LSD4WSD VX: An Open Dataset for Wet Snow Detection with SAR Data and Physical Labelling - Full Analysis Version

Learning SAR Dataset for Wet Snow Detection - Full Analysis Version. 

The aim of this dataset is to provide a basis for automatic learning to detect wet snow. It is based on Sentinel-1 SAR GRD satellite images acquired between August 2020 and August 2021 over the French Alps. The new version of this dataset is no longer simply restricted to a classification task, and provides a set of metadata for each sample. It consists of 2467516 samples of size 15 by 15 by 9 stored ins hdf5 file. For each sample, the 9 metadata are provided, using in particular the Crocus physical model:

• topography:
  • elevation (meters) (average),
  • orientation (degrees) (average),
  • slope (degrees) (average),
• metadata:
  • name of the alpine massif,
  • date of acquisition,
  • type of acquisition (ascending/descending),
• physics
  • Liquid Water Content (km/m2),
  • snow height (m),
  • minimum snowpack temperature (Celsius degree).

An overview of the distribution and a summary of the sample statistics can be found in the file info.pdf. A more complete description can be found in the README.pdf file.

 The processing chain is available at the following Github address.