Randi Jandt

University of Alaska Fairbanks

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Eric A. Miller

University of Guelph

Tatiana Loboda

University of Maryland, College Park

Michelle C. Mack

Northern Arizona University

Benjamin Jones

University of Alaska Fairbanks

Teresa N. Hollingsworth

University of Alaska Fairbanks

Nancy H. F. French

Michigan Technological University

Amy Breen

University of Alaska Fairbanks

S. J. Goetz

Northern Arizona University

Dong Chen

University of Maryland, College Park

Gerald V. Frost

Alaska Biological Research (United States)

Cooperative Institutions

University of Alaska Fairbanks

United States Geological Survey

Goddard Space Flight Center

University of Maryland, College Park

National Aeronautics and Space Administration

University of Florida

Woodwell Climate Research Center

Ecological Society of America

International Arctic Research Center

University of Helsinki

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Hyperspectral Data Simulation (Sentinel-2 to AVIRIS-NG) for Improved Wildfire Fuel Mapping, Boreal Alaska

Remote Sensing (2021)

Anushree Badola Santosh K. Panda Dar A. Roberts Christine F. Waigl Uma S. Bhatt

Alaska has witnessed a significant increase in wildfire events in recent decades that have been linked to drier and warmer summers. Forest fuel maps play a vital role in wildfire management and risk assessment. Freely available multispectral datasets are widely used for land use and land cover mapping, but they have limited utility for fuel mapping due to their coarse spectral resolution. Hyperspectral datasets have a high spectral resolution, ideal for detailed fuel mapping, but they are limited and expensive to acquire. This study simulates hyperspectral data from Sentinel-2 multispectral data using the spectral response function of the Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) sensor, and normalized ground spectra of gravel, birch, and spruce. We used the Uniform Pattern Decomposition Method (UPDM) for spectral unmixing, which is a sensor-independent method, where each pixel is expressed as the linear sum of standard reference spectra. The simulated hyperspectral data have spectral characteristics of AVIRIS-NG and the reflectance properties of Sentinel-2 data. We validated the simulated spectra by visually and statistically comparing it with real AVIRIS-NG data. We observed a high correlation between the spectra of tree classes collected from AVIRIS-NG and simulated hyperspectral data. Upon performing species level classification, we achieved a classification accuracy of 89% for the simulated hyperspectral data, which is better than the accuracy of Sentinel-2 data (77.8%). We generated a fuel map from the simulated hyperspectral image using the Random Forest classifier. Our study demonstrated that low-cost and high-quality hyperspectral data can be generated from Sentinel-2 data using UPDM for improved land cover and vegetation mapping in the boreal forest.

Imaging spectrometer

Spectral resolution

Spectral signature

10.3390/rs13091693

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Citations (14)

Homeowner Preferences for Wildfire Risk Mitigation in the Alaskan Wildland Urban Interface

Sustainability (2021)

Allen Molina Joseph Little Stacy A. Drury Randi Jandt

Wildfire has become a larger threat to human life and property with the proliferation of homes into the wildland urban interface and warming climate. In this study we explored Alaskan homeowner preferences for wildfire risk mitigation in the wildland urban interface using discrete choice experiments to better understand the drivers of their risk mitigation actions. Estimates of willingness-to-pay for private mitigation actions are increased with wildfire risk reduction for all respondents. Willingness-to-pay for private mitigation is also positively associated with the presence of thinned fuel treatments on nearby public lands, but is estimated to decrease if cleared fuel treatments are present on public lands. Our study concludes that homeowners minimize wildfire risk while maintaining neighborhood amenity values. Additionally, findings suggest that there is an optimal amount of neighborhood participation to motivate individual risk mitigation actions, as well as having a say in the mitigation actions on public lands.

Wildland–urban interface

Amenity

Clearance

10.3390/su132111754

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Citations (7)

Recovery of lichen in tussock tundra following fire in northwestern Alaska /

Randi Jandt C. Meyers

Paired permanent vegetative cover transects were established after a small (2 ha) 1981 tundra fire in the Buckland River valley of western Alaska.Data on the regeneration of forage lichens was collected 14 years after the burn and compared to conditions in adjacent unburned plots.Graminoids, primarily cottongrass (Eriophorum vaginatum), were stimulated by the fire and grew still more vigorously on the burn area (55% cover in burn vs. 44% in adjacent unburned area).Lichen cover on burned plots had recovered very little (1%) compared to unburned plots (15%).Further study is required to establish a regeneration curve, but data from older bums in tussock tundra in western Alaska indicate the recovery period for fire-disturbed ranges of the Western Arctic Caribou Herd ( WACH) is well over 25 years.Recovery times appear similar to those reported for the Northwest Territories of Canada.Land and wildlife managers need information on lichen regeneration timelines specific to their regions to establish sound fire management guidelines for caribou (Rangifer tarandus) winter range.Point-intercept sampling, compared to canopy cover estimation, proved to be a more efficient sampling technique in the tundra cover type.

Tussock

10.5962/bhl.title.61209

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Citations (12)

Decrease of lichens in Arctic ecosystems: the role of wildfire, caribou, reindeer, competition and climate in north-western Alaska

Polar Research (2009)

Kyle Joly Randi Jandt David R. Klein

We review and present a synthesis of the existing research dealing with changing Arctic tundra ecosystems, in relation to caribou and reindeer winter ranges. Whereas pan-Arctic studies have documented the effects on tundra vegetation from simulated climate change, we draw upon recent long-term regional studies in Alaska that have documented the actual, on-the-ground effects. Our review reveals signs of marked change in Arctic tundra ecosystems. Factors known to be affecting these changes include wildfire, disturbance by caribou and reindeer, differential growth responses of vascular plants and lichens, and associated competition under climate warming scenarios. These factors are interrelated, and, we posit, unidirectional: that is, they are all implicated in the significant reduction of terricolous lichen ground cover and biomass during recent decades. Lichens constitute the primary winter forage for large, migratory caribou and reindeer herds, which in turn are a critical subsistence resource for rural residents in Alaska. Thus, declines in these lichens are a major concern for rural people who harvest caribou and reindeer for subsistence, as well as for sport hunters, reindeer herders, wildlife enthusiasts and land managers. We believe a more widely distributed and better integrated research programme is warranted to quantify the magnitude and extent of the decline in lichen communities across the Arctic.

Arctic ecology

10.1111/j.1751-8369.2009.00113.x

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Citations (146)

Post-fire stabilization of thaw-affected permafrost terrain in northern Alaska

Scientific Reports (2024)

Benjamin Jones Mikhail Kanevskiy Yuri Shur Benjamin V. Gaglioti M. Torre Jorgenson

Abstract In 2007, the Anaktuvuk River fire burned more than 1000 km 2 of arctic tundra in northern Alaska, ~ 50% of which occurred in an area with ice-rich syngenetic permafrost (Yedoma). By 2014, widespread degradation of ice wedges was apparent in the Yedoma region. In a 50 km 2 area, thaw subsidence was detected across 15% of the land area in repeat airborne LiDAR data acquired in 2009 and 2014. Updating observations with a 2021 airborne LiDAR dataset show that additional thaw subsidence was detected in < 1% of the study area, indicating stabilization of the thaw-affected permafrost terrain. Ground temperature measurements between 2010 and 2015 indicated that the number of near-surface soil thawing-degree-days at the burn site were 3 × greater than at an unburned control site, but by 2022 the number was reduced to 1.3 × greater. Mean annual ground temperature of the near-surface permafrost increased by 0.33 °C/yr in the burn site up to 7-years post-fire, but then cooled by 0.15 °C/yr in the subsequent eight years, while temperatures at the control site remained relatively stable. Permafrost cores collected from ice-wedge troughs (n = 41) and polygon centers (n = 8) revealed the presence of a thaw unconformity, that in most cases was overlain by a recovered permafrost layer that averaged 14.2 cm and 18.3 cm, respectively. Taken together, our observations highlight that the initial degradation of ice-rich permafrost following the Anaktuvuk River tundra fire has been followed by a period of thaw cessation, permafrost aggradation, and terrain stabilization.

Thermokarst

Active layer

10.1038/s41598-024-58998-5

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Citations (1)

Carbon loss from an unprecedented Arctic tundra wildfire

Nature (2011)

Michelle C. Mack M. Syndonia Bret‐Harte Teresa N. Hollingsworth Randi Jandt Edward A. G. Schuur

Biome

Fire regime

10.1038/nature10283

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Citations (434)

Comment on essd-2023-222

Xiaoran Zhu Dong Chen Maruko Kogure Elizabeth Hoy Logan T. Berner

Abstract. Studies in recent decades show strong evidence of physical and biological changes in the Arctic tundra largely in response to exceptionally rapid rates of warming. Given the important implications of these changes on ecosystem services, hydrology, surface energy balance, carbon budgets, and climate feedbacks, research on the trends and patterns of these changes is becoming increasingly important and can help better constrain estimates of local, regional, and global impacts as well as inform mitigation and adaptation strategies. Despite this high need, scientific understanding of tundra ecology and change remains limited largely due to the inaccessibility of this region and less intensive study compared to other terrestrial biomes. A synthesis of existing datasets from past field studies can make field data more accessible and open up possibilities for collaborative research as well as for investigating and informing future studies. Here, we synthesize field datasets of vegetation, and active layer properties from the Alaskan tundra, one of the most well-studied tundra regions. Given the potential increasingly intensive fire regimes in the tundra, fire history and severity attributes have been added to data points where available. The resulting database is a resource that future investigators can employ to analyze spatial and temporal patterns in soil, vegetation, and fire disturbance-related environmental variables across the Alaskan tundra. This database, titled Synthesized Alaskan Tundra Field Database (SATFiD), can be accessed at the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC) for Biogeochemical Dynamics (Chen et al., 2023: https://doi.org/10.3334/ORNLDAAC/2177).

Biome

10.5194/essd-2023-222-rc1

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Citations (0)

Fire in arctic tundra of Alaska: past fire activity, future fire potential, and significance for land management and ecology

International Journal of Wildland Fire (2015)

Nancy H. F. French Liza K. Jenkins Tatiana Loboda Mike Flannigan Randi Jandt

A multidecadal analysis of fire in Alaskan Arctic tundra was completed using records from the Alaska Large Fire Database. Tundra vegetation fires are defined by the Circumpolar Arctic Vegetation Map and divided into five tundra ecoregions of Alaska. A detailed review of fire records in these regions is presented, and an analysis of future fire potential was performed based on future climate scenarios. The average size of tundra fire based on the data record is 22 km2 (5454 acres). Fires show a mean size of 10 km2 (2452 acres) and median of 0.064 km2 (16 acres), indicating small fires are common. Although uncommon, 16 fires larger than 300 km2 (74 132 acres) have been recorded across four ecoregions and all five decades. Warmer summers with extended periods of drying are expected to increase fire activity as indicated by fire weather index. The implications of the current fire regime and potential changes in fire regime are discussed in the context of land management and ecosystem services. Current fire management practices and land-use planning in Alaska should be specifically tailored to the tundra region based on the current fire regime and in anticipation of the expected change in fire regime projected with climate change.

Fire regime

10.1071/wf14167

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Citations (66)

Lightning as a major driver of recent large fire years in North American boreal forests

Nature Climate Change (2017)

Sander Veraverbeke Brendan M. Rogers Mike Goulden Randi Jandt Charles E. Miller

Fire regime

Biome

Lightning

Boreal ecosystem

10.1038/nclimate3329

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Citations (419)

A novel method to simulate AVIRIS-NG hyperspectral image from Sentinel-2 image for improved vegetation/wildfire fuel mapping, boreal Alaska

International Journal of Applied Earth Observation and Geoinformation (2022)

Anushree Badola Santosh K. Panda Dar A. Roberts Christine F. Waigl Randi Jandt

Detailed vegetation maps are one of the primary inputs for forest and wildfire management. Hyperspectral remote sensing is a proven technique for detailed and accurate vegetation mapping. However, the availability of recent hyperspectral imagery in Alaska is limited because of the logistics and high cost involved in its acquisition. In this study, we simulated AVIRIS-NG (Airborne Visible InfraRed Imaging Spectrometer - Next Generation) hyperspectral data from widely available Sentinel-2 multispectral data using the Universal Pattern Decomposition Method (UPDM). The UPDM is a spectral unmixing technique that uses detailed ground spectra of vegetation classes and the Spectral Response Functions of AVIRIS-NG and Sentinel-2 sensors to simulate imagery with the same number of bands and spectral resolution as an AVIRIS-NG image. We simulated three images (each covering an area of 100 km × 100 km) from two ecoregions to test portability of the approach. We collected ground spectra of vegetation and bare ground during summers (2019–2021) using a PSR+ 3500 hand-held spectroradiometer and created a spectral library for this study. The Iterative Endmember Selection (IES) algorithm was used to optimize the spectral library and to select the most representative endmembers for simulation: birch, spruce, and gravel. We validated the simulated hyperspectral imagery by comparing it with available AVIRIS-NG images. The simulated image was visually and spectrally similar to the AVIRIS-NG image (RMSE of 0.03 and 0.02 for birch and spruce spectra, respectively). We applied the Random Forest image classification model to derive detailed vegetation maps from the simulated images. Our vegetation map showed an improvement of 33% in the map accuracy compared to the LANDFIRE EVT map. This study demonstrated an efficient and cost-effective approach to derive detailed vegetation maps at the Sentinel scene scale by simulating hyperspectral images in Google's cloud environment. It offers a novel pathway to generate detailed vegetation and fuel maps for the whole boreal region of Alaska to aid effective forest and fire management.

Endmember

Spectroradiometer

Imaging spectrometer

Spectral signature

Spectral bands

10.1016/j.jag.2022.102891

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Citations (9)