Published December 9, 2019 | Version v1
Journal article Open

Feasibility of tundra vegetation height retrieval from Sentinel-1 and Sentinel-2 data

  • 1. b.geos
  • 2. ZAMG
  • 3. Earth Cryosphere Institute, Tyumen Scientific Centre SB RAS
  • 4. b.geos, Korneuburg, Austria d Earth Cryosphere Institute, Tyumen Scientific Centre SB RAS
  • 5. University of Eastern Finland, Joensuu, Finland
  • 6. Swedish University of Agricultural Sciences, Uppsala, Sweden
  • 7. Cold Regions Research Centre, Wilfrid Laurier University, Waterloo, Ontario, Canada
  • 8. Water and Environmental Research Centre, University of Alaska Fairbanks, AK, USA
  • 9. Alaska Biological Research, Inc., ––Environmental Research & Services, Fairbanks, AK, USA

Description

The quantification of vegetation height for the circumpolar Arctic tundra biome is of interest for a wide range of applications, including biomass and habitat studies as well as permafrost modelling in the context of climate change. To date, only indices from multispectral data have been used in these environments to address biomass and vegetation changes over time. The retrieval of vegetation height itself has not been attempted so far over larger areas. Synthetic Aperture Radar (SAR) holds promise for canopy modeling over large extents, but the high variability of near-surface soil moisture during the snow-free season is a major challenge for application of SAR in tundra for such a purpose. We hypothesized that tundra vegetation height can be derived from multispectral
indices as well as from C-band SAR data acquired in winter (close to zero liquid water content). To test our hypothesis, we used C-band SAR data from Sentinel-1 and multi-spectral data from Sentinel-2. Results show that vegetation height can be derived with an RMSE of 44 cm from Normalized Difference Vegetation Index (NDVI) and 54 cm from Tasseled Cap Wetness index (TC). Retrieval from C-band SAR shows similar performance, but CVV is more suitable than C-HH to derive vegetation height (RMSEs of 48 and 56 cm respectively). An exponential relationship with in situ height was evident for all tested parameters (NDVI, TC, C-VV and C-HH) suggesting that the C-band SAR and multi-spectral approaches possess similar capabilities including tundra biomass retrieval.
Errors might occur in specific settings as a result of high surface roughness, high photosynthetic activity in wetlands or high snow density. We therefore introduce a method for combined use of Sentinel-1 and Sentinel-2 to address the ambiguities related to Arctic wetlands and barren rockfields. Snow-related deviations occur within tundra fire scars in permafrost areas in the case of C-VV use. The impact decreases with age of the fire scar, following permafrost and vegetation recovery. The evaluation of masked C-VV retrievals across different regions, tundra types and sources (in situ and circumpolar vegetation community classification from satellite data) suggests pan-Arctic applicability to map current conditions for heights up to 160 cm. The presented methodology
will allow for new applications and provide advanced insight into changing environmental conditions in the Arctic.

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Additional details

Related works

Is supplemented by
Dataset: 10.1594/PANGAEA.897045 (DOI)
References
Dataset: 10.1594/PANGAEA.897046 (DOI)
Journal article: 10.3390/rs10040551 (DOI)

Funding

Permafrost monitoring on Yamal I 1401
FWF Austrian Science Fund
Nunataryuk – Permafrost thaw and the changing arctic coast: science for socio-economic adaptation 773421
European Commission