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Fusion of multi-temporal optical and SAR satellite data for improved snow facies mapping on glaciers

Wendleder, Anna and Rastner, Philipp and Heilig, Achim (2019) Fusion of multi-temporal optical and SAR satellite data for improved snow facies mapping on glaciers. Living Planet Symposium 2019, 13.-17.Mai 2019, Mailand, Italien.

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Abstract

Mapping snow cover (SC) on glaciers at the end of the ablation period supports the comprehension how and in which rate a glacier accumulates and ablates, respectively, and which influence climate variabilities have. Furthermore, the SC can be used for the determination of the mass balance. Remote Sensing data are able to provide this information for remote, large glaciers and back in time. With optical satellite imagery it is possible to detect SC on glacier relatively straight forward when no clouds are present and when the bare ice is clearly different from the snow zone on the glacier. Optical satellite data fail, however, to identify whether the snow on the glacier is dry, wet or whether firn is present or not. In contrast, SAR data like TerraSAR-X or Sentinel-1 can discriminate dry snow, wet snow, firn and bare ice. In this contribution, we compare three types of multi-temporal SC maps for a set of glaciers in the Ötztal Alps-Austria. For several acquisition times we performed a multiple digitizing experiment by manually mapping the SC area on the glaciers based on high resolution Landsat image which served in the following as reference data. Additionally, we applied the automatic SC mapping tool named ´automated snow mapping on glaciers´ (ASMAG) based on Landsat imagery. The algorithm automatically determines cloud cover and converts raw digital numbers into topographically corrected top of atmosphere reflectance (TOAR). Subsequently, a reflectance threshold for the near-infrared band is automatically selected to map snow on glaciers. Finally, we used TerraSAR-X and Sentinel-1 data to derive the various snow facies for the acquisition times . A first assessment shows that the manual derived outlines and the SC maps from ASMAG are of high accuracy (~90%). The maps derived from TerraSAR-X are more difficult to interpret. Wet snow maps agree by about 60% with the SC maps from ASMAG, however, dry snow maps, firn and bare ice are difficult to classify. On the other hand, snow facies maps from Sentinel 1 shows a higher agreement in respect to TerraSAR-X, which might be due to the different snow conditions during the acquisitions of TerraSAR-X and Sentinel-1 (5:30 a.m. UTC) and Landsat (11 a.m. UTC). We conclude, that the combination of different sensors is highly recommendable to support a continuous SC monitoring and to eliminate the disadvantages of each sensor. Also, the round robin experiment resulted in a high agreement. Due to the high repetition time of Sentinel-1 data, the comparison of the SC maps is facilitated in contrast to TerraSAR-X.

Item URL in elib:https://elib.dlr.de/128640/
Document Type:Conference or Workshop Item (Poster)
Title:Fusion of multi-temporal optical and SAR satellite data for improved snow facies mapping on glaciers
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Wendleder, AnnaAnna.Wendleder (at) dlr.deUNSPECIFIED
Rastner, Philippphilipp.rastner (at) geo.uzh.chUNSPECIFIED
Heilig, AchimMunich UniversityUNSPECIFIED
Date:May 2019
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:snow, optical data, SAR, data fusion, glacier
Event Title:Living Planet Symposium 2019
Event Location:Mailand, Italien
Event Type:international Conference
Event Dates:13.-17.Mai 2019
Organizer:ESA
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Remote sensing and geoscience
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Land Surface Dynamics
Deposited By: Wendleder, Anna
Deposited On:05 Aug 2019 10:02
Last Modified:05 Aug 2019 10:02

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