S-NPP 375-m eVIIRS Remote Sensing Phenology Metrics - across the conterminous U.S. (Ver. 2.0, August 2024)

Dates

Publication Date: 2023-08-03
Start Date: 2022-12-27
End Date: 2023-12-25
Revision: 2024-08-30

Citation

Benedict, T.D., and Boyte, S.P., 2023, S-NPP 375-m eVIIRS Remote Sensing Phenology Metrics - across the conterminous U.S. (Ver. 2.0, August 2024): U.S. Geological Survey data release, http://doi.org/10.5066/P9PZTNBI.

Summary

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 Difference Vegetation [...]

Summary

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 Difference Vegetation Index (NDVI) weekly composites are the key input for the phenological metrics data. The weighted least-square approach for temporal smoothing (Swets et. al., 1999) was adopted for the NDVI time series to eliminate anomalously low vegetation index values and reduce time shifts caused by overgeneralization of the NDVI signal. This approach uses a moving temporal window to calculate a family of regression lines that are associated with each observation; the family of lines is then averaged at each point and interpolated between points to provide a continuous temporal NDVI signal. While interpolating values between points, a weighting factor is applied that favors peak (high value) points over valley points. Smoothed NDVI data were stacked in an ascending three year 156 NDVI composite file (52 NDVI composites per year). The three years include the previous year and the following year (e.g., 2023 phenology metrics included 2022, 2023, and 2024 smoothed NDVI). In instances where the full 52 composites are not achieved, an average for each remaining weekly composite from the processed year and three previous years are used to fill those composites in the latter year to reach 156 composites (to fill 2024, composites from years 2021, 2022, and 2023 were averaged).

The smoothed NDVI data were subsequently ingested into a model developed in the Interactive Data Language (IDL) to quantify following phenological events: Start of Season Time (SOST); Start of Season NDVI (SOSN); End of Season Time (EOST); End of Season NDVI (EOSN); Maximum Time (MAXT); Maximum NDVI (MAXN); Duration (DUR); Amplitude (AMP); and Time Integrated NDVI (TIN).

Note:
S-NPP 375m eVIIRS Phenology Metrics CONUS 2021 Publication Date: 2022-08-25
S-NPP 375m eVIIRS Phenology Metrics CONUS 2022 Publication Date: 2023-08-03
S-NPP 375m eVIIRS Phenology Metrics CONUS 2023 Publication Date: 2024-08-30

For details about the algorithms and the data scaling for each of these seasonal phenological metrics, refer to the data creation process section of this metadata.

References:
Swets, D. L., Reed, B. C., Rowland, J. R., and S. E. Marko, 1999, "A Weighted Least-squares Approach to Temporal Smoothing of NDVI," In Proceedings of the 1999 ASPRS Annual Conference, from Image to Information, Portland, Oregon, May 17-21, 1999, Bethesda, Maryland, American Society for Photogrammetry and Remote Sensing, CD-ROM, 1 disc.

First release: 2023

Revised: August 2024 (ver. 2.0)

Contacts

Point of Contact :: Trenton (Contractor) D Benedict
Process Contact :: Trenton (Contractor) D Benedict
Originator :: Trenton (Contractor) D Benedict, Stephen P Boyte
Metadata Contact :: Trenton (Contractor) D Benedict
Publisher :: U.S. Geological Survey
USGS Mission Area :: Core Science Systems
SDC Data Owner :: Earth Resources Observation and Science (EROS) Center
Distributor :: U.S. Geological Survey - ScienceBase

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2023_eVIIRS_375m_conus_metadata.xml Original FGDC Metadata	View	34.65 KB	application/fgdc+xml
S-NPP_375m_eVIIRS _Phenology_Metrics_CONUS_2021.zip		363.58 MB	application/zip
S-NPP_375m_eVIIRS_CONUS_SOST_2021.png		2.59 MB	image/png
S-NPP_375m_eVIIRS _Phenology_Metrics_CONUS_2022.zip		377.83 MB	application/zip
RevisionHistory_v2.txt		788 Bytes	text/plain
S-NPP_375m_eVIIRS _Phenology_Metrics_CONUS_2023.zip		391.33 MB	application/zip

Related External Resources

Type: Online Link

Web Link	http://phenology.cr.usgs.gov
Web Link	http://earthexplorer.usgs.gov
Web Link	http://dx.doi.org/10.5066/F7PC30G1

Purpose

The goal of this project is to provide USGS and other researchers with complete and consistent public domain information on the vegetation phenology across the conterminous U.S. at a 375-m spatial resolution.

S-NPP 375-m eVIIRS Remote Sensing Phenology Metrics - across the conterminous U.S. (Ver. 2.0, August 2024)

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