On the need for a time- and location-dependent estimation of the NDSI threshold value for reducing existing uncertainties in snow cover maps at different scales
Knowledge of current snow cover extent is essential for characterizing energy and moisture fluxes at the Earth's surface. The snow-covered area (SCA) is often estimated by using optical satellite information in combination with the normalized-difference snow index (NDSI). The NDSI thereby uses...
Published in: | The Cryosphere |
---|---|
Main Authors: | , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Copernicus Publications
2018
|
Subjects: | |
Online Access: | https://doi.org/10.5194/tc-12-1629-2018 https://www.the-cryosphere.net/12/1629/2018/tc-12-1629-2018.pdf https://doaj.org/article/a057c6489e9f434980da106b2b9364ae |
id |
fttriple:oai:gotriple.eu:oai:doaj.org/article:a057c6489e9f434980da106b2b9364ae |
---|---|
record_format |
openpolar |
spelling |
fttriple:oai:gotriple.eu:oai:doaj.org/article:a057c6489e9f434980da106b2b9364ae 2023-05-15T18:32:18+02:00 On the need for a time- and location-dependent estimation of the NDSI threshold value for reducing existing uncertainties in snow cover maps at different scales S. Härer M. Bernhardt M. Siebers K. Schulz 2018-05-01 https://doi.org/10.5194/tc-12-1629-2018 https://www.the-cryosphere.net/12/1629/2018/tc-12-1629-2018.pdf https://doaj.org/article/a057c6489e9f434980da106b2b9364ae en eng Copernicus Publications doi:10.5194/tc-12-1629-2018 1994-0416 1994-0424 https://www.the-cryosphere.net/12/1629/2018/tc-12-1629-2018.pdf https://doaj.org/article/a057c6489e9f434980da106b2b9364ae undefined The Cryosphere, Vol 12, Pp 1629-1642 (2018) geo envir Journal Article https://vocabularies.coar-repositories.org/resource_types/c_6501/ 2018 fttriple https://doi.org/10.5194/tc-12-1629-2018 2023-01-22T19:12:27Z Knowledge of current snow cover extent is essential for characterizing energy and moisture fluxes at the Earth's surface. The snow-covered area (SCA) is often estimated by using optical satellite information in combination with the normalized-difference snow index (NDSI). The NDSI thereby uses a threshold for the definition if a satellite pixel is assumed to be snow covered or snow free. The spatiotemporal representativeness of the standard threshold of 0.4 is however questionable at the local scale. Here, we use local snow cover maps derived from ground-based photography to continuously calibrate the NDSI threshold values (NDSIthr) of Landsat satellite images at two European mountain sites of the period from 2010 to 2015. The Research Catchment Zugspitzplatt (RCZ, Germany) and Vernagtferner area (VF, Austria) are both located within a single Landsat scene. Nevertheless, the long-term analysis of the NDSIthr demonstrated that the NDSIthr at these sites are not correlated (r = 0.17) and different than the standard threshold of 0.4. For further comparison, a dynamic and locally optimized NDSI threshold was used as well as another locally optimized literature threshold value (0.7). It was shown that large uncertainties in the prediction of the SCA of up to 24.1 % exist in satellite snow cover maps in cases where the standard threshold of 0.4 is used, but a newly developed calibrated quadratic polynomial model which accounts for seasonal threshold dynamics can reduce this error. The model minimizes the SCA uncertainties at the calibration site VF by 50 % in the evaluation period and was also able to improve the results at RCZ in a significant way. Additionally, a scaling experiment shows that the positive effect of a locally adapted threshold diminishes using a pixel size of 500 m or larger, underlining the general applicability of the standard threshold at larger scales. Article in Journal/Newspaper The Cryosphere Unknown The Cryosphere 12 5 1629 1642 |
institution |
Open Polar |
collection |
Unknown |
op_collection_id |
fttriple |
language |
English |
topic |
geo envir |
spellingShingle |
geo envir S. Härer M. Bernhardt M. Siebers K. Schulz On the need for a time- and location-dependent estimation of the NDSI threshold value for reducing existing uncertainties in snow cover maps at different scales |
topic_facet |
geo envir |
description |
Knowledge of current snow cover extent is essential for characterizing energy and moisture fluxes at the Earth's surface. The snow-covered area (SCA) is often estimated by using optical satellite information in combination with the normalized-difference snow index (NDSI). The NDSI thereby uses a threshold for the definition if a satellite pixel is assumed to be snow covered or snow free. The spatiotemporal representativeness of the standard threshold of 0.4 is however questionable at the local scale. Here, we use local snow cover maps derived from ground-based photography to continuously calibrate the NDSI threshold values (NDSIthr) of Landsat satellite images at two European mountain sites of the period from 2010 to 2015. The Research Catchment Zugspitzplatt (RCZ, Germany) and Vernagtferner area (VF, Austria) are both located within a single Landsat scene. Nevertheless, the long-term analysis of the NDSIthr demonstrated that the NDSIthr at these sites are not correlated (r = 0.17) and different than the standard threshold of 0.4. For further comparison, a dynamic and locally optimized NDSI threshold was used as well as another locally optimized literature threshold value (0.7). It was shown that large uncertainties in the prediction of the SCA of up to 24.1 % exist in satellite snow cover maps in cases where the standard threshold of 0.4 is used, but a newly developed calibrated quadratic polynomial model which accounts for seasonal threshold dynamics can reduce this error. The model minimizes the SCA uncertainties at the calibration site VF by 50 % in the evaluation period and was also able to improve the results at RCZ in a significant way. Additionally, a scaling experiment shows that the positive effect of a locally adapted threshold diminishes using a pixel size of 500 m or larger, underlining the general applicability of the standard threshold at larger scales. |
format |
Article in Journal/Newspaper |
author |
S. Härer M. Bernhardt M. Siebers K. Schulz |
author_facet |
S. Härer M. Bernhardt M. Siebers K. Schulz |
author_sort |
S. Härer |
title |
On the need for a time- and location-dependent estimation of the NDSI threshold value for reducing existing uncertainties in snow cover maps at different scales |
title_short |
On the need for a time- and location-dependent estimation of the NDSI threshold value for reducing existing uncertainties in snow cover maps at different scales |
title_full |
On the need for a time- and location-dependent estimation of the NDSI threshold value for reducing existing uncertainties in snow cover maps at different scales |
title_fullStr |
On the need for a time- and location-dependent estimation of the NDSI threshold value for reducing existing uncertainties in snow cover maps at different scales |
title_full_unstemmed |
On the need for a time- and location-dependent estimation of the NDSI threshold value for reducing existing uncertainties in snow cover maps at different scales |
title_sort |
on the need for a time- and location-dependent estimation of the ndsi threshold value for reducing existing uncertainties in snow cover maps at different scales |
publisher |
Copernicus Publications |
publishDate |
2018 |
url |
https://doi.org/10.5194/tc-12-1629-2018 https://www.the-cryosphere.net/12/1629/2018/tc-12-1629-2018.pdf https://doaj.org/article/a057c6489e9f434980da106b2b9364ae |
genre |
The Cryosphere |
genre_facet |
The Cryosphere |
op_source |
The Cryosphere, Vol 12, Pp 1629-1642 (2018) |
op_relation |
doi:10.5194/tc-12-1629-2018 1994-0416 1994-0424 https://www.the-cryosphere.net/12/1629/2018/tc-12-1629-2018.pdf https://doaj.org/article/a057c6489e9f434980da106b2b9364ae |
op_rights |
undefined |
op_doi |
https://doi.org/10.5194/tc-12-1629-2018 |
container_title |
The Cryosphere |
container_volume |
12 |
container_issue |
5 |
container_start_page |
1629 |
op_container_end_page |
1642 |
_version_ |
1766216410669776896 |