Landcover classes and ecological systems were delineated at an eight ha minimum mapping unit on 1:36,000 and 1:40,000 2004 and 2005 color infrared air photos using a stereoscope. The ecological systems correlate directly with aggregated or single landcover classes. See associated technical report NPS/KEFJ/NRTR—2008/136 for details.

These data were converted from the originally delivered Microsoft Access PLOTs database from the Vegetation Mapping Inventory Project of Kenai Fjords National Park. These comma-delimited data tables contain(s) vegetation mapping plot classification and accuracy assessment data, as well as summary information about the data itself. If a table is empty, then it was empty in the original database.

30 meter pixel grid data set with 1302 grid values and associated land cover attributes representing the land cover classes mapped during the KATM Land Cover Mapping Project (2000-2002)

30 meter pixel grid data set with 1302 grid values and associated land cover attributes representing the land cover classes mapped during the KATM Land Cover Mapping Project (2000-2002)

These ESRI shape files are of National Park Service tract and boundary data that were created by the Land Resources Division. Tracts are numbered and created by the regional cartographic staff at the Land Resources Program Centers and are associated to the Land Status Maps. This data should be used to display properties that NPS owns and properties that NPS may have some type of interest such as scenic easements or right of ways.

These raster images represent continuous surfaces of estimated land cover types for the western Kenai Peninsula circa 1973, circa 2002, and circa 2017. The estimated land cover types (Needleleaf Forest, Mixed Forest, Broadleaf Forest, Herbaceous, Wetland, Alpine, Barren, Shrub, Water) were derived from a random forest classifier executed in R (version 3.5.0). Predictor variables from training data included known landcover types deduced from high resolution aerial imagery, summer and winter spectral indices obtained from historical Landsat scenes, and topographic parameters derived from a digital elevation model. For each era (c. 1973, c. 2002, and c. 2017) 3,600 training points (400 points for each land cover type) were randomly distributed within training areas and training areas were opportunistically distributed to capture the regional and geomorphic extent of each land cover type to the extent possible given availability of aerial imagery. Each training point was assigned feature list values from the Landsat mosaics and digital elevation model while land cover was manually interpreted using high-resolution areal imagery. Model output included predicted landcover types and was rasterized for each era to illustrate the classification of landcover. Raster values (0-9) for each era can be translated into vegetation type using the vegetation_class_table.csv. For the 1973 era, these raster images are at a 60 meter resolution. For the 2002 and 2017 era, raster image resolution is 30 meters.

These raster images represent continuous surfaces of estimated land cover types for the western Kenai Peninsula circa 1973, circa 2002, and circa 2017. This raster image represents the coded series of estimated land cover types for each pixel over the three distinct time periods. The estimated land cover types (Needleleaf Forest, Mixed Forest, Broadleaf Forest, Herbaceous, Wetland, Alpine, Barren, Shrub, Water) were originally derived from a random forest classifier executed in R (version 3.5.0). Predictor variables from training data included known landcover types deduced from high resolution aerial imagery, summer and winter spectral indices obtained from historical Landsat scenes, and topographic parameters derived from a digital elevation model. For each era (c. 1973, c. 2002, and c. 2017) 3,600 training points (400 points for each land cover type) were randomly distributed within training areas and training areas were opportunistically distributed to capture the regional and geomorphic extent of each land cover type to the extent possible given availability of aerial imagery. Each training point was assigned feature list values from the Landsat mosaics and digital elevation model while land cover was manually interpreted using high-resolution areal imagery. Model output included predicted landcover type and a corresponding probability score and were rasterized for each era – one raster image featuring land cover types and one raster image featuring land cover type probability. This raster image characterizes a coded series that represents the unique combinations (or series) of vegetation types that pixels experienced over time. Each cell's series value corresponds to a series of numbers (#_#_#) where the first number is the vegetation code from 1973, the middle number is the vegetation code from 2002 and the last number is the vegetation code from 2017. Raster values (1-687) can be translated into series using the vegetation_code_series_table.csv. Series numbers can be translated into vegetation types using the vegetation_class_table.csv. The code series raster image allows for the graphical depiction of certain landcover change types such as deforestation (e.g. Forest_Forest_Shrub) and has 30 meter resolution.

These data were converted from the originally delivered Microsoft Access PLOTs database from the Vegetation Mapping Inventory Project of Kennesaw Mountain National Battlefield Park. These comma-delimited data tables contain(s) vegetation mapping plot classification and accuracy assessment data, as well as summary information about the data itself. If a table is empty, then it was empty in the original database.

The land cover grid data set is based on a supervised multi-spectral image analysis of Landsat TM5 and TM7 data, supported by field data, modeling, review of aerial photography, interim product review/feedback from NPS, and review/analysis of the other data layers included in the ArcView 9.1 WRST Land Cover Mapping Project. 28.5 meter pixel grid data set with 10062 grid values and associated land cover attributes representing the land cover classes mapped during the WRST Land Cover Mapping Project (2004-2007) completed by Geographic Resource Solutions and ABR Inc under contract with the National Park Service Alaska Regional Office (NPS-AKRO) as part of NPS's Land Cover Mapping Program.