Award Abstract # 1722572
COLLABORATIVE RESEARCH: Patterns, Dynamics, and Vulnerability of Arctic Polygonal Ecosystems: From Ice-Wedge Polygon to Pan-Arctic Landscapes

NSF Org: OPP
Office of Polar Programs (OPP)
Recipient: UNIVERSITY OF ALASKA FAIRBANKS
Initial Amendment Date: April 11, 2017
Latest Amendment Date: April 11, 2017
Award Number: 1722572
Award Instrument: Standard Grant
Program Manager: Gregory Anderson
greander@nsf.gov
 (703)292-4693
OPP
 Office of Polar Programs (OPP)
GEO
 Directorate for Geosciences
Start Date: January 1, 2018
End Date: October 31, 2020 (Estimated)
Total Intended Award Amount: $737,388.00
Total Awarded Amount to Date: $737,388.00
Funds Obligated to Date: FY 2017 = $420,461.00
History of Investigator:
  • Anna Liljedahl (Principal Investigator)
    aliljedahl@woodwellclimate.org
  • Mikhail Kanevskiy (Co-Principal Investigator)
Recipient Sponsored Research Office: University of Alaska Fairbanks Campus
2145 N TANANA LOOP
FAIRBANKS
AK  US  99775-0001
(907)474-7301
Sponsor Congressional District: 00
Primary Place of Performance: University of Alaska Fairbanks Campus
Fairbanks
AK  US  99775-7880
Primary Place of Performance
Congressional District:
00
Unique Entity Identifier (UEI): FDLEQSJ8FF63
Parent UEI:
NSF Program(s): ARCSS-Arctic System Science
Primary Program Source: 0100XXXXDB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 1079
Program Element Code(s): 521900
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.078

ABSTRACT

The warming Arctic is reshaping the tundra landscape as ground-ice that is thousands of years old thaws, resulting in differential ground settlement that alters the distribution of water and snow in a region with desert-like precipitation. Field measurements across the Arctic have documented long-term and gradual warming of permafrost and recently the observations have also included rapid ice-wedge degradation in response to a single and unusually warm summer. The goal of this project is to understand the complex and interlinked processes responsible for the evolution of the pan-Arctic ice-wedge polygon tundra landscape by combining field measurements from nine Canadian, Russian, and Alaskan field sites, numerical modeling, and very high spatial resolution optical imagery that has recently become available for the entire Arctic tundra domain.

A combination of detailed imagery and advanced processing algorithms will allow pan-Arctic mapping of ice-wedge polygon extent and types (low- and high-centered). A map of that extent and detail does not yet exisxt, but is necessary to link carbon, water, and energy processes occurring at the ice-wedge polygon scale to the larger Arctic land-ocean-atmosphere system. Currently, permafrost thaw and subsequent carbon release is, at best, described in global models via gradual increases in active layer thickness, while field observations clearly show additional dramatic changes to the tundra ecosystem due to rapid differential ground subsidence as ice-wedges melt. A low-centered polygon landscape, which evolved over several thousand years via the slow process of ice-wedge growth, can harbor a sea of shallow ponds throughout the summer that supports a myriad of migratory birds during the breeding season. In just two years, the scene could change dramatically with exposed dry mounds where the shallow water bodies once were, while the surface water area can shrink into narrow elongated beads of deeper ponds above the melted ice-wedges. A complicated set of sub-polygon to watershed scale responses will determine the fate of the landscape. These mechanisms, part of the soil-vegetation-water continuum, will be defined via a numerical biogeophysical model informed by field measurements and repeat imagery of ice-wedge evolution. The new knowledge will support the research community in refining the role of the Arctic in the global climate system.

Broader impacts of this project include training of the new generation of Arctic researchers by supporting a graduate student, a post-doctoral fellow, and an early-career scientist. Fairbanks, Alaska, the base for several of the investigators, offers an excellent opportunity to show K-12 students the results of ice-wedge degradation. The products, such as the maps of ice-wedge polygon types and the projected transformation of the vegetation, water, and topography, are at spatial and temporal scales that are relevant to managers. Digital maps of ice-wedge polygon type and ground-ice estimates will be given to state and federal agencies operating in Alaska in a half-day workshop along with ice-wedge polygon ecosystem projections. The information could inform management decisions about habitat protection, or surface-water dependent oil and gas exploration activities. There will also be support for field travel for a journalist and a photographer.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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(Showing: 1 - 10 of 12)
Bhuiyan, Md Abul and Witharana, Chandi and Liljedahl, Anna K. "Use of Very High Spatial Resolution Commercial Satellite Imagery and Deep Learning to Automatically Map Ice-Wedge Polygons across Tundra Vegetation Types" Journal of Imaging , v.6 , 2020 https://doi.org/10.3390/jimaging6120137 Citation Details
Bhuiyan, Md Abul and Witharana, Chandi and Liljedahl, Anna K. and Jones, Benjamin M. and Daanen, Ronald and Epstein, Howard E. and Kent, Kelcy and Griffin, Claire G. and Agnew, Amber "Understanding the Effects of Optimal Combination of Spectral Bands on Deep Learning Model Predictions: A Case Study Based on Permafrost Tundra Landform Mapping Using High Resolution Multispectral Satellite Imagery" Journal of Imaging , v.6 , 2020 https://doi.org/10.3390/jimaging6090097 Citation Details
Hasan, A. and Udawalpola, M. R. and Witharana, C. and Liljedahl, A. K. "COUNTING ICE-WEDGE POLYGONS FROM SPACE: USE OF COMMERCIAL SATELLITE IMAGERY TO MONITOR CHANGING ARCTIC POLYGONAL TUNDRA" The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences , v.XLIV-M- , 2021 https://doi.org/10.5194/isprs-archives-XLIV-M-3-2021-67-2021 Citation Details
Hasan, Amit and Udawalpola, Mahendra and Liljedahl, Anna and Witharana, Chandi "Use of Commercial Satellite Imagery to Monitor Changing Arctic Polygonal Tundra" Photogrammetric Engineering & Remote Sensing , v.88 , 2022 https://doi.org/10.14358/PERS.21-00061R2 Citation Details
Jorgenson, M.T. and Kanevskiy, M.Z. and Jorgenson, J.C. and Liljedahl, A. and Shur, Y. and Epstein, H. and Kent, K. and Griffin, C.G. and Daanen, R. and Boldenow, M. and Orndahl, K. and Witharana, C. and Jones, B.M. "Rapid transformation of tundra ecosystems from ice-wedge degradation" Global and Planetary Change , 2022 https://doi.org/10.1016/j.gloplacha.2022.103921 Citation Details
Kanevskiy, Mikhail and Shur, Yuri and (Skip) Walker, D.A. and Jorgenson, Torre and Raynolds, Martha K. and Peirce, Jana L. and Jones, Benjamin M. and Buchhorn, Marcel and Matyshak, Georgiy and Bergstedt, Helena and Breen, Amy L. and Connor, Billy and Daan "The shifting mosaic of ice-wedge degradation and stabilization in response to infrastructure and climate change, Prudhoe Bay Oilfield, Alaska, USA" Arctic Science , v.8 , 2022 https://doi.org/10.1139/as-2021-0024 Citation Details
Udawalpola, Mahendra R. and Hasan, Amit and Liljedahl, Anna and Soliman, Aiman and Terstriep, Jeffrey and Witharana, Chandi "An Optimal GeoAI Workflow for Pan-Arctic Permafrost Feature Detection from High-Resolution Satellite Imagery" Photogrammetric Engineering & Remote Sensing , v.88 , 2022 https://doi.org/10.14358/PERS.21-00059R2 Citation Details
Udawalpola, M. and Hasan, A. and Liljedahl, A. K. and Soliman, A. and Witharana, C. "OPERATIONAL-SCALE GEOAI FOR PAN-ARCTIC PERMAFROST FEATURE DETECTION FROM HIGH-RESOLUTION SATELLITE IMAGERY" The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences , v.XLIV-M- , 2021 https://doi.org/10.5194/isprs-archives-XLIV-M-3-2021-175-2021 Citation Details
Witharana, C. and Bhuiyan, M. A. and Liljedahl, A. K. "BIG IMAGERY AND HIGH PERFORMANCE COMPUTING AS RESOURCES TO UNDERSTAND CHANGING ARCTIC POLYGONAL TUNDRA" The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences , v.XLIV-M- , 2020 https://doi.org/10.5194/isprs-archives-XLIV-M-2-2020-111-2020 Citation Details
Witharana, Chandi and Bhuiyan, Md Abul and Liljedahl, Anna K. and Kanevskiy, Mikhail and Epstein, Howard E. and Jones, Benjamin M. and Daanen, Ronald and Griffin, Claire G. and Kent, Kelcy and Ward Jones, Melissa K. "Understanding the synergies of deep learning and data fusion of multispectral and panchromatic high resolution commercial satellite imagery for automated ice-wedge polygon detection" ISPRS Journal of Photogrammetry and Remote Sensing , v.170 , 2020 https://doi.org/10.1016/j.isprsjprs.2020.10.010 Citation Details
Witharana, Chandi and Bhuiyan, Md Abul and Liljedahl, Anna K. and Kanevskiy, Mikhail and Jorgenson, Torre and Jones, Benjamin M. and Daanen, Ronald and Epstein, Howard E. and Griffin, Claire G. and Kent, Kelcy and Ward Jones, Melissa K. "An Object-Based Approach for Mapping Tundra Ice-Wedge Polygon Troughs from Very High Spatial Resolution Optical Satellite Imagery" Remote Sensing , v.13 , 2021 https://doi.org/10.3390/rs13040558 Citation Details
(Showing: 1 - 10 of 12)

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