Wet Snow Depth from Tandem-X Single-Pass Insar Dem Differencing

Silvan Leinss; Oleg Antropov; Juho Vehvilainen; Juha Lemmetyinen; Irena Hajnsek; Jaan Praks

doi:10.1109/IGARSS.2018.8518661

Wet Snow Depth from Tandem-X Single-Pass Insar Dem Differencing

Silvan Leinss^*, Oleg Antropov, Juho Vehvilainen, Juha Lemmetyinen, Irena Hajnsek, Jaan Praks

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

3 Citations (Scopus)

Abstract

Single pass radar interferometry (sp-InSAR) is a well established technique for generation of digital elevation models (DEM). Differencing two DEMs acquired at different times can reveal topographic changes. However snow depth estimation by DEM differencing is still an ongoing topic in radar research: in contrast to snow free surfaces, the snow surface elevation is difficult to detect either because of microwave penetration into dry snow or because of the weak backscatter return from wet snow which significantly decorrelates the interferometric signal. In this study we demonstrate first results of wet snow depth estimation by differencing sp-InSAR DEMs acquired by the TanDEM-X satellite mission. The results show, in contrast to dry snow, a clear sensitivity to wet snow. However, additionally to a high vertical sensitivity of a few ten centimeters a very low noise-equivalent-sigma-zero (NESZ) is crucial for successful snow depth estimation.

Original language	English
Title of host publication	IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium
Publisher	IEEE
Pages	8500-8503
Number of pages	4
ISBN (Electronic)	978-1-5386-7150-4
ISBN (Print)	978-1-5386-7151-1
DOIs	https://doi.org/10.1109/IGARSS.2018.8518661
Publication status	Published - 2018
MoE publication type	A4 Article in a conference publication
Event	International Geoscience and Remote Sensing Symposium - Valencia, Spain Duration: 22 Jul 2018 → 27 Jul 2018 Conference number: 38 https://www.igarss2018.org/

Publication series

Name	IEEE International Symposium on Geoscience and Remote Sensing IGARSS
Publisher	IEEE
ISSN (Print)	2153-6996
ISSN (Electronic)	2153-7003

Conference

Conference	International Geoscience and Remote Sensing Symposium
Abbreviated title	IGARSS
Country/Territory	Spain
City	Valencia
Period	22/07/2018 → 27/07/2018
Internet address	https://www.igarss2018.org/

Keywords

snow depth
wet snow
TanDEM-X
radar interferometry
DEM generation
DEM differencing
CLIMATE

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10.1109/IGARSS.2018.8518661

https://elib.dlr.de/127342/1/08518661.pdf

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Leinss, S., Antropov, O., Vehvilainen, J., Lemmetyinen, J., Hajnsek, I., & Praks, J. (2018). Wet Snow Depth from Tandem-X Single-Pass Insar Dem Differencing. In IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium (pp. 8500-8503). (IEEE International Symposium on Geoscience and Remote Sensing IGARSS). IEEE. https://doi.org/10.1109/IGARSS.2018.8518661

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abstract = "Single pass radar interferometry (sp-InSAR) is a well established technique for generation of digital elevation models (DEM). Differencing two DEMs acquired at different times can reveal topographic changes. However snow depth estimation by DEM differencing is still an ongoing topic in radar research: in contrast to snow free surfaces, the snow surface elevation is difficult to detect either because of microwave penetration into dry snow or because of the weak backscatter return from wet snow which significantly decorrelates the interferometric signal. In this study we demonstrate first results of wet snow depth estimation by differencing sp-InSAR DEMs acquired by the TanDEM-X satellite mission. The results show, in contrast to dry snow, a clear sensitivity to wet snow. However, additionally to a high vertical sensitivity of a few ten centimeters a very low noise-equivalent-sigma-zero (NESZ) is crucial for successful snow depth estimation.",

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author = "Silvan Leinss and Oleg Antropov and Juho Vehvilainen and Juha Lemmetyinen and Irena Hajnsek and Jaan Praks",

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Leinss, S, Antropov, O, Vehvilainen, J, Lemmetyinen, J, Hajnsek, I & Praks, J 2018, Wet Snow Depth from Tandem-X Single-Pass Insar Dem Differencing. in IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. IEEE International Symposium on Geoscience and Remote Sensing IGARSS, IEEE, pp. 8500-8503, International Geoscience and Remote Sensing Symposium, Valencia, Spain, 22/07/2018. https://doi.org/10.1109/IGARSS.2018.8518661

Wet Snow Depth from Tandem-X Single-Pass Insar Dem Differencing. / Leinss, Silvan; Antropov, Oleg; Vehvilainen, Juho et al.

IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2018. p. 8500-8503 (IEEE International Symposium on Geoscience and Remote Sensing IGARSS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

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AU - Leinss, Silvan

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AU - Vehvilainen, Juho

AU - Lemmetyinen, Juha

AU - Hajnsek, Irena

AU - Praks, Jaan

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N2 - Single pass radar interferometry (sp-InSAR) is a well established technique for generation of digital elevation models (DEM). Differencing two DEMs acquired at different times can reveal topographic changes. However snow depth estimation by DEM differencing is still an ongoing topic in radar research: in contrast to snow free surfaces, the snow surface elevation is difficult to detect either because of microwave penetration into dry snow or because of the weak backscatter return from wet snow which significantly decorrelates the interferometric signal. In this study we demonstrate first results of wet snow depth estimation by differencing sp-InSAR DEMs acquired by the TanDEM-X satellite mission. The results show, in contrast to dry snow, a clear sensitivity to wet snow. However, additionally to a high vertical sensitivity of a few ten centimeters a very low noise-equivalent-sigma-zero (NESZ) is crucial for successful snow depth estimation.

AB - Single pass radar interferometry (sp-InSAR) is a well established technique for generation of digital elevation models (DEM). Differencing two DEMs acquired at different times can reveal topographic changes. However snow depth estimation by DEM differencing is still an ongoing topic in radar research: in contrast to snow free surfaces, the snow surface elevation is difficult to detect either because of microwave penetration into dry snow or because of the weak backscatter return from wet snow which significantly decorrelates the interferometric signal. In this study we demonstrate first results of wet snow depth estimation by differencing sp-InSAR DEMs acquired by the TanDEM-X satellite mission. The results show, in contrast to dry snow, a clear sensitivity to wet snow. However, additionally to a high vertical sensitivity of a few ten centimeters a very low noise-equivalent-sigma-zero (NESZ) is crucial for successful snow depth estimation.

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ER -

Wet Snow Depth from Tandem-X Single-Pass Insar Dem Differencing

Abstract

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Keywords

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