Browsing by Author "Johnson, Kris"

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    Camp Ripley Sentinel Landscape Climate Resilience Analysis and Strategic Plan Amendments
    (University of Minnesota Duluth, 2023-07) Bartsch, Will; Cai, Meijun; Johnson, Kris; Nixon, Kristi; Sprague, Tiffany; Wright, Chris; Olsen, Louis; Reed, Jane
    Camp Ripley is a military training facility located in central Minnesota. It is surrounded by the 750,000-acre Camp Ripley Sentinel Landscape (CRSL). Created in 2015, the CRSL consists of working and natural lands surrounding Camp Ripley with the purpose of protecting the training mission of the facility. The rural character of this landscape is generally compatible with that mission. However, it could be compromised by development, which could diminish habitat quality and raise the potential for conflict with landowners. The ability of Camp Ripley to maintain its mission is also threatened by a changing climate, which is projected to get warmer and wetter with a higher frequency of large precipitation events in the region. To help ensure the viability of the mission, the Natural Resources Research Institute assessed climate vulnerabilities and developed strategies to build and enhance climate resilience. Specifically, we 1) evaluated and selected Global Climate Models (GCM) that are expected to perform well in the region, 2) modeled stream water quantity and quality under different land use and climate scenarios, 3) characterized the landscape using Geographic Information Systems, 4) modeled and identified high-quality habitat for at-risk species, 5) evaluated and ranked parcels for conservation and restoration opportunities, 6) created afforestation plans for individual parcels, and 7) amended the Camp Ripley Strategic Plan with climate resilience language and strategies. Modeling stream quantity and quality under different land use scenarios indicates generally increased flow and sediment and nutrient concentration in scenarios where forest land is converted to agriculture or developed. Modeling under different future climate scenarios generally predicts decreased summer baseflow and increased nutrient and sediment concentrations. A suite of environmental data was acquired and developed to help characterize the landscape and prioritize parcels for conservation or restoration activity. Habitat models were developed for the Red-shouldered hawk, Golden-winged warbler, Northern long-eared bat, and Blanding’s turtle, all listed as at-risk or endangered under the Endangered Species Act. Afforestation plans with carbon sequestration modeling and carbon market participation compensation estimates were completed for two parcels within the landscape, illustrating an economically viable, market-driven solution. Climate resilience language was added to the strategic plan with emphasis placed on the restructuring and expansion of the strategy table while improving alignment with Minnesota’s Climate Adaptation Framework.
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    Normalized Difference Vegetation Index, 2015-2018
    (2024-02-26) Johnson, Kris; kristofj@d.umn.edu; Johnson, Kris; Natural Resources Research Institute
    A Normalized Difference Vegetation Index (NDVI) is an indicator of the live vegetation on the landscape. It was developed at a 10 meter resolution using Google Earth Engine Sentinel-2 satellite imagery. For more information on the Sentinel-2 imagery: https://explorer.earthengine.google.com/#detail/COPERNICUS%2FS2 Script used to derive data: https://code.earthengine.google.com/774e4ed152e4651971dc6e9456998d17 Methods: This is a composite image where each pixel is selected based on the NDVI function (NIR-Red/NIR+Red). This composite thus represents the highest NDVI for every pixel for that location captured by Sentinel-2.
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    Normalized Difference Water Index, 2015-2018
    (2024-02-26) Johnson, Kris; kristofj@d.umn.edu; Johnson, Kris; Natural Resources Research Institute
    A Normalized Difference Water Index (NDWI) is an indicator of open water on the landscape. It was developed at a 10 meter resolution using Google Earth Engine Sentinel-2 satellite imagery. For more information on the Sentinel-2 imagery: https://explorer.earthengine.google.com/#detail/COPERNICUS%2FS2 Script used to derive data: https://code.earthengine.google.com/774e4ed152e4651971dc6e9456998d17 Methods: This is a composite image where each pixel is selected based on the NDWI function (Green-NIR/Green+NIR). This composite thus represents the highest NDWI for every pixel for that location captured by Sentinel-2.