Exploring the seasonality of rapid Arctic changes from space - Monitoring of permafrost disturbance, snow cover and vegetation in trundra environments with TerraSAR-X

Arctic warming has implications for the functioning of terrestrial Arctic ecosystems, global climate and socioeconomic systems of northern communities. A research gap exists in high spatial resolution monitoring and understanding of the seasonality of permafrost degradation, spring snowmelt and vege...

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Bibliographic Details
Main Author: Stettner, Samuel
Format: Thesis
Language:unknown
Published: University of Potsdam 2019
Subjects:
Ice
Online Access:https://epic.awi.de/id/eprint/50496/
https://publishup.uni-potsdam.de/frontdoor/index/index/docId/42578
https://hdl.handle.net/10013/epic.fbb347be-eb36-4252-8425-5d3395b7267f
id ftawi:oai:epic.awi.de:50496
record_format openpolar
institution Open Polar
collection Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center)
op_collection_id ftawi
language unknown
description Arctic warming has implications for the functioning of terrestrial Arctic ecosystems, global climate and socioeconomic systems of northern communities. A research gap exists in high spatial resolution monitoring and understanding of the seasonality of permafrost degradation, spring snowmelt and vegetation phenology. This thesis explores the diversity and utility of dense TerraSAR-X (TSX) X-Band time series for monitoring ice-rich riverbank erosion, snowmelt, and phenology of Arctic vegetation at long-term study sites in the central Lena Delta, Russia and on Qikiqtaruk (Herschel Island), Canada. In the thesis the following three research questions are addressed: • Is TSX time series capable of monitoring the dynamics of rapid permafrost degradation in ice-rich permafrost on an intra-seasonal scale and can these datasets in combination with climate data identify the climatic drivers of permafrost degradation? • Can multi-pass and multi-polarized TSX time series adequately monitor seasonal snow cover and snowmelt in small Arctic catchments and how does it perform compared to optical satellite data and field-based measurements? • Do TSX time series reflect the phenology of Arctic vegetation and how does the recorded signal compare to in-situ greenness data from RGB time-lapse camera data and vegetation height from field surveys? To answer the research questions three years of TSX backscatter data from 2013 to 2015 for the Lena Delta study site and from 2015 to 2017 for the Qikiqtaruk study site were used in quantitative and qualitative analysis complimentary with optical satellite data and in-situ time-lapse imagery. The dynamics of intra-seasonal ice-rich riverbank erosion in the central Lena Delta, Russia were quantified using TSX backscatter data at 2.4 m spatial resolution in HH polarization and validated with 0.5 m spatial resolution optical satellite data and field-based time-lapse camera data. Cliff top lines were automatically extracted from TSX intensity images using threshold-based segmentation and vectorization and combined in a geoinformation system with manually digitized cliff top lines from the optical satellite data and rates of erosion extracted from time-lapse cameras. The results suggest that the cliff top eroded at a constant rate throughout the entire erosional season. Linear mixed models confirmed that erosion was coupled with air temperature and precipitation at an annual scale, seasonal fluctuations did not influence 22-day erosion rates. The results highlight the potential of HH polarized X-Band backscatter data for high temporal resolution monitoring of rapid permafrost degradation. The distinct signature of wet snow in backscatter intensity images of TSX data was exploited to generate wet snow cover extent (SCE) maps on Qikiqtaruk at high temporal resolution. TSX SCE showed high similarity to Landsat 8-derived SCE when using cross-polarized VH data. Fractional snow cover (FSC) time series were extracted from TSX and optical SCE and compared to FSC estimations from in-situ time-lapse imagery. The TSX products showed strong agreement with the in-situ data and significantly improved the temporal resolution compared to the Landsat 8 time series. The final combined FSC time series revealed two topography-dependent snowmelt patterns that corresponded to in-situ measurements. Additionally TSX was able to detect snow patches longer in the season than Landsat 8, underlining the advantage of TSX for detection of old snow. The TSX-derived snow information provided valuable insights into snowmelt dynamics on Qikiqtaruk previously not available. The sensitivity of TSX to vegetation structure associated with phenological changes was explored on Qikiqtaruk. Backscatter and coherence time series were compared to greenness data extracted from in-situ digital time-lapse cameras and detailed vegetation parameters on 30 areas of interest. Supporting previous results, vegetation height corresponded to backscatter intensity in co-polarized HH/VV at an incidence angle of 31°. The dry, tall shrub dominated ecological class showed increasing backscatter with increasing greenness when using the cross polarized VH/HH channel at 32° incidence angle. This is likely driven by volume scattering of emerging and expanding leaves. Ecological classes with more prostrate vegetation and higher bare ground contributions showed decreasing backscatter trends over the growing season in the co-polarized VV/HH channels likely a result of surface drying instead of a vegetation structure signal. The results from shrub dominated areas are promising and provide a complementary data source for high temporal monitoring of vegetation phenology. Overall this thesis demonstrates that dense time series of TSX with optical remote sensing and in-situ time-lapse data are complementary and can be used to monitor rapid and seasonal processes in Arctic landscapes at high spatial and temporal resolution.
format Thesis
author Stettner, Samuel
spellingShingle Stettner, Samuel
Exploring the seasonality of rapid Arctic changes from space - Monitoring of permafrost disturbance, snow cover and vegetation in trundra environments with TerraSAR-X
author_facet Stettner, Samuel
author_sort Stettner, Samuel
title Exploring the seasonality of rapid Arctic changes from space - Monitoring of permafrost disturbance, snow cover and vegetation in trundra environments with TerraSAR-X
title_short Exploring the seasonality of rapid Arctic changes from space - Monitoring of permafrost disturbance, snow cover and vegetation in trundra environments with TerraSAR-X
title_full Exploring the seasonality of rapid Arctic changes from space - Monitoring of permafrost disturbance, snow cover and vegetation in trundra environments with TerraSAR-X
title_fullStr Exploring the seasonality of rapid Arctic changes from space - Monitoring of permafrost disturbance, snow cover and vegetation in trundra environments with TerraSAR-X
title_full_unstemmed Exploring the seasonality of rapid Arctic changes from space - Monitoring of permafrost disturbance, snow cover and vegetation in trundra environments with TerraSAR-X
title_sort exploring the seasonality of rapid arctic changes from space - monitoring of permafrost disturbance, snow cover and vegetation in trundra environments with terrasar-x
publisher University of Potsdam
publishDate 2019
url https://epic.awi.de/id/eprint/50496/
https://publishup.uni-potsdam.de/frontdoor/index/index/docId/42578
https://hdl.handle.net/10013/epic.fbb347be-eb36-4252-8425-5d3395b7267f
long_lat ENVELOPE(-139.089,-139.089,69.583,69.583)
geographic Arctic
Canada
Herschel Island
geographic_facet Arctic
Canada
Herschel Island
genre Arctic
Arctic
Herschel Island
Ice
lena delta
permafrost
genre_facet Arctic
Arctic
Herschel Island
Ice
lena delta
permafrost
op_source EPIC3University of Potsdam
op_relation Stettner, S. orcid:0000-0001-5278-7931 (2019) Exploring the seasonality of rapid Arctic changes from space - Monitoring of permafrost disturbance, snow cover and vegetation in trundra environments with TerraSAR-X , PhD thesis, University of Potsdam. doi:10.25932/publishup-42578 <https://doi.org/10.25932/publishup-42578> , hdl:10013/epic.fbb347be-eb36-4252-8425-5d3395b7267f
op_doi https://doi.org/10.25932/publishup-42578
_version_ 1766298575323529216
spelling ftawi:oai:epic.awi.de:50496 2023-05-15T14:26:06+02:00 Exploring the seasonality of rapid Arctic changes from space - Monitoring of permafrost disturbance, snow cover and vegetation in trundra environments with TerraSAR-X Stettner, Samuel 2019-02-04 https://epic.awi.de/id/eprint/50496/ https://publishup.uni-potsdam.de/frontdoor/index/index/docId/42578 https://hdl.handle.net/10013/epic.fbb347be-eb36-4252-8425-5d3395b7267f unknown University of Potsdam Stettner, S. orcid:0000-0001-5278-7931 (2019) Exploring the seasonality of rapid Arctic changes from space - Monitoring of permafrost disturbance, snow cover and vegetation in trundra environments with TerraSAR-X , PhD thesis, University of Potsdam. doi:10.25932/publishup-42578 <https://doi.org/10.25932/publishup-42578> , hdl:10013/epic.fbb347be-eb36-4252-8425-5d3395b7267f EPIC3University of Potsdam Thesis notRev 2019 ftawi https://doi.org/10.25932/publishup-42578 2021-12-24T15:45:01Z Arctic warming has implications for the functioning of terrestrial Arctic ecosystems, global climate and socioeconomic systems of northern communities. A research gap exists in high spatial resolution monitoring and understanding of the seasonality of permafrost degradation, spring snowmelt and vegetation phenology. This thesis explores the diversity and utility of dense TerraSAR-X (TSX) X-Band time series for monitoring ice-rich riverbank erosion, snowmelt, and phenology of Arctic vegetation at long-term study sites in the central Lena Delta, Russia and on Qikiqtaruk (Herschel Island), Canada. In the thesis the following three research questions are addressed: • Is TSX time series capable of monitoring the dynamics of rapid permafrost degradation in ice-rich permafrost on an intra-seasonal scale and can these datasets in combination with climate data identify the climatic drivers of permafrost degradation? • Can multi-pass and multi-polarized TSX time series adequately monitor seasonal snow cover and snowmelt in small Arctic catchments and how does it perform compared to optical satellite data and field-based measurements? • Do TSX time series reflect the phenology of Arctic vegetation and how does the recorded signal compare to in-situ greenness data from RGB time-lapse camera data and vegetation height from field surveys? To answer the research questions three years of TSX backscatter data from 2013 to 2015 for the Lena Delta study site and from 2015 to 2017 for the Qikiqtaruk study site were used in quantitative and qualitative analysis complimentary with optical satellite data and in-situ time-lapse imagery. The dynamics of intra-seasonal ice-rich riverbank erosion in the central Lena Delta, Russia were quantified using TSX backscatter data at 2.4 m spatial resolution in HH polarization and validated with 0.5 m spatial resolution optical satellite data and field-based time-lapse camera data. Cliff top lines were automatically extracted from TSX intensity images using threshold-based segmentation and vectorization and combined in a geoinformation system with manually digitized cliff top lines from the optical satellite data and rates of erosion extracted from time-lapse cameras. The results suggest that the cliff top eroded at a constant rate throughout the entire erosional season. Linear mixed models confirmed that erosion was coupled with air temperature and precipitation at an annual scale, seasonal fluctuations did not influence 22-day erosion rates. The results highlight the potential of HH polarized X-Band backscatter data for high temporal resolution monitoring of rapid permafrost degradation. The distinct signature of wet snow in backscatter intensity images of TSX data was exploited to generate wet snow cover extent (SCE) maps on Qikiqtaruk at high temporal resolution. TSX SCE showed high similarity to Landsat 8-derived SCE when using cross-polarized VH data. Fractional snow cover (FSC) time series were extracted from TSX and optical SCE and compared to FSC estimations from in-situ time-lapse imagery. The TSX products showed strong agreement with the in-situ data and significantly improved the temporal resolution compared to the Landsat 8 time series. The final combined FSC time series revealed two topography-dependent snowmelt patterns that corresponded to in-situ measurements. Additionally TSX was able to detect snow patches longer in the season than Landsat 8, underlining the advantage of TSX for detection of old snow. The TSX-derived snow information provided valuable insights into snowmelt dynamics on Qikiqtaruk previously not available. The sensitivity of TSX to vegetation structure associated with phenological changes was explored on Qikiqtaruk. Backscatter and coherence time series were compared to greenness data extracted from in-situ digital time-lapse cameras and detailed vegetation parameters on 30 areas of interest. Supporting previous results, vegetation height corresponded to backscatter intensity in co-polarized HH/VV at an incidence angle of 31°. The dry, tall shrub dominated ecological class showed increasing backscatter with increasing greenness when using the cross polarized VH/HH channel at 32° incidence angle. This is likely driven by volume scattering of emerging and expanding leaves. Ecological classes with more prostrate vegetation and higher bare ground contributions showed decreasing backscatter trends over the growing season in the co-polarized VV/HH channels likely a result of surface drying instead of a vegetation structure signal. The results from shrub dominated areas are promising and provide a complementary data source for high temporal monitoring of vegetation phenology. Overall this thesis demonstrates that dense time series of TSX with optical remote sensing and in-situ time-lapse data are complementary and can be used to monitor rapid and seasonal processes in Arctic landscapes at high spatial and temporal resolution. Thesis Arctic Arctic Herschel Island Ice lena delta permafrost Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center) Arctic Canada Herschel Island ENVELOPE(-139.089,-139.089,69.583,69.583)