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 avoid two repetitive ground field efforts, the sampling plan was devised from a combination of both vegetation maps. Using OR logic, overlays were created using both maps as input for each class, and random samples were developed for each class in excess of 30 polygons. Where there were less than 30 polygons sample sites were selected non-randomly from each polygon (i.e. a 100% sample). A total of 512 ground sampling sites were developed from a total of 21 vegetation and land cover classes which are represented on both vegetation maps. Using GIS tools, an ASCII file was generated with ground coordinates representing each of these sites. The 512 sets of coordinates were appropriately re-formatted and directly downloaded as waypoints in three North American Rockwell PLGR GPS receivers. During the week of August 4, 1997 three field crews of two persons each worked together at the monument in a coordinated effort to identify vegetation/cover types at each of the sites. The field crews had a paper map showing the location of the plots and the polygon boundaries (but not attributes) overlaid on topographic data. One team member operated the GPS receiver to navigate to the site, and the other identified the vegetation/cover type and provided a general physical description of the site environs. Sites were considered to be circular with a radius of 50 m. from the coordinate point. Where 2 or more vegetation/cover types occurred, or there was a mosaic of types, all were described within the 50 m. radius of the site coordinate.

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 for Fort Davis NHS was developed using a combined strategy of automated digital image classification and direct analog image interpretation of aerial photography and satellite imagery. Initially, the aerial photography and satellite imagery were processed and entered into a geographic information system (GIS) along with ancillary spatial layers. A working map legend of ecologically based vegetation map units was developed using the vegetation classification described in Chapter 2 as the foundation. The intent was to develop map units that targeted the plant-association level wherever possible within the constraints of image quality, information content, and resolution. With the provisional legend and ground-control points provided by the field-plot data (the same data used to develop the vegetation classification), a combination of hands-on manual digitizing on a screen (heads-up screen digitizing) of polygons based on image interpretation and supervised image classifications was conducted. The outcome was a vegetation map composed of a suite of map units defined by plant associations and represented by sets of mapped polygons with similar spectral and site characteristics

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. A final vegetation map for Fort Caroline National Monument was created to represent the vegetation occurring within the park during 2012. This product is the final of four steps necessary to produce an accurate vegetation map based upon aerial photographs. This includes the determination of the community element global (CEGL) codes (2008) and acquisition of aerial imagery (2012), using the aerial imagery, with ground truthing points (2014), to create a draft vegetation map, performing an accuracy assessment (2015), and then using all the available information to create a final vegetation map (2018).

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. Just over 698 acres, including 214 acres in the authorized boundary of HOME and an additional 484 acres in the environs, were mapped using ten map classes (Figure 5). This included four land cover classes and six vegetation classes. Of all the map units, the most frequent was Fraxinus pennsylvanica / Ulmus spp. / Celtis occidentalis Forest with 21 polygons. Fraxinus pennsylvanica / Ulmus spp. / Celtis occidentalis Forest was also the most abundant map unit in terms of area other than cropfields in the environs, covering 219 acres (89 hectares) or about 13% of the project area. All of the frequencies for each map unit (i.e., number of polygons) along with acreage per map unit are listed in Table 3. Normally the standard minimum mapping unit for NPS vegetation mapping projects is defined as 0.5 hectare. However this is a nominal unit and due to the small size of HOME and the resolution of the imagery it was reduced to allow for more detail in the mapping. Therefore, 13 of the total 60 polygons were under 0.5 hectare. The average area of polygons for this project was 28.8 acres (11.6 hectares).

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. A total of 237 acres (96 hectares) are within the accepted boundaries of GWCA (Figure 8). The standard minimum mapping unit for NPS vegetation mapping projects is defined as 0.5 hectare, although several mapped polygons were smaller for GWCA. Restored tallgrass prairie made up most of the current vegetation of the park, and accounted for 134 acres (54.1 ha) in eight polygons, or 56.5% of the total area. Ruderal woodland and forest was the next most abundant with 53.6 acres in eight polygons, or 22.6% of the park. Non-native ruderal grassland and ruderal shrubland accounted for 25 acres (10.1 ha or 10.5%) and 2.2 acres (0.9 ha or <1%) of the area of the park, respectively. Developed land accounts for 21.9 acres (8.9 ha), or 9.2% of the park. A total of 36 polygons were mapped, with an average area of 15.2 acres (6.1 ha).

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. A total of 237 acres (96 hectares) are within the accepted boundaries of GWCA (Figure 8). The standard minimum mapping unit for NPS vegetation mapping projects is defined as 0.5 hectare, although several mapped polygons were smaller for GWCA. Restored tallgrass prairie made up most of the current vegetation of the park, and accounted for 134 acres (54.1 ha) in eight polygons, or 56.5% of the total area. Ruderal woodland and forest was the next most abundant with 53.6 acres in eight polygons, or 22.6% of the park. Non-native ruderal grassland and ruderal shrubland accounted for 25 acres (10.1 ha or 10.5%) and 2.2 acres (0.9 ha or <1%) of the area of the park, respectively. Developed land accounts for 21.9 acres (8.9 ha), or 9.2% of the park. A total of 36 polygons were mapped, with an average area of 15.2 acres (6.1 ha).

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. Polygon boundary edits were transferred from the paper maps used in the field to the digital shapefiles each week using ArcMap GIS software. Field edits were also transferred to a set of master paper maps that did not go into the field; these will be archived along with the datasheets. The polygons were contained in a field geodatabase structure (.mdb), enabling topography rules and relationships to be established. The geodatabase was archived each week to ensure no loss of data and to allow for reversion or retrieval if needed. Strict nomenclature was enforced for polygons, and a unique name was assigned to each polygon. The names reflected the verified physiognomic formation type by a prefix of representative letters (W = Woodland, SS = shrub savanna, etc.) followed by a number. In the final map, there are 16 vegetation alliances or associations attributed to 74 polygons (Figure 2-3). For each, there is a oneto- one correlation between the alliance or association and map units (polygons). Table 2-3 shows each vegetation community type, the number of polygons attributed with that type, and the total area.