Global Determination of Snow Cover using Remote Sensing and a Near Real Time Processing Chain
Remote sensing offers the best prerequisites for obtaining comprehensive information on global snow cover. Although microwave remote sensing can provide limited information about the thickness of the snowpack and the water stored (i.e. snow water equivalent), its geometric resolution is not sufficie...
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ftdlr:oai:elib.dlr.de:187165 2024-05-19T07:47:34+00:00 Global Determination of Snow Cover using Remote Sensing and a Near Real Time Processing Chain Rößler, Sebastian Dietz, Andreas 2021-06-09 application/pdf https://elib.dlr.de/187165/ https://elib.dlr.de/187165/1/72.%2BRoessler_Dietz.pdf https://elib.dlr.de/187165/2/PosterRoesslerDietzESC21.pdf https://www.easternsnow.org/esc-2021 en eng https://elib.dlr.de/187165/1/72.%2BRoessler_Dietz.pdf https://elib.dlr.de/187165/2/PosterRoesslerDietzESC21.pdf Rößler, Sebastian und Dietz, Andreas (2021) Global Determination of Snow Cover using Remote Sensing and a Near Real Time Processing Chain. In: Proceedings of the 77th Eastern Snow Conference. 77th Eastern Snow Conference, 2021-06-09, Saskatoon, Canada (virtual). ISBN 978-1-926503-07-3. ISSN 0424-1932. Dynamik der Landoberfläche Konferenzbeitrag NonPeerReviewed 2021 ftdlr 2024-04-25T01:02:02Z Remote sensing offers the best prerequisites for obtaining comprehensive information on global snow cover. Although microwave remote sensing can provide limited information about the thickness of the snowpack and the water stored (i.e. snow water equivalent), its geometric resolution is not sufficient for an accurate spatial analysis. Optical remote sensing provides the required spatial resolution, but it is often compromised by clouds or at high geographical latitudes by the polar night. In order to obtain cloud-free information on daily snow cover from optical data, the German Aerospace Center developed the already established product Global SnowPack (GSP). It is based on the daily MODIS snow products originating from Terra and Aqua platforms and provided by NSIDC. With the help of sequential algorithms and additional data (digital elevation model, land cover classifications), pixels with clouds or polar night are continuously eliminated. While the Global SnowPack has so far only been calculated retrospectively for the entire hydrological year, there will now also be a near real time product (NRT-GSP). The latest MODIS data (these are available after approx. 2 days) are interpolated on a daily basis using the previous days. The product will be available in the future on the GeoService of the Earth Observation Center. We see an application of this product, for example, in the prediction of extreme hydrological events. In a recently published study, the development of the snow cover of various catchment areas of nival rivers derived from Global SnowPack was incorporated into a snowmelt runoff model. It was found that extreme high and low water events during the annual spring flood were reflected early in the development of the snow cover extent. With the help of the NRT-GSP product, such a development would be recognizable at an early stage and preparations could be made. Conference Object polar night German Aerospace Center: elib - DLR electronic library |
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German Aerospace Center: elib - DLR electronic library |
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English |
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Dynamik der Landoberfläche |
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Dynamik der Landoberfläche Rößler, Sebastian Dietz, Andreas Global Determination of Snow Cover using Remote Sensing and a Near Real Time Processing Chain |
topic_facet |
Dynamik der Landoberfläche |
description |
Remote sensing offers the best prerequisites for obtaining comprehensive information on global snow cover. Although microwave remote sensing can provide limited information about the thickness of the snowpack and the water stored (i.e. snow water equivalent), its geometric resolution is not sufficient for an accurate spatial analysis. Optical remote sensing provides the required spatial resolution, but it is often compromised by clouds or at high geographical latitudes by the polar night. In order to obtain cloud-free information on daily snow cover from optical data, the German Aerospace Center developed the already established product Global SnowPack (GSP). It is based on the daily MODIS snow products originating from Terra and Aqua platforms and provided by NSIDC. With the help of sequential algorithms and additional data (digital elevation model, land cover classifications), pixels with clouds or polar night are continuously eliminated. While the Global SnowPack has so far only been calculated retrospectively for the entire hydrological year, there will now also be a near real time product (NRT-GSP). The latest MODIS data (these are available after approx. 2 days) are interpolated on a daily basis using the previous days. The product will be available in the future on the GeoService of the Earth Observation Center. We see an application of this product, for example, in the prediction of extreme hydrological events. In a recently published study, the development of the snow cover of various catchment areas of nival rivers derived from Global SnowPack was incorporated into a snowmelt runoff model. It was found that extreme high and low water events during the annual spring flood were reflected early in the development of the snow cover extent. With the help of the NRT-GSP product, such a development would be recognizable at an early stage and preparations could be made. |
format |
Conference Object |
author |
Rößler, Sebastian Dietz, Andreas |
author_facet |
Rößler, Sebastian Dietz, Andreas |
author_sort |
Rößler, Sebastian |
title |
Global Determination of Snow Cover using Remote Sensing and a Near Real Time Processing Chain |
title_short |
Global Determination of Snow Cover using Remote Sensing and a Near Real Time Processing Chain |
title_full |
Global Determination of Snow Cover using Remote Sensing and a Near Real Time Processing Chain |
title_fullStr |
Global Determination of Snow Cover using Remote Sensing and a Near Real Time Processing Chain |
title_full_unstemmed |
Global Determination of Snow Cover using Remote Sensing and a Near Real Time Processing Chain |
title_sort |
global determination of snow cover using remote sensing and a near real time processing chain |
publishDate |
2021 |
url |
https://elib.dlr.de/187165/ https://elib.dlr.de/187165/1/72.%2BRoessler_Dietz.pdf https://elib.dlr.de/187165/2/PosterRoesslerDietzESC21.pdf https://www.easternsnow.org/esc-2021 |
genre |
polar night |
genre_facet |
polar night |
op_relation |
https://elib.dlr.de/187165/1/72.%2BRoessler_Dietz.pdf https://elib.dlr.de/187165/2/PosterRoesslerDietzESC21.pdf Rößler, Sebastian und Dietz, Andreas (2021) Global Determination of Snow Cover using Remote Sensing and a Near Real Time Processing Chain. In: Proceedings of the 77th Eastern Snow Conference. 77th Eastern Snow Conference, 2021-06-09, Saskatoon, Canada (virtual). ISBN 978-1-926503-07-3. ISSN 0424-1932. |
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1799487999054970880 |