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Combination of PROBA-V/MODIS-based Products with Sentinel-1 SAR Data for Detecting Wet and Dry Snow Cover in Mountainous Areas

Tsai, Ya-Lun and Dietz, Andreas and Oppelt, Natascha and Künzer, Claudia (2019) Combination of PROBA-V/MODIS-based Products with Sentinel-1 SAR Data for Detecting Wet and Dry Snow Cover in Mountainous Areas. Remote Sensing, 11 (16), pp. 1-20. Multidisciplinary Digital Publishing Institute (MDPI). DOI: 10.3390/rs11161904 ISSN 2072-4292

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Official URL: https://www.mdpi.com/2072-4292/11/16/1904


In the present study, we explore the value of employing both vegetation indexes as well as land surface temperature derived from Project for On-Board Autonomy—Vegetation (PROBA-V) and Moderate Resolution Imaging Spectroradiometer (MODIS) sensors, respectively, to support the detection of total (wet + dry) snow cover extent (SCE) based on a simple tuning machine learning approach and provide reliability maps for further analysis. We utilize Sentinel-1-based synthetic aperture radar (SAR) observations, including backscatter coefficient, interferometric coherence, and polarimetric parameters, and four topographical factors as well as vegetation and temperature information to detect the total SCE with a land cover-dependent random forest-based approach. Our results show that the overall accuracy and F-measure are over 90% with an ’Area Under the receiver operating characteristic Curve (ROC)’ (AUC) score of approximately 80% over five study areas located in different mountain ranges, continents, and hemispheres. These accuracies are also confirmed by a comprehensive validation approach with different data sources, attesting the robustness and global transferability. Additionally, based on the reliability maps, we find an inversely proportional relationship between classification reliability and vegetation density. In conclusion, comparing to a previous study only utilizing SAR-based observations, the method proposed in the present study provides a complementary approach to achieve a higher total SCE mapping accuracy while maintaining global applicability with reliable accuracy and corresponding uncertainty Information.

Item URL in elib:https://elib.dlr.de/129203/
Document Type:Article
Title:Combination of PROBA-V/MODIS-based Products with Sentinel-1 SAR Data for Detecting Wet and Dry Snow Cover in Mountainous Areas
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Tsai, Ya-LunYa-Lun.Tsai (at) dlr.deUNSPECIFIED
Dietz, AndreasAndreas.Dietz (at) dlr.deUNSPECIFIED
Oppelt, NataschaLMU MünchenUNSPECIFIED
Künzer, Claudiaclaudia.kuenzer (at) dlr.deUNSPECIFIED
Journal or Publication Title:Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In ISI Web of Science:Yes
DOI :10.3390/rs11161904
Page Range:pp. 1-20
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
Keywords:Synthetic aperture radar; InSAR; PolSAR; backscatter; machine learning; snow cover area; land use land cover; Sentinel-2; Landsat
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: Dietz, Andreas
Deposited On:18 Sep 2019 10:02
Last Modified:14 Dec 2019 04:27

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