Remote sensing of global snow cover

Snow cover is an important variable for water availability, the radiation budget, glaciers, flora and fauna, and may cause natural disasters such as avalanches or floods. In many countries, snow is an important source of freshwater for reservoirs and the subsequent production of electricity. Climate...

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Bibliographic Details
Main Authors: Dietz, Andreas, Künzer, Claudia
Format: Conference Object
Language:unknown
Published: 2018
Subjects:
Online Access:https://elib.dlr.de/121192/
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spelling ftdlr:oai:elib.dlr.de:121192 2024-05-19T07:47:34+00:00 Remote sensing of global snow cover Dietz, Andreas Künzer, Claudia 2018 https://elib.dlr.de/121192/ unknown Dietz, Andreas und Künzer, Claudia (2018) Remote sensing of global snow cover. International Symposium on Regional Reanalysis, 2018-07-17 - 2018-07-19, Bonn, Deutschland. Landoberfläche Konferenzbeitrag NonPeerReviewed 2018 ftdlr 2024-04-25T00:45:34Z Snow cover is an important variable for water availability, the radiation budget, glaciers, flora and fauna, and may cause natural disasters such as avalanches or floods. In many countries, snow is an important source of freshwater for reservoirs and the subsequent production of electricity. Climate change is affecting the global snow cover distribution, extent, and mass, influencing all the aforementioned parameters. It is therefore important to monitor the developments and changes to be able to detect possible trends and future impacts of changing snow cover on our environment. Remote Sensing offers an ideal data source to detect global snow cover with both high temporal and spatial resolution. Observations from medium resolution sensors such as AVHRR, MODIS, or Sentinel-3 provide time series of daily data, which can be processed and classified to calculate the snow cover extent on a global scale. Polar night, cloud cover, and complex terrain in mountain regions can cause data gaps and classification uncertainties. To overcome these problems, several techniques can be applied to the data in order to provide a consistent time series of daily snow cover information, which can further be processed to derive parameters such as snow cover duration per year or beginning/end of snow cover season. These parameters can be analysed to quantify the effects of climate change on snow cover on local, regional, and global scales. The presentation will outline the different steps in order to obtain snow cover information from remote sensing data and how these snow cover parameters can further be processed. Several examples will be presented for possible applications, and the opportunity of combining the results from remote sensing with those obtained by modelling/re-analysis will also be discussed. Conference Object polar night German Aerospace Center: elib - DLR electronic library
institution Open Polar
collection German Aerospace Center: elib - DLR electronic library
op_collection_id ftdlr
language unknown
topic Landoberfläche
spellingShingle Landoberfläche
Dietz, Andreas
Künzer, Claudia
Remote sensing of global snow cover
topic_facet Landoberfläche
description Snow cover is an important variable for water availability, the radiation budget, glaciers, flora and fauna, and may cause natural disasters such as avalanches or floods. In many countries, snow is an important source of freshwater for reservoirs and the subsequent production of electricity. Climate change is affecting the global snow cover distribution, extent, and mass, influencing all the aforementioned parameters. It is therefore important to monitor the developments and changes to be able to detect possible trends and future impacts of changing snow cover on our environment. Remote Sensing offers an ideal data source to detect global snow cover with both high temporal and spatial resolution. Observations from medium resolution sensors such as AVHRR, MODIS, or Sentinel-3 provide time series of daily data, which can be processed and classified to calculate the snow cover extent on a global scale. Polar night, cloud cover, and complex terrain in mountain regions can cause data gaps and classification uncertainties. To overcome these problems, several techniques can be applied to the data in order to provide a consistent time series of daily snow cover information, which can further be processed to derive parameters such as snow cover duration per year or beginning/end of snow cover season. These parameters can be analysed to quantify the effects of climate change on snow cover on local, regional, and global scales. The presentation will outline the different steps in order to obtain snow cover information from remote sensing data and how these snow cover parameters can further be processed. Several examples will be presented for possible applications, and the opportunity of combining the results from remote sensing with those obtained by modelling/re-analysis will also be discussed.
format Conference Object
author Dietz, Andreas
Künzer, Claudia
author_facet Dietz, Andreas
Künzer, Claudia
author_sort Dietz, Andreas
title Remote sensing of global snow cover
title_short Remote sensing of global snow cover
title_full Remote sensing of global snow cover
title_fullStr Remote sensing of global snow cover
title_full_unstemmed Remote sensing of global snow cover
title_sort remote sensing of global snow cover
publishDate 2018
url https://elib.dlr.de/121192/
genre polar night
genre_facet polar night
op_relation Dietz, Andreas und Künzer, Claudia (2018) Remote sensing of global snow cover. International Symposium on Regional Reanalysis, 2018-07-17 - 2018-07-19, Bonn, Deutschland.
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