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Daily MODIS Snow Cover Maps for the European Alps from 2002 onwards at 250 m Horizontal Resolution Along with a Nearly Cloud-Free Version

Author

Listed:
  • Michael Matiu

    (Institute for Earth Observation, Eurac Research, 39100 Bolzano/Bozen, Italy)

  • Alexander Jacob

    (Institute for Earth Observation, Eurac Research, 39100 Bolzano/Bozen, Italy)

  • Claudia Notarnicola

    (Institute for Earth Observation, Eurac Research, 39100 Bolzano/Bozen, Italy)

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 two high-resolution daily snow cover data sets for the entire European Alps covering the years 2002 to 2019, and with automatic updates. The first is based on moderate resolution imaging spectroradiometer (MODIS) and its implementation is specifically tailored to the complex terrain, exploiting the highest possible resolution available of 250 m. The second is a nearly cloud-free product derived from the first using temporal and spatial filters, which reduce average cloud cover from 41.9% to less than 0.1%. Validation has been performed using an extensive network of 312 ground stations, and for the cloud filtering also with cross-validation. Average overall accuracies were 93% for the initial and 91.5% for the cloud-filtered product using the ground stations; and 95.3% for the cross-validation of the cloud-filter. 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.

Suggested Citation

  • Michael Matiu & Alexander Jacob & Claudia Notarnicola, 2019. "Daily MODIS Snow Cover Maps for the European Alps from 2002 onwards at 250 m Horizontal Resolution Along with a Nearly Cloud-Free Version," Data, MDPI, vol. 5(1), pages 1-11, December.
    • Handle: RePEc:gam:jdataj:v:5:y:2019:i:1:p:1-:d:299417
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    References listed on IDEAS

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    1. Ludovica Gregorio & Mattia Callegari & Paolo Mazzoli & Stefano Bagli & Davide Broccoli & Alberto Pistocchi & Claudia Notarnicola, 2018. "Operational River Discharge Forecasting with Support Vector Regression Technique Applied to Alpine Catchments: Results, Advantages, Limits and Lesson Learned," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(1), pages 229-242, January.
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