Remote Sensing Phenology
Science Center Objects
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.
Phenology tracks nature’s seasonal life cycles in relation to climate and land change. EROS is at the forefront of remotely-sensed phenology.(Credit: Sarah Scott, USGS. Public domain.)
A Longstanding Tradition
Phenology is not a new science. The Chinese are credited with keeping the first written phenological records, which date back to nearly 1000 BC. In Japan, accounts of when cherry tree blossoms were at their peak each year have been maintained for the last twelve centuries. Swedish botanist Carolus Linnaeus and British landowner Robert Marsham both kept precise and systematic phenological records in the 1700s. Their work did much to shape modern phenological observations, which are today aided by internet technology. In the United Kingdom, for example, Nature's Calendar integrates over two million seasonal change sightings made by adults and schoolchildren each year. The USA National Phenology Network brings together citizen scientists, government agencies, educators and others to monitor the impacts of climate change on plants and animals across the U.S.
Remote Sensing Phenology - A Unique Perspective
Remote sensing phenology—the use of satellites to track phenological events—complements ground observation networks. Satellites provide a unique perspective of the planet and allow for regular, even daily, monitoring of the entire global land surface.
Because the most frequently used satellite sensors for monitoring phenological events have relatively large "footprints" on the land surface, they gather data about entire ecosystems or regions rather than individual species. Remote sensing phenology can reveal
broad-scale phenological trends that would be difficult, if not impossible, to detect from the ground. And, because data collection by satellite sensors can be standardized, the data are reliably objective. Remotely sensed phenological data are useful for assessing crop conditions, drought severity, and wildfire risk as well as tracking invasive species, infectious diseases, and insect pests. Because phenological events are sensitive to climate variation, these data also represent a powerful tool for documenting phenological trends over time and detecting the impacts of climate change on ecosystems at multiple scales.
For more information, visit the USGS Remote Sensing Phenology page.
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Year Published: 2014Remote 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...
Meier, G.A.; Brown, Jesslyn F.Attribution: Earth Resources Observation and Science (EROS) Center, Earth Resources Observation and Science Center, United States of America, Remote Sensing PhenologyView CitationRemote sensing of land surface phenology; 2014; FS; 2014-3052; Meier, G. A.; Brown, J. F.
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 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. 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. 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...
Gallant, Alisa L.; Sadinski, Walter J.; Brown, Jesslyn F.; Senay, Gabriel B.; Roth, Mark F. 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, −...
Ji, Lei; Brown, Jesslyn F. 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...
Brown, Jesslyn F.; Howard, Daniel M.; Wylie, Bruce K.; Friesz, Aaron M.; Ji, Lei; Gacke, Carolyn 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...
Hayes, M.; Trnka, M.; Brown, Jesslyn F.; Meier, Gretchen 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...
Boyte, Stephen P.; Wylie, Bruce K.; Major, Donald J.; Brown, Jesslyn F. 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...
Meier, Gretchen A.; Brown, Jesslyn F.; Evelsizer, Ross J.; Vogelmann, James E. 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...
Meier, G.A.; Brown, Jesslyn F. Variability and trends in irrigated and non-irrigated croplands in the central U.S
Over 23 million hectares (233 thousand km2) of U.S. croplands are irrigated and there was an overall net expansion of 522 thousand hectares nationally from 2002 to 2007. Most of this expansion occurred across the High Plains Aquifer (HPA) in the central Great Plains. Until recently, there has been a lack of geospatially-detailed irrigation data...
Brown, Jesslyn F.; Pervez, Md Shahriar Phenological classification of the United States: A geographic framework for extending multi-sensor time-series data
This study introduces a new geographic framework, phenological classification, for the conterminous United States based on Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) time-series data and a digital elevation model. The resulting pheno-class map is comprised of 40 pheno-classes, each having...
Gu, Yingxin; Brown, Jesslyn F.; Miura, Tomoaki; van Leeuwen, Willem J.D.; Reed, Bradley C.-
Date published: June 22, 2018AVHRR Orbital Drift Data
A USGS EROS-led study concluded that NOAA satellite orbital drift increased the solar zenith angle (SZA), and in turn, influenced the phenological metrics. Eliminating the years with high SZA greatly reduced the influence of orbital drift on the Remote Sensing Phenology time-series. Read the full publication.
Users of these...
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Date published: June 22, 2018
Temporally Smoothed Weekly AQUA C6 Moderate MODIS NDVI data - 250m
The Temporally Smoothed Weekly AQUA C6 Moderate MODIS NDVI data were developed to provide researchers an analysis ready NDVI dataset, at a spatial resolution of 250 meters, suitable for time series analysis applications and research. Click here to learn more.
Users of these NDVI data sets should cite this DOI:...
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Date published: June 22, 2018C5 Terra Eastern U.S. 250 m eMODIS Remote Sensing Phenology Data
Historical remote sensing phenology (RSP) image data and graphics for the conterminous U.S. are made freely available from the USGS/EROS Center through this website. Five data sets are distributed: CONUS 1 km AVHRR RSP data, C5 Eastern CONUS 250 m eMODIS RSP data, C6 Eastern CONUS 250 m eMODIS RSP data, C5 Western CONUS 250 m eMODIS RSP data, and C6 Western CONUS 250 m eMODIS RSP data.
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Date published: June 22, 2018C5 Terra Western U.S. 250 m eMODIS Remote Sensing Phenology Data
Historical remote sensing phenology (RSP) image data and graphics for the conterminous U.S. are made freely available from the USGS/EROS Center through this website. Five data sets are distributed: CONUS 1 km AVHRR RSP data, C5 Eastern CONUS 250 m eMODIS RSP data, C6 Eastern CONUS 250 m eMODIS RSP data, C5 Western CONUS 250 m eMODIS RSP data, and C6 Western CONUS 250 m eMODIS RSP data.
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Date published: June 22, 2018Conterminous U.S. 1 km AVHRR Remote Sensing Phenology Data
Historical remote sensing phenology (RSP) image data and graphics for the conterminous U.S. are made freely available from the USGS/EROS Center through this website. Five data sets are distributed: CONUS 1 km AVHRR RSP data, C5 Eastern CONUS 250 m eMODIS RSP data, C6 Eastern CONUS 250 m eMODIS RSP data, C5 Western CONUS 250 m eMODIS RSP data, and C6 Western CONUS 250 m eMODIS RSP data.
Getting Started with MODIS Version 6 Vegetation Indices Data Part 3
This video focuses on the National Aeronautics and Space Administration’s (NASA) Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Version 6 Vegetation Indices data distributed by NASA’s Land Processes Distributed Active Archive Center (LP DAAC). Information about MODIS Vegetation Indices quality information, including how to decode quality bits, tools
Getting Started with MODIS Version 6 Vegetation Indices Data Part 2
This video focuses on the National Aeronautics and Space Administration’s (NASA) Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Version 6 Vegetation Indices data distributed by NASA’s Land Processes Distributed Active Archive Center (LP DAAC). Information about MODIS Vegetation Indices quality information, including how to decode quality bits, tools
Getting Started with MODIS Version 6 Vegetation Indices Data Part 1
This video focuses on the National Aeronautics and Space Administration’s (NASA) Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Version 6 Vegetation Indices data distributed by NASA’s Land Processes Distributed Active Archive Center (LP DAAC). Information about the MODIS Version 6 Vegetation Indices products, changes between the Version 5 and Version
AVHRR Remote Sensing Phenology Start of 2013 Season Graphic
AVHRR Phenology Start of Season graphic for 2013.
Watching spring arrive at EROS
A slideshow of photographs of volunteers at the U.S. Geological Survey Earth Resources Observation and Science (EROS) Center documenting the arrival of spring in 2014.
eMODIS Remote Sensing Phenology - Start of Season for 2001
Western region eMODIS Phenology Start of Season for 2001.
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Date published: September 20, 2017
Remote Sensing Phenology Metrics Released
Scientists with the Remote Sensing Phenology program at the U.S. Geological Survey Earth Resources Observation and Science (EROS) Center release data on seasonal life cycles on an annual basis.