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. To produce the spatial database and map layer, 2006, 0.6-meter, 4-band Quickbird satellite imagery (supplemented with 2008 Quickbird imagery) was provided by PACN. By comparing the signatures on the imagery to field and ground data 30 map units (18 vegetated, five barren, and seven land-use / land-cover) were developed and directly crosswalked or matched to their corresponding rUSNVC plant associations. The interpreted and remotely sensed data were converted to Geographic Information System (GIS) databases and maps were printed, field tested, reviewed, and revised. The final map layer was accessed for thematic accuracy by overlaying 90 independent accuracy assessment points. The final overall accuracy of the map layer was determined to be 97% with a Kappa value of 82%.

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. Final WUPA map classes used for interpreting the aerial photographs were derived (1) from plant associations and alliances described by CPRS, (2) from the Anderson (1976) Level II land use classification system, (3) from land cover classes, and (4) from unique stands specific to WUPA. A draft hard copy vegetation map at the 1:12,000 scale was printed and checked against the interpreted aerial photographs. As a final internal accuracy check, RSGIG applied photointerpretation observations and classification relevés over the vegetation map to determine if the polygon labels matched the field data. Map validation occurred prior to the accuracy assessment. Because of the difficulties in interpreting the vegetation directly from the aerial photographs, we eventually mapped and/or validated much of the project area in the field. Metadata are required for all spatial data produced by the federal government. RSGIG used SIMMS™ software to create the three FGDC-compliant metadata files attached to the spatial databases and to this report. The metadata files explain the vegetation coverage and ancillary coverages created by RSGIG, the plot data coverage created by CPRS, and the accuracy assessment data created by CPRS.

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. Final WUPA map classes used for interpreting the aerial photographs were derived (1) from plant associations and alliances described by CPRS, (2) from the Anderson (1976) Level II land use classification system, (3) from land cover classes, and (4) from unique stands specific to WUPA. A draft hard copy vegetation map at the 1:12,000 scale was printed and checked against the interpreted aerial photographs. As a final internal accuracy check, RSGIG applied photointerpretation observations and classification relevés over the vegetation map to determine if the polygon labels matched the field data. Map validation occurred prior to the accuracy assessment. Because of the difficulties in interpreting the vegetation directly from the aerial photographs, we eventually mapped and/or validated much of the project area in the field. Metadata are required for all spatial data produced by the federal government. RSGIG used SIMMS™ software to create the three FGDC-compliant metadata files attached to the spatial databases and to this report. The metadata files explain the vegetation coverage and ancillary coverages created by RSGIG, the plot data coverage created by CPRS, and the accuracy assessment data created by CPRS.

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 order to accommodate the complex vegetation patterns often found in National Park units and generally maintain a minimum mapping unit of 0.5 ha, a three-tiered scheme was developed for attributing vegetation polygons. Where appropriate, secondary and tertiary vegetation classes are added to describe mixed-plant communities within the polygon. Secondary and tertiary classes were especially useful for describing ecotones, and for polygons with a patchwork of communities below the minimum mapping unit size. Final products included seamless park-wide GIS databases in ArcGIS geodatabase and ArcView shapefile formats of detailed overstory vegetation communities, along with vegetation statistics, hardcopy maps and orthophoto images plotted at large scale corresponding to the park area.

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 order to accommodate the complex vegetation patterns often found in National Park units and generally maintain a minimum mapping unit of 0.5 ha, a three-tiered scheme was developed for attributing vegetation polygons. Where appropriate, secondary and tertiary vegetation classes are added to describe mixed-plant communities within the polygon. Secondary and tertiary classes were especially useful for describing ecotones, and for polygons with a patchwork of communities below the minimum mapping unit size. Final products included seamless park-wide GIS databases in ArcGIS geodatabase and ArcView shapefile formats of detailed overstory vegetation communities, along with vegetation statistics, hardcopy maps and orthophoto images plotted at large scale corresponding to the park area.

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. Several imagery sources were used to derive the vegetation map, primarily Light Imaging and Detection Radar (LiDAR) and aerial imagery from the National Agriculture Imagery Program. The eCognition software package and Berkley Imaging Segmentation was used to create the initial image segments and polygon map. The mean values of variable inputs were summarized for each of the training data polygons and were used to generate a predictive non-parametric model using RandomForest in the statistical program R. The model was then applied to all polygons. The resulting draft map was reviewed by experts familiar with the vegetation types of the area. The final map includes 24 classes, representing 3 land cover types and 21 alliance-based map classes. A field-based, blind random sample accuracy assessment of the map was carried out in mid-August 2011 and December 2011. A total of 175 accuracy assessment points were collected. Based on the assessment, the total map accuracy was 88.9%, exceeding the program standard of 80%.

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. Several imagery sources were used to derive the vegetation map, primarily Light Imaging and Detection Radar (LiDAR) and aerial imagery from the National Agriculture Imagery Program. The eCognition software package and Berkley Imaging Segmentation was used to create the initial image segments and polygon map. The mean values of variable inputs were summarized for each of the training data polygons and were used to generate a predictive non-parametric model using RandomForest in the statistical program R. The model was then applied to all polygons. The resulting draft map was reviewed by experts familiar with the vegetation types of the area. The final map includes 24 classes, representing 3 land cover types and 21 alliance-based map classes. A field-based, blind random sample accuracy assessment of the map was carried out in mid-August 2011 and December 2011. A total of 175 accuracy assessment points were collected. Based on the assessment, the total map accuracy was 88.9%, exceeding the program standard of 80%.

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. Several imagery sources were used to derive the vegetation map, primarily Light Imaging and Detection Radar (LiDAR) and aerial imagery from the National Agriculture Imagery Program. The eCognition software package and Berkley Imaging Segmentation was used to create the initial image segments and polygon map. The mean values of variable inputs were summarized for each of the training data polygons and were used to generate a predictive non-parametric model using RandomForest in the statistical program R. The model was then applied to all polygons. The resulting draft map was reviewed by experts familiar with the vegetation types of the area. The final map includes 24 classes, representing 3 land cover types and 21 alliance-based map classes. A field-based, blind random sample accuracy assessment of the map was carried out in mid-August 2011 and December 2011. A total of 175 accuracy assessment points were collected. Based on the assessment, the total map accuracy was 88.9%, exceeding the program standard of 80%.

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. To produce the spatial database and map layer, year 2006 0.6-meter, 4-band Quickbird satellite imagery was provided by PACN. By comparing the signatures on the imagery to field and ground data 40 map units (23 vegetated, five barren or geologic, and 12 land-use / land-cover) were developed and directly crosswalked or matched to their corresponding rUSNVC plant associations. The interpreted and remotely sensed data were converted to Geographic Information System (GIS) databases and maps were printed, field tested, reviewed, and revised. The final map layer was accessed for thematic accuracy by overlaying 77 independent accuracy assessment points. The final overall accuracy of the map layer was determined to be 86% with a Kappa value of 88%.

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. To produce the spatial database and map layer, year 2006 0.6-meter, 4-band Quickbird satellite imagery was provided by PACN. By comparing the signatures on the imagery to field and ground data 40 map units (23 vegetated, five barren or geologic, and 12 land-use / land-cover) were developed and directly crosswalked or matched to their corresponding rUSNVC plant associations. The interpreted and remotely sensed data were converted to Geographic Information System (GIS) databases and maps were printed, field tested, reviewed, and revised. The final map layer was accessed for thematic accuracy by overlaying 77 independent accuracy assessment points. The final overall accuracy of the map layer was determined to be 86% with a Kappa value of 88%.