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NOTE: We discovered some errors in the data for images after February 2019. They will be fixed in version >= 1.1.x, until then, usage of the data after Feb 2019 is not advised. The rest of the data is fine. This is the data to the same-titled Data paper. Abstract: Snow cover dynamics impact a whole range of systems in mountain regions, from society to economy to ecology; and they also affect downstream regions. Monitoring and analyzing snow cover dynamics has been facilitated with remote sensing products. Here, we present a high-resolution daily snow cover data set for the entire European Alps based on MODIS covering the years 2002 to 2019, with automatic updates. Its implementation is specifically tailored to the complex terrain. Additionally, a nearly-cloud free product was created using temporal and spatial filters, which reduces average cloud cover from 41.9% to less than 0.1%. Overall accuracy was 91.9% for the original and 91.1% for the nearly cloud-free version based on a comparison with ground data from 90 stations in the province of Bolzano in Northern Italy for 17 years (2002 Jul – 2019 May). The data can be accessed online and via the R and python programming languages. Possible applications of the data include but are not limited to hydrology, cryosphere and climate.
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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