Remote Sensing Phenology

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Phenology is the study of plant and animal life cycles in relation to the seasons. EROS maintains a set of nine annual phenological metrics for the conterminous United States, all curated from satellite data. Taken together, the metrics represent a powerful tool for documenting life cycle trends and the impacts of climate change on ecosystems.

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Remote Sensing Phenology uses satellites to track seasonal changes in vegetation on regional, continental, and global scales.

Overview

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Historical remote sensing phenology (RSP) image data and graphics for the conterminous U.S. are made freely available from the USGS/EROS Center.

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News

Date published: September 28, 2021

Remote Sensing Phenology Metrics for 2020 Released

The 2020 Remote Sensing Phenology Metrics have been released. This suite of phenology metrics was
derived from time-series Collection 6 Aqua eMODIS Normalized Difference Vegetation Index (NDVI) data.

Date published: April 16, 2021

Remote Sensing Phenology Metrics for 2019 Released

The 2019 Remote Sensing Phenology Metrics have been released. This suite of phenology metrics was
derived from time-series Collection 6 Aqua eMODIS Normalized Difference Vegetation Index (NDVI) data.

Date published: August 6, 2019

Remote Sensing Phenology Metrics for 2018 Released

The 2018 Remote Sensing Phenology Metrics have been released. This suite of phenology metrics was
derived from time-series Collection 6 Aqua eMODIS Normalized Difference Vegetation Index (NDVI) data.

Publications

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Year Published: 2019

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...

Brown, Jesslyn F.; Ji, Lei; Gallant, Alisa L.; Kauffman, Matthew

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Year Published: 2018

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....

Marshall, Michael; Tu, Kevin; Brown, Jesslyn F.

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Year Published: 2018

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...

Sadinski, Walter; Gallant, Alisa L.; Roth, Mark; Brown, Jesslyn F.; Senay, Gabriel; Brininger, Wayne L.; Jones, Perry M.; Stoker, Jason M.
Sadinski, W., Gallant, A.L., Roth, M., Brown, J., Senay, G., Brininger, W., Jones, P.M., Stoker, J. 2018. 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. PLoS ONE. 13(9):e0201951. DOI: 10.1371/journal.pone.0201951.