Flipping through field notebooks…
This dataset represents an estimate of interannual variability in the day of year (i.e. , "Julian Day") of the onset of the seasonal snowpack. Specifically these are estimates of the last day of bare ground derived from long-term time-series of Landsat TM, ETM, and OLI imagery starting in 1993. To facilitate computation of snow cover duration, day of year is scaled from January 1st of the following year. This means that negative values represent days before January 1st. For example, a snow onset on November 11th, 2021 (Day of Year 315) would be represented in the 2022 map with a value of -50 (315 - 365). These maps combine monthly ground snow cover fraction maps from the USGS Landsat Collection 2 Level 3 fSCA Statistics (https://doi.org/10.5066/F7VQ31ZQ), with a time-series analysis of a spectral snow index (NDSI) using a heirarchical Bayesian model (Gao et al. 2021). The combination of these two approaches allows reconstruction of detailed annual snow persistence maps from sparse imagery time-series (Landsat data have an 8 to 16-day return interval in the absence of clouds). A comparison of these data to independent in-situ observations from SNOTEL and microclimate sensors show that these products capture about 85% of spatial variation in snow persistence for recent years (2021-2022), and greater than 90% of temporal variation across the full 1993 - 2022 time-series. This data represents the 30-year standard deviation from 1993 - 2022. References: Gao, X., Gray, J. M., & Reich, B. J. (2021). Long-term, medium spatial resolution annual land surface phenology with a Bayesian hierarchical model. Remote Sensing of Environment, 261, 112484. https://doi.org/10.1016/j.rse.2021.112484
Knowledge graph centered on Fall Snowpack Onset Standard Deviation Day of Year with 3 nodes and 3 connections. Top connected: Upper East River Beaver Pond, Multi-model PlanetScope snow cover classification.
Items connected by shared entities, co-authorship, citations, or semantic similarity.