the response of the Earth's vegetation canopy to changes in climate and hydrology and are thus important to monitor operationally. Researchers at the U.S. Geological Survey (USGS), Earth Resources Observation and Science (EROS) Center have developed methods for documenting the seasonal dynamics of vegetation in an operational fashion from satellite time-series data. The phenological metrics data produced at USGS EROS provide indicators of key phenological events for the conterminous United States on a yearly basis based on Collection 6 Aqua eMODIS NDVI input data (for the 2003 - 2020 metrics). As the objective is to monitor the phenological dynamics of the...
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