ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - viewable snow (SCFV) from MODIS (2000 - 2022), version 3.0
type: Dataset
modified: 2000-02-24T00:00:00Z
keyword: ESA
keyword: CCI
keyword: Snow
keyword: Snow Cover Fraction
keyword: orthoimagery
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language: EN
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      creator: https://doi.org/
      notation: https://doi.org/10.1016/j.rse.2014.09.018
    title: MetsÃ¤mÃ¤ki, S., Pulliainen, J., Salminen, M., Luojus, K., Wiesmann, A., Solberg R. and Ripper, E. 2015. Introduction to GlobSnow Snow Extent products with considerations for accuracy assessment. Remote Sensing of Environment, 156, 96â108
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      notation: Salminen, M., Pulliainen, J., MetsÃ¤mÃ¤ki, S., Ikonen, J., HeinilÃ¤, K. (2018). Determination of uncertainty characteristics for the satellite
    title: Salminen, M., Pulliainen, J., MetsÃ¤mÃ¤ki, S., Ikonen, J., HeinilÃ¤, K. (2018). Determination of uncertainty characteristics for the satellite-based estimation of fractional snow cover. Remote Sensing Environ., 212, 103-113. https://doi.org/10.1016/j.rse.2018.04.038
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description: This dataset contains Daily Snow Cover Fraction of viewable snow from the MODIS satellite instruments, produced by the Snow project of the ESA Climate Change Initiative programme. Snow cover fraction viewable (SCFV) indicates the area of snow viewable from space over all land surfaces. In forested areas this refers to snow viewable on top of the forest canopy. The SCFV is given in percentage (%) per pixel. The global SCFV product is available at about 1 km pixel size for all land areas, excluding Antarctica and Greenland ice sheets and permanent snow and ice areas. The coastal zones of Greenland are included. The SCFV time series provides daily products for the period 2000 â 2022. The SCFV product is based on Moderate resolution Imaging Spectroradiometer (MODIS) data on-board the Terra satellite. The retrieval method of the Snow_cci SCFV product from MODIS data has been further developed and improved based on the ESA GlobSnow approach described by MetsÃ¤mÃ¤ki et al. (2015) and complemented with a pre-classification module developed by ENVEO (ENVironmental Earth Observation IT GmbH). For the SCFV product generation from MODIS, multiple reflective and emissive spectral bands are used. In a first step, clouds are masked using an adapted version of the Simple Cloud Detection Algorithm version 2.0 (SCDA2.0) (MetsÃ¤mÃ¤ki et al., 2015). All cloud free pixels are then used for the snow extent mapping, using spectral bands centred at about 0.55 Âµm and 1.6 Âµm, and an emissive band centred at about 11 Âµm. The snow_cci snow cover mapping algorithm is a two-step approach: first, a strict pre-classification is applied to identify all cloud free pixels which are certainly snow free. For all remaining pixels, the Snow_cci SCFV retrieval method is applied. The main differences of the Snow_cci snow cover mapping algorithm compared to the GlobSnow algorithm described in MetsÃ¤mÃ¤ki et al. (2015) are (i) improvements of the cloud screening approach applicable on a global scale, (ii)…
temporal: PeriodOfTime
  start date: 2000-02-24T00:00:00Z
  end date: 2022-12-31T23:59:59Z

CatalogRecord
modified: 2026-08-05T00:53:16Z
conforms to: https://joinup.ec.europa.eu/release/geodcat-ap/20

https://fedeo.ceos.org/collections/e955813b0e1a4eb7af971f923010b4a3
type: CatalogRecord
conforms to: ISO19139-2

CEDA Data Catalogue Page
type: Document
description: Detail and access information for the resource

j.rse.2014.09.018
type: Document
description: No further details.
title: MetsÃ¤mÃ¤ki, S., Pulliainen, J., Salminen, M., Luojus, K., Wiesmann, A., Solberg R. and Ripper, E. 2015. Introduction to GlobSnow Snow Extent products with considerations for accuracy assessment. Remote Sensing of Environment, 156, 96â108

MODIS Characterization Support Team, MODIS Adaptive Processing System, 2012. Level 1 and Atmosphere Archive and Distribution System (LAADS): MOD03
type: Document
description: No further details.

ESA CCI Snow key documents
type: Document
description: No further details.

ESA CCI Snow project website
type: Document
description: No further details.

MODIS Characterization Support Team, MODIS Adaptive Processing System, 2012. Level 1 and Atmosphere Archive and Distribution System (LAADS): MOD021KM
type: Document
description: No further details.

Salminen, M., Pulliainen, J., MetsÃ¤mÃ¤ki, S., Ikonen, J., HeinilÃ¤, K. (2018). Determination of uncertainty characteristics for the satellite
type: Document
description: based estimation of fractional snow cover. Remote Sensing Environ., 212, 103-113. https://doi.org/10.1016/j.rse.2018.04.038 - No further details.

https://catalogue.ceda.ac.uk/uuid/b382ebe6679d44b8b0e68ea4ef4b701c
type: Document
description: No further details.
title: ESA Land Cover CCI project team; Defourny, P. (2019): ESA Land Cover Climate Change Initiative (Land_Cover_cci): Global Land Cover Maps, Version 2.0.7. Centre for Environmental Data Analysis, 13.04.2021

ESA Climate Change Initiative Website
type: Document
description: No further details.

Product User Guide
type: Document
description: No further details.

ESA CCI data standards
type: Document
description: No further details.

Snow CCI ENVEO homepage
type: Document
description: No further details.

Climate Research Data Package
type: Document
description: No further details.

EARTH SCIENCE>CLIMATE INDICATORS>CRYOSPHERIC INDICATORS>SNOW COVER
type: Concept
in scheme: https://gcmd.earthdata.nasa.gov/kms/concepts/concept_scheme/sciencekeywords