Geospatial data for the Vegetation Mapping Inventory Project of Grand Canyon National Park/ Parashant National Monument

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. In 2009, Kass Green & Associates (KGA) was chosen by the NPS to map the vegetation of Grand Canyon National Park and the Lake Mead National Recreation Area – administered portions of the Grand Canyon Parashant National Monument using a National Vegetation Classification Standard (NVCS) compliant classification. Mapping tools and techniques used included remotely sensed digital airborne NAIP imagery, image segmentation, ancillary data, GIS biophysical modeling, photo interpretation, and field visits. This section of the report summarizes the methods used by KGA to map the vegetation of the project area. The vegetation was mapped in three phases based on floristic similarity and difficulties dealing with the logistical barriers presented by extreme terrain. Phase 1 included the high elevation forests and woodlands on rims of the eastern portion of the mapping area; Phase 2 was the inner canyon areas of the eastern and central mapping area; Phase 3 was most of the rim- and canyon areas west of Parashant Canyon. Each phase was mapped and accuracy assessed as a unit. The final mapping activities involved reconciling map classes, boundaries and accuracy assessment among all phases. The final map contained 87 map classes with a minimum mapping unit of 0.5 hectares across more than 560,000 hectares. The classes included 41 NVC Associations, 36 NVC Alliances, seven NVC Group-level classes and three classes of unvegetated surfaces (built-up, water, and bare soil/rock). Accuracy assessment (AA) was done for 1847 map segments, distributed based on map class abundances. Accuracy by map class varied between 13% (Pinyon – Juniper / Talus or Canyon Slope Scrub) and 100% (Douglas Fir / Snowberry Forest and 5 others); project-wide accuracy was 77%. Roughly one-third of the mis-identified samples were among closely– related vegetation types. Others were among classes which were found in similar habitats (e.g., constrained tributary beds) and had very similar spectral signatures.

                                            [
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    "@type": "dcat:Distribution",
    "title": "grca_parageodata.zip",
    "format": "ZIP",
    "mediaType": "application/zip",
    "description": "ArcGIS geodatabase with metadata, .mxd and layer files",
    "downloadURL": "https://irma.nps.gov/DataStore/DownloadFile/636177?Reference=2242989"
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                                            [
  "Accuracy Assessment",
  "Classification",
  "Geodatabase",
  "Habitat Types",
  "Imagery",
  "NVC",
  "NVCS",
  "National Vegetation Classification",
  "Plots",
  "Releve",
  "Relevé",
  "Remote Sensing",
  "USNVCS",
  "Vegetation",
  "Vegetation Inventory",
  "Vegetation Map",
  "Vegetation Mapping",
  "botanical survey"
]
                                        

                                            [
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