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

Bartsch, Annett and Widhalm, Barbara and Leibman, Marina and Emorkhina, Ksenia and Kumpula, Timo and Skarin, Anna and Wilcox, Evan J. and Jones, Benjamin M. and Frost, Gerald V. and Höfler, Angelika and Pointner, Georg (2020). Feasibility of tundra vegetation height retrieval from Sentinel-1 and Sentinel-2 data. Remote Sensing of Environment. 237 , 1-19
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Abstract

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 C-VV 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.

Authors/Creators:Bartsch, Annett and Widhalm, Barbara and Leibman, Marina and Emorkhina, Ksenia and Kumpula, Timo and Skarin, Anna and Wilcox, Evan J. and Jones, Benjamin M. and Frost, Gerald V. and Höfler, Angelika and Pointner, Georg
Title:Feasibility of tundra vegetation height retrieval from Sentinel-1 and Sentinel-2 data
Year of publishing :2020
Volume:237
Page range:1-19
Number of Pages:19
Publisher:Elsevier
ISSN:0034-4257
Language:English
Publication Type:Journal article
Article category:Scientific peer reviewed
Version:Published version
Copyright:Creative Commons: Attribution 4.0
Full Text Status:Public
Subjects:(A) Swedish standard research categories 2011 > 2 Engineering and Technology > 207 Environmental Engineering > Remote Sensing
Keywords:Tundra, Vegetation, Shrubs, Radar, Optical
URN:NBN:urn:nbn:se:slu:epsilon-p-103186
Permanent URL:
http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-p-103186
Additional ID:
Type of IDID
DOI10.1016/j.rse.2019.111515
Web of Science (WoS)000509819300011
ID Code:16745
Faculty:VH - Faculty of Veterinary Medicine and Animal Science
Department:(VH) > Dept. of Animal Nutrition and Management
Deposited By: SLUpub Connector
Deposited On:14 Apr 2020 11:48
Metadata Last Modified:14 Apr 2020 11:48

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