Abstract:
This product shows globally the daily snow cover extent (SCE). The snow cover extent is the result of the Global SnowPack processor's interpolation steps and all data gaps have been filled. Snow cover extent is updated daily and processed in near real time (3 days lag). In addition to the near real-time product (NRT_SCE), the entire annual data set is processed again after the end of a calendar year in order to close data gaps etc. and the result is made available as a quality-tested SCE product. There is also a quality layer for each day (SCE_Accuracy), which reflects the quality of the snow determination based on the time interval to the next "cloud-free" day, the time of year and the topographical/geographical location.
The “Global SnowPack” is derived from daily, operational MODIS snow cover product for each day since February 2000. Data gaps due to polar night and cloud cover are filled in several processing steps, which provides a unique global data set characterized by its high accuracy, spatial resolution of 500 meters and continuous future expansion. It consists of the two main elements daily snow cover extent (SCE) and seasonal snow cover duration (SCD; full and for early and late season). Both parameters have been designated by the WMO as essential climate variables, the accurate determination of which is important in order to be able to record the effects of climate change. Changes in the largest part of the cryosphere in terms of area have drastic effects on people and the environment.
Product Information:
- Product Name: GSP - Global SnowPack Daily
- Product Version: 2
- Release: 2022-03-01
- Contact: Sebastian Rößler
Data Information:
- Satellite: Terra (EOS-1)/Aqua (EOS-PM1)
- Sensor: MODIS
- Format: Cloud Optimized GeoTIFF
- Resolution: 460 x 460
- Period: 2000 - today
- Coverage: Global
- License: CC BY 4.0
Data:
Attributes:
The individual bit positions indicate the class to which they belong (bits 4-8) or the interpolation level (bits 1-3). The meaning of the bytes is as follows (little-endian):
- 1: Classified by 3-day interpolation
- 2: Classified according to topographical interpolation of absolute snow lines
- 4: Classified according to seasonal interpolation of the previous days
- 8: Class: ocean
- 16: Class: inland water
- 32: Class: snow-free land
- 64: Class: snow covered with low NDSI (greater than 0.1, smaller than 0.4) - snow in the forest
- 128: snow covered with high NDSI (greater than 0.4)
The value of the pixels can be read as follows: A value of 132 (128+4) indicates that there is snow cover (value 128), but this was only detected with the seasonal interpolation (value 4). If a binary mask is required, all pixels with a value greater than or equal to 64 should be selected.
References:
- Dietz, A.J., Kuenzer, C., Conrad, C., 2013. Snow–cover variability in central Asia between 2000 and 2011 derived from improved MODIS daily snow-cover products. International Journal of Remote Sensing 34, 3879–3902. https://doi.org/10.1080/01431161.2013.767480
- Dietz, A.J., Kuenzer, C., Dech, S., 2015. Global SnowPack: a new set of snow cover parameters for studying status and dynamics of the planetary snow cover extent. Remote Sensing Letters 6, 844–853. https://doi.org/10.1080/2150704X.2015.1084551
- Dietz, A.J., Wohner, C., Kuenzer, C., 2012. European Snow Cover Characteristics between 2000 and 2011 Derived from Improved MODIS Daily Snow Cover Products. Remote Sensing 4. https://doi.org/10.3390/rs4082432
- Dietz, J.A., Conrad, C., Kuenzer, C., Gesell, G., Dech, S., 2014. Identifying Changing Snow Cover Characteristics in Central Asia between 1986 and 2014 from Remote Sensing Data. Remote Sensing 6. https://doi.org/10.3390/rs61212752
- Rößler, S., Witt, M.S., Ikonen, J., Brown, I.A., Dietz, A.J., 2021. Remote Sensing of Snow Cover Variability and Its Influence on the Runoff of Sápmi’s Rivers. Geosciences 11, 130. https://doi.org/10.3390/geosciences11030130
DLR © 2022
Keywords:
DLR, EOC, Land, Global Snowpack, daily, snow cover extent, near real-time
Map Projection:
Bounds: -180, -90, 180, 90