Detection of snow change using polarimetric TerraSAR-X time-series (Svalbard, Norway)

• Main Authors: Dedieu, Jean-Pierre, Wendleder, Anna, Vauclare, Simon, Momber, Marion, Bernard, Eric, Boike, Julia, Jacobi, Hans-Werner
• Format: Conference Object
• Language: unknown
• Published: 2023
• Subjects: Internationales Bodensegment; Arctic; Norway; Ny-Ålesund; Svalbard; Climate change; Ny Ålesund; polar night
• Online Access: https://elib.dlr.de/199486/

Due to recent climate change conditions, i.e. increasing temperatures and changing precipitation patterns, arctic snow cover dynamics exhibit strong changes in terms of extent and duration. Arctic amplification processes and impacts are well documented expected to strengthen in coming decades. In this context, innovative observation methods are helpful for a better comprehension of the spatial variability of snow properties relevant for climate research and hydrological applications. Microwave remote sensing provides exceptional spatial and temporal performance in terms of all-weather application and target penetration. Time-series of Synthetic Active Radar images (SAR) are becoming more accessible at different frequencies and polarimetry has demonstrated a significant advantage for detecting changes in different media. Concerning arctic snow monitoring, SAR sensors can offer continuous time-series during the polar night and with cloud cover, providing a consequent advantage in regard of optical sensors. The aim of this study is dedicated to the spatial and temporal variability of snow in the Ny-Ålesund area on the BrØgger peninsula, Svalbard (N 78°55’ / E 11° 55’) using a high temporal TerraSAR-X Stripmap time series from November 2018 to June 2022, providing four consecutive winter datasets. The dual-cross polarized (HH/VV) SAR data were acquired from two different orbits (ascending and descending) with high incidence angles (36° to 39°) increasing snow volume backscattering and reducing topographic constraints. Additionally, a high spatial resolution Digital Elevation Model (NPI 5-m), consistent in-situ measurements of meteorological data, and snow profiles including lowlands and glaciers sites are available. Polarimetric processing is based on the Kennaugh matrix decomposition, co-polar phase coherence (CCOH) and co-polar phase difference (CPD). The Kennaugh matrix elements K0, K3, K4, and K7 are the total intensity, phase ratio, intensity ratio, and shift between HH and VV phase center, respectively. Their ...