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Geospatial data for the Vegetation Mapping Inventory Project of Carlsbad Caverns National Park
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.
The vegetation map was developed using a strategy that combined and automated digital image classification of satellite imagery with direct analog image interpretation. Two sets of satellite imagery were used for mapping: SpaceImaging’s IKONOS and Landsat Enhanced Thematic Mapper+ (ETM+). IKONOS was the primary imagery used because of its high-resolution 1 m panchromatic (Pan— a black and white panchromatic band) and 4 m Multi-Spectral (MS—three visible and one infrared band) data. Variations in plant reflection and absorption due to biochemical composition will vary within and among bands and generate distinct spectral “signatures” for various elements of interest). In this case, the signature of each picture element (pixel) in the image provides a quantitative measure of reflectance at specific wavelengths that can then be statistically analyzed to generate a vegetation map of spectrally similar vegetation communities. In addition, the high resolution of both the Pan and MS imagery enabled the visual differentiation of trees and shrubs from one another along with various physical features that allow the enhancement of the statistically generated map during the interpretation phase
Complete Metadata
| @id | http://datainventory.doi.gov/id/dataset/4375a759de98611ccb2a35c9adcfb029 |
|---|---|
| bureauCode |
[ "010:24" ] |
| dataQuality | true |
| identifier | NPS_DataStore_2233258 |
| issued | 2003-06-01T12:00:00Z |
| landingPage | https://irma.nps.gov/DataStore/Reference/Profile/2233258 |
| programCode |
[ "010:118", "010:119" ] |
| references |
[ "https://irma.nps.gov/DataStore/Reference/Profile/2233258" ] |
| spatial | -108.201988,28.69211,-99.08216,34.3876343 |
| theme |
[ "geospatial" ] |