Abstract

The timing of snowmelt is an important turning point in the seasonal cycle of small Arctic catchments. The TerraSAR-X (TSX) satellite mission is a synthetic aperture radar system (SAR) with high potential to measure the high spatiotemporal variability of snow cover extent (SCE) and fractional snow cover (FSC) on the small catchment scale. We investigate the performance of multi-polarized and multi-pass TSX X-Band SAR data in monitoring SCE and FSC in small Arctic tundra catchments of Qikiqtaruk (Herschel Island) off the Yukon Coast in the Western Canadian Arctic. We applied a threshold based segmentation on ratio images between TSX images with wet snow and a dry snow reference, and tested the performance of two different thresholds. We quantitatively compared TSX- and Landsat 8-derived SCE maps using confusion matrices and analyzed the spatiotemporal dynamics of snowmelt from 2015 to 2017 using TSX, Landsat 8 and in situ time lapse data. Our data showed that the quality of SCE maps from TSX X-Band data is strongly influenced by polarization and to a lesser degree by incidence angle. VH polarized TSX data performed best in deriving SCE when compared to Landsat 8. TSX derived SCE maps from VH polarization detected late lying snow patches that were not detected by Landsat 8. Results of a local assessment of TSX FSC against the in situ data showed that TSX FSC accurately captured the temporal dynamics of different snow melt regimes that were related to topographic characteristics of the studied catchments. Both in situ and TSX FSC showed a longer snowmelt period in a catchment with higher contributions of steep valleys and a shorter snowmelt period in a catchment with higher contributions of upland terrain. Landsat 8 had fundamental data gaps during the snowmelt period in all 3 years due to cloud cover. The results also revealed that by choosing a positive threshold of 1 dB, detection of ice layers due to diurnal temperature variations resulted in a more accurate estimation of snow cover than a negative threshold that detects wet snow alone. We find that TSX X-Band data in VH polarization performs at a comparable quality to Landsat 8 in deriving SCE maps when a positive threshold is used. We conclude that TSX data polarization can be used to accurately monitor snowmelt events at high temporal and spatial resolution, overcoming limitations of Landsat 8, which due to cloud related data gaps generally only indicated the onset and end of snowmelt.

Highlights

  • The evolution of snowmelt is a crucial component in the seasonal cycle of Arctic ecosystems; affecting temporal and spatial patterns of hydrology, vegetation, and biogeochemical processes

  • The results of this study highlight the potential of TerraSAR-X X-Band to improve and complement existing optical based snow cover products by increasing the temporal resolution of snow cover measurements

  • When we used common thresholds of −2 and −2.3 dB on TSX images, snow cover extent (SCE) was strongly underestimated when compared to Landsat 8 SCE maps, while a threshold of 1 dB produced very comparable results to Landsat 8 SCE

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Summary

Introduction

The evolution of snowmelt is a crucial component in the seasonal cycle of Arctic ecosystems; affecting temporal and spatial patterns of hydrology, vegetation, and biogeochemical processes. Late lying snow patches affect the soil moisture content and thermal properties of the active layer late in the season and create unique vegetation communities beneath and in their vicinity [8]. Both prolonged winter snow and late lying snow patch dynamics directly affect heterotrophic soil respiration and carbon cycling [6,9,10,11,12,13]. The monitoring of snowmelt at high spatial (30 m) and temporal scales (daily) is important to better understand the impacts of changing SCE on the abiotic and biotic functioning of small catchments in a rapidly changing Arctic. The snowmelt period is a logistically challenging time in Arctic regions to conduct in situ work because of unstable sea and river ice conditions as well as very wet ground surfaces due to snowmelt and permafrost thaw

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