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These raster datasets represent historical stand age. The last four digits of the file name specifies the year represented by the raster. For example a file named Age_years_historical_1990.tif represents the year 1990. Cell values represent the age of vegetation in years since last fire, with zero (0) indicating burned area in that year. Files from years 1860-2006 use a variety of historical datasets for Boreal ALFRESCO model spin up and calibration to most closely match historical wildfire dynamics.
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These raster datasets represent historical stand age. The last four digits of the file name specifies the year represented by the raster. For example a file named Age_years_historical_1990.tif represents the year 1990. Cell values represent the age of vegetation in years since last fire, with zero (0) indicating burned area in that year. Files from years 1860-2006 use a variety of historical datasets for Boreal ALFRESCO model spin up and calibration to most closely match historical wildfire dynamics.
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These raster datasets represent historical stand age. The last four digits of the file name specifies the year represented by the raster. For example a file named Age_years_historical_1990.tif represents the year 1990. Cell values represent the age of vegetation in years since last fire, with zero (0) indicating burned area in that year. Files from years 1860-2006 use a variety of historical datasets for Boreal ALFRESCO model spin up and calibration to most closely match historical wildfire dynamics.
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The Integrated Ecosystem Model is designed to help resource managers understand the nature and expected rate of landscape change. Maps and other products generated by the IEM will illustrate how arctic and boreal landscapes are expected to alter due to climate-driven changes to vegetation, disturbance, hydrology, and permafrost. The products will also provide resource managers with an understanding of the uncertainty in the expected outcomes.
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These raster datasets represent historical stand age. The last four digits of the file name specifies the year represented by the raster. For example a file named Age_years_historical_1990.tif represents the year 1990. Cell values represent the age of vegetation in years since last fire, with zero (0) indicating burned area in that year. Files from years 1860-2006 use a variety of historical datasets for Boreal ALFRESCO model spin up and calibration to most closely match historical wildfire dynamics.
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We mosaicked twelve LandSat-8 OLI satellite images taken during the summer of 2014, which were used in an object based image analysis (OBIA) to classify the landscape. We mapped seventeen of the most dominant geomorphic land cover classes on the ACP: (1) Coastal saline waters, (2) Large lakes, (3) Medium lakes, (4) Small lakes, (5) Ponds, (6) Rivers, (7) Meadows, (8) Coalescent low-center polygons, (9) Low-center polygons, (10) Flat-center polygons, (11) High-center polygons, (12) Drained slope, (13) Sandy barrens, (14) Sand dunes, (15) Riparian shrub, (16) Ice, and (17) Urban (i.e. towns and roads). Mapped products were validated with an array of oblique aerial/ground based photography (Jorgenson et al., 2011)...
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This pilot project has initiated a long-term integrated modeling project that aims todevelop a dynamically linked model framework focused on climate driven changes tovegetation, disturbance, hydrology, and permafrost, and their interactions and feedbacks.This pilot phase has developed a conceptual framework for linking current state-of-thesciencemodels of ecosystem processes in Alaska – ALFRESCO, TEM, GIPL-1 – and theprimary processes of vegetation, disturbance, hydrology, and permafrost that theysimulate. A framework that dynamically links these models has been defined and primaryinput datasets required by the models have been developed.
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These raster datasets represent historical stand age. The last four digits of the file name specifies the year represented by the raster. For example a file named Age_years_historical_1990.tif represents the year 1990. Cell values represent the age of vegetation in years since last fire, with zero (0) indicating burned area in that year. Files from years 1860-2006 use a variety of historical datasets for Boreal ALFRESCO model spin up and calibration to most closely match historical wildfire dynamics.
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The Bureau of Ocean Energy Management (BOEM) is supporting a field effort in support of a ShoreZone mapping project along the Chukchi and Beaufort coasts. Funds from the LCC will allow for the inclusion of three additional ShoreStations. Researchers will conduct ground surveys to get detailed physical and biological measurements throughout the various and often unique Chukchi and Beaufort coastal habitats. Sediment samples will be archived from each shore station for hydrocarbon analyses in the event of a local or regional oil spill. The Arctic ShoreZone Shore Stations will be added to the statewide database and made available online to the public NOAA website.
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These raster datasets represent historical stand age. The last four digits of the file name specifies the year represented by the raster. For example a file named Age_years_historical_1990.tif represents the year 1990. Cell values represent the age of vegetation in years since last fire, with zero (0) indicating burned area in that year. Files from years 1860-2006 use a variety of historical datasets for Boreal ALFRESCO model spin up and calibration to most closely match historical wildfire dynamics.
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These raster datasets are output from the Geophysical Institute Permafrost Lab (GIPL) model and represents simulated mean annual ground temperature (MAGT) in Celsius, averaged across a decade, at the base of active layer or at the base of the seasonally frozen soil column. These data were generated by driving the GIPL model with a composite of five GCM model outputs for the A1B emissions scenario. The file name specifies the decade the raster represents. For example, a file named MAGT_1980_1989.tif represents the decade spanning 1980-1989. Cell values represent simulated mean annual ground temperature (degree C) at the base of the active layer (for areas with permafrost) or at the base of the soil column that is...
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The Integrated Ecosystem Model for Alaska project (IEM) uses down-scaled climate models as the drivers of ecosystem change to produce forecasts of future fire, vegetation, permafrost and hydrology regimes at a resolution of 1km. This effort is the first to model ecosystem change on a statewide scale, using climate change input as a major driving variable. The objectives of the IEM project are as follows; to better understand and predict effects of climate change and other stressors on landscape level physical and ecosystem processes, and to provide support for resource conservation planning.The IEM will provide resource managers with a decision support tool to visualize future landscapes in Alaska. Model outputs...
Categories: Data, Project; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: Academics & scientific researchers, DYNAMIC VEGETATION/ECOSYSTEM MODELS, DYNAMIC VEGETATION/ECOSYSTEM MODELS, Datasets/Database, Federal resource managers, All tags...
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These raster datasets represent output from the Boreal ALFRESCO (Alaska Frame Based Ecosystem Code) model. Boreal ALFRESCO operates on an annual time step, in a landscape composed of 1 x 1 km pixels, a scale appropriate for interfacing with mesoscale climate and carbon models. The last four digits of the file name specifies the year represented by the raster. For example a file named Age_years_historical_1990.tif represents the year 1990. Cell values represent the age of vegetation in years since last fire, with zero (0) indicating burned area in that year. Coverage of this dataset includes much of the state of Alaska (but does exclude Southeastern AK, Kodiak Island, portions of the Alaska Peninsula, and the Aleutian...
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These raster datasets are output from the Geophysical Institute Permafrost Lab (GIPL) model and represent simulated active layer thickness (ALT) in meters averaged across a decade. These data were generated by driving the GIPL model with a composite of five GCM model outputs for the A1B emissions scenario. The file name specifies the decade the raster represents. For example, a file named ALT_1980_1989.tif represents the decade spanning 1980-1989. Cell values represent simulated maximum depth (in meters) of thaw penetration (for areas with permafrost) or frost penetration (for areas without permafrost). If the value of the cell is positive, the area is underlain by permafrost and the cell value specifies the depth...
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These raster datasets represent historical stand age. The last four digits of the file name specifies the year represented by the raster. For example a file named Age_years_historical_1990.tif represents the year 1990. Cell values represent the age of vegetation in years since last fire, with zero (0) indicating burned area in that year. Files from years 1860-2006 use a variety of historical datasets for Boreal ALFRESCO model spin up and calibration to most closely match historical wildfire dynamics.
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These raster datasets represent historical stand age. The last four digits of the file name specifies the year represented by the raster. For example a file named Age_years_historical_1990.tif represents the year 1990. Cell values represent the age of vegetation in years since last fire, with zero (0) indicating burned area in that year. Files from years 1860-2006 use a variety of historical datasets for Boreal ALFRESCO model spin up and calibration to most closely match historical wildfire dynamics.
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Webinar 2015: Alaska’s National Hydrography Dataset (NHD), the digital data layer that depicts the location of lakes and streams, was originally created from the 1950’s topographic maps. With funding support from the LCC Network, this project focused on establishing a statewide framework to improve the hydrography mapping and stewardship in Alaska. This will be achieved through the creation of a statewide system to make digital mapping data updates accessible and affordable, and through the creation of a statewide hydrography mapping coordinator position to synchronize updates and guide hydrography mapping development. This framework will allow agencies and organizations to greatly improve their hydrography mapping...
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The Arctic LCC and National Park Service has partnered together to complete a ShoreZone imagining and mapping project for the entire coastline, lagoons inclusive, from Point Hope to Wales in Northwestern Alaska. The ShoreZone Mapping System uses oblique aerial imagery and field data from ShoreStations to classify coastline habitats based on geological and biological attributes. ShoreZone products are made available to the public through the National Oceanic and Atmospheric Administration (NOAA) National Marine Fisheries Website.


map background search result map search result map Integrated Ecosystem Model (AIEM) for Alaska and Northwest Canada Alaskan Arctic Coastal Plain Polygonal Geomorphology Map 2015 Webinar: Bringing Alaska's Freshwater Hydrography into the 21st Century ShoreZone Program on the North Slope of Alaska WEAR ShoreZone and ShoreStation Surveys NPS Simulated Active Layer Thickness Simulated Mean Annual Ground Temperature Potential Evapotranspiration: CCCMA - A1B Scenario Potential Evapotranspiration: ECHAM5 - A1B Scenario Integrated Ecosystem Model Reports IEM-CSC Factsheet with Supplement, 2015 Stand Age Projections Historical Stand Age 1980-1989 Historical Stand Age 1870-1879 Historical Stand Age 2000-2006 Historical Stand Age 1940-1949 Historical Stand Age 1900-1909 Historical Stand Age 1960-1969 Historical Stand Age 1890-1899 Historical Stand Age 1910-1919 ShoreZone Program on the North Slope of Alaska WEAR ShoreZone and ShoreStation Surveys NPS Alaskan Arctic Coastal Plain Polygonal Geomorphology Map Integrated Ecosystem Model (AIEM) for Alaska and Northwest Canada Simulated Active Layer Thickness Simulated Mean Annual Ground Temperature Potential Evapotranspiration: CCCMA - A1B Scenario Potential Evapotranspiration: ECHAM5 - A1B Scenario Integrated Ecosystem Model Reports IEM-CSC Factsheet with Supplement, 2015 Stand Age Projections Historical Stand Age 1980-1989 Historical Stand Age 1870-1879 Historical Stand Age 2000-2006 Historical Stand Age 1940-1949 Historical Stand Age 1900-1909 Historical Stand Age 1960-1969 Historical Stand Age 1890-1899 Historical Stand Age 1910-1919 2015 Webinar: Bringing Alaska's Freshwater Hydrography into the 21st Century