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1. www.mdpi.com › 2072/4292/16-1 › 188Reconstructing Snow Cover under Clouds and Cloud Shadows by ...

   www.mdpi.com › 2072/4292/16-1 › 188

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   Jan 2, 2024 · Based on our previously published approach for snow reconstruction on S2 images using the Google Earth Engine (GEE), this study introduces two main innovations to reconstruct snow cover: (1) combining S2 and L8 images and choosing different CCS detection methods, and (2) improving the cloud shadow detection algorithm by considering land cover ...

   • Snow Cover Reconstruction in the Brunswick Peninsula ... - MDPI

     The results show a 98% agreement between MODIS snow...

2. tc.copernicus.org › articles › 9/451/2015Snow-cover reconstruction methodology for mountainous regions ...

   tc.copernicus.org › articles › 9/451/2015

   Reconstructed snow cover was cross validated against independent remote sensing data and shows an accu-racy of about 85 %. The methodology can be used in moun-tainous regions to overcome the data gap for earlier decades when the availability of remote sensing snow-cover data was strongly limited.

   • Author: A. Gafurov, S. Vorogushyn, D. Farinotti, D. Duethmann, A. Merkushkin, B. Merz

   • Publish Year: 2015

3. tc.copernicus.org › articles › 9/451/2015TC - Snow-cover reconstruction methodology for mountainous ...

   tc.copernicus.org › articles › 9/451/2015

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   Mar 4, 2015 · We present a methodology to reconstruct historical snow coverage using recently available remote sensing data and long-term point observations of snow depth from existing meteorological stations. The methodology is mainly based on correlations between station records and spatial snow-cover patterns.

   • Author: A. Gafurov, S. Vorogushyn, D. Farinotti, D. Duethmann, A. Merkushkin, B. Merz

   • Publish Year: 2015

4. www.sciencedirect.com › science › articleAn integrated approach to reconstructing snow cover under ...

   www.sciencedirect.com › science › article

   Apr 1, 2023 · Based on the digital elevation model (DEM), in this paper, an integrated method of snow cover reconstruction on Sentinel-2 images is created by combining the improved SNOWL (snow line) algorithm considering unstable snow cover areas, Fmask cloud detection algorithms, and the Sen2Cor clear sky snow cover detection tool with a geospatial ...

5. www.mdpi.com › 2072/4292/15-22 › 5430Snow Cover Reconstruction in the Brunswick Peninsula ... - MDPI

   www.mdpi.com › 2072/4292/15-22 › 5430

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   Nov 20, 2023 · The results show a 98% agreement between MODIS snow detection and ground-based snow measurements at the automatic weather station, Tres Morros (53.3174°S, 71.2790°W), with fractional snow cover values between 20% and 50%, showing a close relationship between snow and vegetation type.

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7. www.frontiersin.org › journals › earth-scienceMulti-Decadal Variability in the Snow-Cover Reconstruction at ...

   www.frontiersin.org › journals › earth-science

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   Oct 29, 2020 · Data on snowfall and the persistence of snow cover on the surface are becoming increasingly important due to the high variability of snowfall rates worldwide (e.g., Davi et al., 2012), and the impact that snow cover can have on society, agriculture and water resources.

8. www.researchgate.net › publication › 273384116_Snow(PDF) Snow-cover reconstruction methodology for mountainous ...

   www.researchgate.net › publication › 273384116_Snow

   Mar 4, 2015 · Reconstructed snow cover was cross validated against independent remote sensing data and shows an accuracy of about 85 %. The methodology can be used in mountainous regions to overcome the...

9. People also ask

   How is snow cover reconstructed in mountainous regions?

   • Snow cover in mountainous is reconstructed by combing the Fmask, Sen2Cor and the improved SNOWL algorithms. Snow is an important type of surface cover and an important freshwater resource in the arid regions of northwest China, and optical satellites are an important means for monitoring variation in snow cover.

   An integrated approach to reconstructing snow cover under clouds and

   www.sciencedirect.com/science/article/pii/S0022169423002068

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   How accurate is snow cover extraction?

   • It can be seen that the snow cover extraction accuracy in flat surface and shady slope is the highest, and their user accuracy, mapping accuracy, and overall accuracy are all above 79 %, followed by semi-shady slope.

   An integrated approach to reconstructing snow cover under clouds and

   www.sciencedirect.com/science/article/pii/S0022169423002068

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   Why is snow cover important?

   • Due to the properties of high reflectance, low thermal conductivity, and snowmelt water effect, snow cover plays vital roles in the global energy balance, in hydrological and ecological models, and climate change ( Ault et al., 2006, McCabe and Wolock, 2010 ).

   An integrated approach to reconstructing snow cover under clouds and

   www.sciencedirect.com/science/article/pii/S0022169423002068

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   Does snow cover in mountainous areas have a spatial heterogeneity?

   • On the one hand, the spatial heterogeneity of snow distribution in mountainous areas is very strong, and the images with coarse spatial resolution cannot describe the snow cover in detail; on the other hand, these images are often saturated with snow pixels, especially on sun-facing slopes ( Zhang et al., 2020 ).

   An integrated approach to reconstructing snow cover under clouds and

   www.sciencedirect.com/science/article/pii/S0022169423002068

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   Which slope has the worst snow recognition accuracy?

   • The sunny slope has the worst snow recognition accuracy, which may be due to the fact that it is located in the unstable snow cover area and the snow ablation changes rapidly, while the GF-2 image used for accuracy validation was obtained after two days. Table 6. Accuracy evaluation results of snow cover in different aspects.

   An integrated approach to reconstructing snow cover under clouds and

   www.sciencedirect.com/science/article/pii/S0022169423002068

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   What factors affect snow cover in mountainous areas?

   • In mountainous areas with complex topography, however, in addition to surface elevation, many other factors will affect the accumulation and ablation of snow cover, such as surface energy balance, windward/leeward position, and slope/aspect, which all cause the strong spatial heterogeneity of snow cover ( Tong et al., 2009 ).

   An integrated approach to reconstructing snow cover under clouds and

   www.sciencedirect.com/science/article/pii/S0022169423002068

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