@inproceedings{0d97ad71b0444d9c94a68c689d178177,
title = "Wet snow depth from tandEM-X single-pass InSAR DEM differencing",
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.",
keywords = "DEM differencing, DEM generation, Radar interferometry, Snow depth, TanDEM-X, Wet snow",
author = "Silvan Leinss and Oleg Antropov and Juho Vehvil{\"a}inen and Juha Lemmetyinen and Irena Hajnsek and Jaan Praks",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE Copyright: Copyright 2019 Elsevier B.V., All rights reserved.; 38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018, IGARSS ; Conference date: 22-07-2018 Through 27-07-2018",
year = "2018",
month = oct,
day = "31",
doi = "10.1109/IGARSS.2018.8518661",
language = "English",
isbn = "978-1-5386-7151-1",
series = "IEEE International Geoscience and Remote Sensing Symposium Proceedings",
publisher = "IEEE Institute of Electrical and Electronic Engineers",
pages = "8500--8503",
booktitle = "2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018",
address = "United States",
}