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

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

Researchers

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

Research units

  • Swiss Federal Institute of Technology Zurich
  • Finnish Meteorological Institute
  • German Aerospace Center

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.

Details

Original languageEnglish
Title of host publicationIGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium
Publication statusPublished - 2018
MoE publication typeA4 Article in a conference publication
EventInternational Geoscience and Remote Sensing Symposium - Valencia, Spain
Duration: 22 Jul 201827 Jul 2018
Conference number: 38
https://www.igarss2018.org/

Publication series

NameIEEE International Symposium on Geoscience and Remote Sensing IGARSS
PublisherIEEE
ISSN (Print)2153-6996
ISSN (Electronic)2153-7003

Conference

ConferenceInternational Geoscience and Remote Sensing Symposium
Abbreviated titleIGARSS
CountrySpain
CityValencia
Period22/07/201827/07/2018
Internet address

    Research areas

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

ID: 31399515