Vegetation Mapping Inventory Project for Mount Rainier National Park

Cook, Tammy

The Mount Rainier National Park Vegetation Mapping Inventory Project is part of the NPS Vegetation Mapping Inventory Program (VMI). The NPS Vegetation Mapping Inventory Program uses the National Vegetation Classification Standard (NVCS), a classification system well integrated with the major scientific efforts in the taxonomic classification of vegetation. The classification system is a Federal Geographic Data Committee (FGDC) standard for the physiognomic levels (coarser detail). Work continues on the floristic levels (fine detail) through both the FGDC Vegetation Subcommittee and the Ecological Society of America Vegetation Panel. The map class themes represent NVCS natural/semi-natural vegetation communities. Maps are produced in Universal Transverse Mercator (UTM), NAD83 datum with a 1:24,000 scale and a minimum mapping unit of 0.5 hectares. The vegetation maps must meet the National Map Accuracy Standards for positional accuracy and the minimum class accuracy goal across all vegetation and land cover classes of 80 percent. The Institute for Natural Resources, working in cooperation with the NPS North Coast and Cascades Network (NCCN), has completed a VMI project for the vegetation communities of Mount Rainier National Park (MORA). The map is based on a vegetation classification developed during the project and was created using an inductive modeling approach. Data used to construct the classification were collected between 2005 and 2015 and included plots from Olympic National Park and North Cascades National Park Complex. These plots were used to develop and refine the association-level National Vegetation Classification (NVC). The associations were combined into map classes based roughly on the NVC alliance-level classification, but updated to allow improved map detail and accuracy. Model training data relied only on plots from MORA, collected between 2005 and 2019. Independent field accuracy assessment data were collected in 2011, supplemented in 2014 and 2019 and applied to the final map. The map was made using the random forests machine learning algorithm. The modeling used 1,900 plots combined with predictor metrics developed from aerial imagery, Lidar, elevation and climate data. The final vegetation map, including a buffer surrounding the park, contains 33 natural vegetated classes, five mostly unvegetated natural classes, and four classes representing burned areas or anthropogenic disturbance. The map uses 3m2 pixels, with a typical minimum mapping unit of 500m2. Overall map accuracy based on 761 field plots was 86.9%. Project products include report, geospatial data, imagery, plot data, descriptions of the map classes and a key to the map classes and are linked in an assemblage.

Vegetation Mapping Inventory Project for Mount Rainier National Park

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