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). 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.