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 mapping component of the BLCA project used a combination of methods to interpret and delineate vegetation polygons. Initial line work was prepared by USBOR photointerpreters who delineated the most contrasting signatures, e.g., water bodies, exposed shoreline, unvegetated geology, land use types, and vegetation at the physiognomic level. The project photo interpreter used this baseline mapping and refined it by examining digital orthophotos in stereo. The stereo photography was used as needed to distinguish fine scale vegetation patterns. Ancillary datasets such as plot and observation point data and classification and local descriptions of plant associations were used by the photointerpreter to assist with map class definitions and manual delineations. Polygons were drawn on Mylar overlays of printed orthophotos that were later scanned, or were drawn digitally on a computer screen. Heads-up digitizing consisted of delineating map class polygons on an electronic version of the digital orthophotos at a computer workstation. Digitizing was performed using vector editing in ArcGIS.

This reference contains the imagery data used in the completion of the baseline vegetation inventory project for the NPS park unit. Orthophotos, raw imagery, and scanned aerial photos are common files held here. The mapping component of the BLCA project used a combination of methods to interpret and delineate vegetation polygons. Initial line work was prepared by USBOR photointerpreters who delineated the most contrasting signatures, e.g., water bodies, exposed shoreline, unvegetated geology, land use types, and vegetation at the physiognomic level. The project photo interpreter used this baseline mapping and refined it by examining digital orthophotos in stereo. The stereo photography was used as needed to distinguish fine scale vegetation patterns. Ancillary datasets such as plot and observation point data and classification and local descriptions of plant associations were used by the photointerpreter to assist with map class definitions and manual delineations.

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 mapping component of the BRCA project used a combination of methods to interpret and delineate vegetation and land use polygons. The USGS applied an electronic segmentation method (e-Cognition software) to create preliminary linework on features with high-contrast photo-signatures. Using the preliminary linework as a baseline starting point, the primary photointerpreter drew polygons directly on screen through heads-up digitizing using ArcGIS editing tools. Additionally, trained photointerpreters assisting the primary photointerpreter drew polygons on Mylar overlays covering 1m resolution, 1:12,000-scale, 9 x 9-inch true-color aerial photographs. This process enabled the photointerpreters to view the landscape in stereo in order to identify finer details. The linework drawn on Mylar overlays was then transferred into digital media by heads-up digitizing using ArcGIS software. The park and environs were interpreted and mapped to the same level of detail.

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 mapping component of the BRCA project used a combination of methods to interpret and delineate vegetation and land use polygons. The USGS applied an electronic segmentation method (e-Cognition software) to create preliminary linework on features with high-contrast photo-signatures. Using the preliminary linework as a baseline starting point, the primary photointerpreter drew polygons directly on screen through heads-up digitizing using ArcGIS editing tools. Additionally, trained photointerpreters assisting the primary photointerpreter drew polygons on Mylar overlays covering 1m resolution, 1:12,000-scale, 9 x 9-inch true-color aerial photographs. This process enabled the photointerpreters to view the landscape in stereo in order to identify finer details. The linework drawn on Mylar overlays was then transferred into digital media by heads-up digitizing using ArcGIS software. The park and environs were interpreted and mapped to the same level of detail.

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. Vegetation and land use were interpreted to as detailed a level possible from high-resolution, 9” x 9” stereo pairs of 1:12,000-scale true color aerial photography. Polygons representing vegetation or land use map classes were delineated directly on-screen through heads-up digitizing using ArcGIS editing tools and transferred to a spatial database. The project used the program standard minimum mapping unit of 0.5 ha with few exceptions. Fifty-four map classes represented by 31,497 polygons were developed for CANY. A total of 30,329 polygons represent 41 natural or semi-natural vegetation map classes covering 94.8% of the mapping project area. One map class was documented as point locations only. Twelve additional land use/land cover and geologic map classes describe 1,168 polygons (3.7% of polygons and 5.2% of the area). Average polygon size across all map classes is 9.9 ha (24.4 acres). Lands within CANY make up 135,204 ha (334,096 acres) or 79.2% of the total project area. Blackbrush Shrubland had the highest number of polygons (3600) polygons covering 9.4% of the mapping area. The Potholed and Jointed Sandstone Woodland Complex is the most common map class, delineated on 30,495 ha (75,354 acres) or 17.9% of the project 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. Vegetation and land use were interpreted to as detailed a level possible from high-resolution, 9” x 9” stereo pairs of 1:12,000-scale true color aerial photography. Polygons representing vegetation or land use map classes were delineated directly on-screen through heads-up digitizing using ArcGIS editing tools and transferred to a spatial database. The project used the program standard minimum mapping unit of 0.5 ha with few exceptions. Fifty-four map classes represented by 31,497 polygons were developed for CANY. A total of 30,329 polygons represent 41 natural or semi-natural vegetation map classes covering 94.8% of the mapping project area. One map class was documented as point locations only. Twelve additional land use/land cover and geologic map classes describe 1,168 polygons (3.7% of polygons and 5.2% of the area). Average polygon size across all map classes is 9.9 ha (24.4 acres). Lands within CANY make up 135,204 ha (334,096 acres) or 79.2% of the total project area. Blackbrush Shrubland had the highest number of polygons (3600) polygons covering 9.4% of the mapping area. The Potholed and Jointed Sandstone Woodland Complex is the most common map class, delineated on 30,495 ha (75,354 acres) or 17.9% of the project 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 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.

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.

These data were converted from the originally delivered Microsoft Access PLOTs database from the Vegetation Mapping Inventory Project of Black Canyon of the Gunnison 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.

These data were converted from the originally delivered Microsoft Access PLOTs database from the Vegetation Mapping Inventory Project of Black Canyon of the Gunnison 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.