Wet snow depth from tandEM-X single-pass InSAR DEM differencing

Silvan Leinss, Oleg Antropov, Juho Vehviläinen, Juha Lemmetyinen, Irena Hajnsek, Jaan Praks

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

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 languageEnglish
Title of host publication2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018
PublisherIEEE Institute of Electrical and Electronic Engineers
Pages8500-8503
ISBN (Electronic)978-1-5386-7150-4, 978-1-5386-7149-8
ISBN (Print)978-1-5386-7151-1
DOIs
Publication statusPublished - 31 Oct 2018
MoE publication typeA4 Article in a conference publication
Event38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Valencia, Spain
Duration: 22 Jul 201827 Jul 2018

Publication series

SeriesIEEE International Geoscience and Remote Sensing Symposium Proceedings
Volume38
ISSN2153-6996

Conference

Conference38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018
CountrySpain
CityValencia
Period22/07/1827/07/18

Keywords

  • DEM differencing
  • DEM generation
  • Radar interferometry
  • Snow depth
  • TanDEM-X
  • Wet snow

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