ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - viewable snow (SCFV) from MODIS (2000 - 2020), version 2.0
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keyword: ESA
keyword: CCI
keyword: Snow
keyword: Snow Cover Fraction
keyword: orthoimagery
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  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 - No further details.
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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. The coastal zones of Greenland are included. The SCFV time series provides daily products for the period 2000 â 2020. 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. 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) the pre-classification of snow free areas on global land areas, (iii) the …
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relation: https://fedeo.ceos.org/collections/ebe625b6f77945a68bda0ab7c78dd76b/items/b03715f83ec6f8073518c97302d16b86281de408
format: application/ld+json
had role: https://stacspec.org/def/rel/iana/1.0/item

20000312-ESACCI-L3C_SNOW-SCFV-MODIS_TERRA-fv2.0.nc
type: Relationship
relation: https://fedeo.ceos.org/collections/ebe625b6f77945a68bda0ab7c78dd76b/items/8f3fdd1899475319e085c044bf800e4fdf984c30
format: application/ld+json
had role: https://stacspec.org/def/rel/iana/1.0/item

20000313-ESACCI-L3C_SNOW-SCFV-MODIS_TERRA-fv2.0.nc
type: Relationship
relation: https://fedeo.ceos.org/collections/ebe625b6f77945a68bda0ab7c78dd76b/items/ce9d360ecc9617ca063666c19b45f6e79665415a
format: application/ld+json
had role: https://stacspec.org/def/rel/iana/1.0/item

Landing Page in JSON media type.
type: Relationship
relation: https://fedeo.ceos.org
format: application/json
had role: http://www.iana.org/assignments/relation/alternate

PeriodOfTime
start date: 2000-02-24T00:00:00.000Z
end date: 2020-12-31T23:59:59.999Z