Remote Sensing Phenology Active
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.
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.
Below are multimedia items associated with this project.
Below are publications associated with this project.
Remote sensing of land surface phenology
Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982-2006
A five-year analysis of MODIS NDVI and NDWI for grassland drought assessment over the central Great Plains of the United States
A 16-year time series of 1 km AVHRR satellite data of the conterminous United States and Alaska
Trend analysis of time-series phenology of North America derived from satellite data
Trend analysis of time-series phenology derived from satellite data
Issues in characterizing phenology from satellite observations
Assessing satellite-derived start-of-season measures in the conterminous USA
Interactive visualization of vegetation dynamics
A weighted least-squares approach to temporal NDVI smoothing
Measuring phenological variability from satellite imagery
- Overview
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.
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.
- Multimedia
Below are multimedia items associated with this project.
- Publications
Below are publications associated with this project.
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 proAuthorsG.A. Meier, Jesslyn F. BrownFilter Total Items: 23Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982-2006
Shifts in the timing of spring phenology are a central feature of global change research. Long-term observations of plant phenology have been used to track vegetation responses to climate variability but are often limited to particular species and locations and may not represent synoptic patterns. Satellite remote sensing is instead used for continental to global monitoring. Although numerous methAuthorsM.A. White, K. M. de Beurs, K. Didan, D.W. Inouye, A.D. Richardson, O.P. Jensen, J. O'Keefe, G. Zhang, R.R. Nemani, Leeuwen van, Jesslyn F. Brown, A. de Wit, M. Schaepman, X. Lin, M. Dettinger, A.S. Bailey, J. Kimball, M.D. Schwartz, D. D. Baldocchi, J.T. Lee, W.K. LauenrothA five-year analysis of MODIS NDVI and NDWI for grassland drought assessment over the central Great Plains of the United States
A five-year (2001–2005) history of moderate resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) data was analyzed for grassland drought assessment within the central United States, specifically for the Flint Hills of Kansas and Oklahoma. Initial results show strong relationships among NDVI, NDWI, and drought conditAuthorsYingxin Gu, Jesslyn F. Brown, J. P. Verdin, B. WardlowA 16-year time series of 1 km AVHRR satellite data of the conterminous United States and Alaska
The U.S. Geological Survey (USGS) has developed a 16-year time series of vegetation condition information for the conterminous United States and Alaska using 1 km Advanced Very High Resolution Radiometer (AVHRR) data. The AVHRR data have been processed using consistent methods that account for radiometric variability due to calibration uncertainty, the effects of the atmosphere on surface radiometAuthorsJeff EidenshinkTrend analysis of time-series phenology of North America derived from satellite data
Remote sensing information has been used in studies of the seasonal dynamics (phenology) of the land surface since the 1980s. While our understanding of remote sensing phenology is still in development, it is regarded as a key to understanding land-surface processes over large areas. Phenologic metrics, including start of season, end of season, duration of season, and seasonally integrated greenneAuthorsB. C. ReedTrend analysis of time-series phenology derived from satellite data
Remote sensing information has been used in studies of the seasonal dynamics (phenology) of the land surface for the past 15 years. While our understanding of remote sensing phenology is still in development, it is regarded as a key to understanding land surface processes over large areas. Repeat observations from satellite-borne multispectral sensors provide a mechanism to move from plant-specifiAuthorsB. C. Reed, Jesslyn F. BrownIssues in characterizing phenology from satellite observations
Over the past decade, many investigators have published techniques for deriving phenological parameters, especially the start of the growing season (SOS), from time-series satellite imagery. The principal satellite sensor for these studies is the advanced very high resolution radiometer (AVHRR). This study investigates the characteristics of four of the primary methods for identifying SOS; maximumAuthorsB. C. Reed, J.F. BrownAssessing satellite-derived start-of-season measures in the conterminous USA
National Oceanic and Atmospheric Administration (NOAA)-series satellites, carrying advanced very high-resolution radiometer (AVHRR) sensors, have allowed moderate resolution (1 km) measurements of the normalized difference vegetation index (NDVI) to be collected from the Earth's land surfaces for over 20 years. Across the conterminous USA, a readily accessible and decade-long data set is now avaiAuthorsMark D. Schwartz, Bradley C. Reed, Michael A. WhiteInteractive visualization of vegetation dynamics
Satellite imagery provides a mechanism for observing seasonal dynamics of the landscape that have implications for near real-time monitoring of agriculture, forest, and range resources. This study illustrates a technique for visualizing timely information on key events during the growing season (e.g., onset, peak, duration, and end of growing season), as well as the status of the current growing sAuthorsB. C. Reed, D. Swets, L. Bard, J. Brown, James RowlandA weighted least-squares approach to temporal NDVI smoothing
Satellite imagery provides a unique vantage point for observing seasonal dynamics of the landscape that have implications for global change issues. An objective evaluation of surface conditions may be performed using the normalized difference vegetation index (NDVI) derived from National Oceanic and Atmospheric Administration advanced very high resolution radiometer data. NDVI data are typically vAuthorsD. Swets, Bradley C. Reed, James Rowland, S.E. MarkoMeasuring phenological variability from satellite imagery
Vegetation phenological phenomena are closely related to seasonal dynamics of the lower atmosphere and are therefore important elements in global models and vegetation monitoring. Normalized difference vegetation index (NDVI) data derived from the National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer (AVHRR) satellite sensor offer a means of efficiently and obAuthorsBradley C. Reed, Jesslyn F. Brown, D. Vanderzee, Thomas R. Loveland, James W. Merchant, Donald O. Ohlen