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      Satellite-Based Assessment of Grassland Conversion and Related Fire Disturbance in the Kenai Peninsula, Alaska

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          Abstract

          Spruce beetle-induced (Dendroctonus rufipennis (Kirby)) mortality on the Kenai Peninsula has heightened local wildfire risk as canopy loss facilitates the conversion from bare to fire-prone grassland. We collected images from NASA satellite-based Earth observations to visualize land cover succession at roughly five-year intervals following a severe, mid-1990’s beetle infestation to the present. We classified these data by vegetation cover type to quantify grassland encroachment patterns over time. Raster band math provided a change detection analysis on the land cover classifications. Results indicate the highest wildfire risk is linked to herbaceous and black spruce land cover types, The resulting land cover change image will give the Kenai National Wildlife Refuge (KENWR) ecologists a better understanding of where forests have converted to grassland since the 1990s. These classifications provided a foundation for us to integrate digital elevation models (DEMs), temperature, and historical fire data into a model using Python for assessing and mapping changes in wildfire risk. Spatial representations of this risk will contribute to a better understanding of ecological trajectories of beetle-affected landscapes, thereby informing management decisions at KENWR.

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          Climate Change and Bark Beetles of the Western United States and Canada: Direct and Indirect Effects

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            Modeling spatial patterns of fire occurrence in Mediterranean Europe using Multiple Regression and Random Forest

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              Spruce beetle outbreaks on the Kenai Peninsula, Alaska, and Kluane National Park and Reserve, Yukon Territory: Relationship to summer temperatures and regional differences in disturbance regimes

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                Author and article information

                Journal
                101624426
                42184
                Remote Sens (Basel)
                Remote Sens (Basel)
                Remote sensing
                2072-4292
                15 December 2019
                1 February 2019
                2019
                04 February 2020
                : 11
                : 3
                : 10.3390/rs11030283
                Affiliations
                [1 ]NASA DEVELOP National Program, NASA Langley Research Center MS 307, Hampton, VA 23681, USA
                [2 ]Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
                [3 ]NOAA-Crest Center, The City University of New York, Bronx, New York 10453, USA
                [4 ]Department of Mechanical Engineering, University of California, Riverside; Riverside, CA 92521, USA
                [5 ]Science Systems and Applications, Inc., 10210 Greenbelt Rd, Lanham, MD 20706, USA
                [6 ]Department of Geography, University of South Carolina, Columbia, SC 29208, USA
                [7 ]Kenai National Wildlife Refuge, U.S. Fish and Wildlife Service, Soldotna, AK 99669, USA
                [8 ]Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Mail Code 617.0, Greenbelt, MD 20771, USA
                [9 ]Universities Space Research Association, 7178 Columbia Gateway Dr, Columbia, MD 21046, USA
                [10 ]NASA Stennis Space Center, Stennis Space Center, MS, United States
                Author notes

                Author Contributions: Katherine Hess, Cheila Cullen, Jeanette Cobian-Iñiguez, and Jacob Ramthun designed and implemented the methodology of the study and processed the data. Victor Lenske and Dawn Magness prepared the original proposal for this project. Dawn Magness provided ground-truthed data. Dawn Magness, John Bolten, Adrianna Foster, and Joseph Spruce all provided guidance and expertise regarding the design and implementation of the methodology.

                [* ]Correspondence: katehess2@ 123456gmail.com ; Tel.: +1-973-223-4266; john.bolten@ 123456nasa.gov ; Tel.: +1-301-614-6529; dawn_magness@ 123456fws.gov ; Tel.: +1-907-260-2814
                Article
                NASAPA1521889
                10.3390/rs11030283
                6999731
                20d69f2d-0d80-496f-b1ba-ee6b7ccff2e3

                Submitted for possible open access publication under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

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                Categories
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                wildfire,grassland,risk modeling,land cover,change detection,alaska

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