A method for monthly mapping of wet and dry snow using Sentinel-1 and MODIS: Application to a Himalayan river basin

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dc.contributor.author Snapir, Boris
dc.contributor.author Momblanch, Andrea
dc.contributor.author Jain, S. K.
dc.contributor.author Waine, Toby
dc.contributor.author Holman, Ian P.
dc.date.accessioned 2018-10-24T14:29:18Z
dc.date.available 2018-10-24T14:29:18Z
dc.date.issued 2018-10-01
dc.identifier.citation Snapir B, Momblanch A, Jain SK, et al., A method for monthly mapping of wet and dry snow using Sentinel-1 and MODIS: Application to a Himalayan river basin. International Journal of Applied Earth Observation and Geoinformation, Volume 74, February 2019, pp. 222-230 en_UK
dc.identifier.issn 0303-2434
dc.identifier.uri https://doi.org/10.1016/j.jag.2018.09.011
dc.identifier.uri http://dspace.lib.cranfield.ac.uk/handle/1826/13564
dc.description.abstract Satellite Remote Sensing, with both optical and SAR instruments, can provide distributed observations of snow cover over extended and inaccessible areas. Both instruments are complementary, but there have been limited attempts at combining their measurements. We describe a novel approach to produce monthly maps of dry and wet snow areas through application of data fusion techniques to MODIS fractional snow cover and Sentinel-1 wet snow mask, facilitated by Google Earth Engine. The method is demonstrated in a 55,000 km2 river basin in the Indian Himalayan region over a period of ∼2.5 years, although it can be applied to any areas of the world where Sentinel-1 data are routinely available. The typical underestimation of wet snow area by SAR is corrected using a digital elevation model to estimate the average melting altitude. We also present an empirical model to derive the fractional cover of wet snow from Sentinel-1. Finally, we demonstrate that Sentinel-1 effectively complements MODIS as it highlights a snowmelt phase which occurs with a decrease in snow depth but no/little decrease in snowpack area. Further developments are now needed to incorporate these high resolution observations of snow areas as inputs to hydrological models for better runoff analysis and improved management of water resources and flood risk. en_UK
dc.language.iso en en_UK
dc.publisher Elsevier en_UK
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/ *
dc.subject Snow en_UK
dc.subject MODIS en_UK
dc.subject Sentinel-1 en_UK
dc.subject Google Earth Engine en_UK
dc.subject Himalayas en_UK
dc.title A method for monthly mapping of wet and dry snow using Sentinel-1 and MODIS: Application to a Himalayan river basin en_UK
dc.type Article en_UK
dc.identifier.cris 19158964


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