Cross-Country Assessment of H-SAF Snow Products by Sentinel-2 Imagery Validated against In-Situ Observations and Webcam Photography

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Piazzi G., Tanis C. M., KUTER S., Simsek B., Puca S., Toniazzo A., ...More

GEOSCIENCES, vol.9, no.3, 2019 (ESCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 9 Issue: 3
  • Publication Date: 2019
  • Doi Number: 10.3390/geosciences9030129
  • Journal Name: GEOSCIENCES
  • Journal Indexes: Emerging Sources Citation Index (ESCI), Scopus
  • Keywords: snow cover, fractional snow cover, Sentinel-2, H-SAF, webcam photography, COVERED AREA, NORTHERN XINJIANG, GRAIN-SIZE, MODIS, FORESTS, LANDSAT, PHENOLOGY, RETRIEVAL, FRACTION, CLOUD
  • Middle East Technical University Affiliated: Yes


Information on snow properties is of critical relevance for a wide range of scientific studies and operational applications, mainly for hydrological purposes. However, the ground-based monitoring of snow dynamics is a challenging task, especially over complex topography and under harsh environmental conditions. Remote sensing is a powerful resource providing snow observations at a large scale. This study addresses the potential of using Sentinel-2 high-resolution imagery to assess moderate-resolution snow products, namely H10-Snow detection (SN-OBS-1) and H12-Effective snow cover (SN-OBS-3) supplied by the Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF) project of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT). With the aim of investigating the reliability of reference data, the consistency of Sentinel-2 observations is evaluated against both in-situ snow measurements and webcam digital imagery. The study area encompasses three different regions, located in Finland, the Italian Alps and Turkey, to comprehensively analyze the selected satellite products over both mountainous and flat areas having different snow seasonality. The results over the winter seasons 2016/17 and 2017/18 show a satisfying agreement between Sentinel-2 data and ground-based observations, both in terms of snow extent and fractional snow cover. H-SAF products prove to be consistent with the high-resolution imagery, especially over flat areas. Indeed, while vegetation only slightly affects the detection of snow cover, the complex topography more strongly impacts product performances.