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. Instrumental to the photo interpretive effort was the use of the GPS located vegetation plots collected by the field crew. These plots provided an idea of what the signatures of the individual map units should look like. In addition to the tablular data associated with each vegetation plot were five photographs collected at each plot. These photographs helped not only in identifying the immediate area but also provided us with a “look” at the areas surrounding the vegetation plot which might be a different map unit. These photographs may be “hyperlinked” within ArcMap to the salient vegetation observation point for a better concept of on the ground conditions.All interpreted mylar layers were scanned at 300 dpi. Each scanned mylar was then rectified to the NAIP base layer using recognizable ground features as registration points. The resulting scan produced a raster image that was subsequently vectorized. Each vectorized output was then extensively edited to produce clean digital vector lines. From the digitized vectors we created polygons by building topology in the GIS program. Finally, we created labels for each polygon and used these to add the attribute information. Attribution for all the polygons at CHIC included information pertaining to map units, NVC associations, Anderson land-use classes, and other relevant data. Attribute data were taken directly from the interpreted photos or were added later using the orthophotos as a guide.

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 TOP 2015 imagery was mosaiced and manipulated using image processing and segmentation techniques (e.g. unsupervised image classification, normalized difference vegetation index, etc.) to highlight any subtle vegetation signature differences. All of the preliminary results were evaluated for usefulness and the best examples were first converted to digital lines and polygons, were next combined with other relevant AMIS GIS layers (such as the roads network), and the results were used as the base layer for the new AMIS vegetation mapping effort. Building off the base layer, all relevant lines and polygons were exported as shapefiles and converted to ArcGIS coverages. The resulting coverages were run through a series of smoothing routines provided in the ArcGIS software. Following the smoothing, all digital line-work was manipulated to remove extraneous lines, eliminate small polygons, and merged polygons that split obvious stands of homogeneous vegetation. The cleaning stage was considered complete when all resulting polygons matched homogenous stands of vegetation apparent on the TOP 2015 imagery. At this point, the mapping shifted to manual techniques and all vegetation lines and polygons were visually inspected and manually moved, edited and/or updated as needed.

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 TOP 2015 imagery was mosaiced and manipulated using image processing and segmentation techniques (e.g. unsupervised image classification, normalized difference vegetation index, etc.) to highlight any subtle vegetation signature differences. All of the preliminary results were evaluated for usefulness and the best examples were first converted to digital lines and polygons, were next combined with other relevant AMIS GIS layers (such as the roads network), and the results were used as the base layer for the new AMIS vegetation mapping effort. Building off the base layer, all relevant lines and polygons were exported as shapefiles and converted to ArcGIS coverages. The resulting coverages were run through a series of smoothing routines provided in the ArcGIS software. Following the smoothing, all digital line-work was manipulated to remove extraneous lines, eliminate small polygons, and merged polygons that split obvious stands of homogeneous vegetation. The cleaning stage was considered complete when all resulting polygons matched homogenous stands of vegetation apparent on the TOP 2015 imagery. At this point, the mapping shifted to manual techniques and all vegetation lines and polygons were visually inspected and manually moved, edited and/or updated as needed.

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. Following the vegetation plot data analysis, the preliminary vegetation map was edited and refined to produce a revised preliminary vegetation map prior to thematic accuracy assessment. Using ArcMap 9.2 (ESRI 1999-2006), polygon boundaries were revised on screen based on the plot data, field observations, classification analyses, aerial photography signatures, and topographic maps. Each polygon was assigned the NVC Community Element Global (CEGL) code of a preliminary vegetation association based on the information sources listed above. Second, third, and fourth CEGL code choices were entered in cases of uncertainty, or for polygons representing mosaics of two or more types.

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. Following the vegetation plot data analysis, the preliminary vegetation map was edited and refined to produce a revised preliminary vegetation map prior to thematic accuracy assessment. Using ArcMap 9.2 (ESRI 1999-2006), polygon boundaries were revised on screen based on the plot data, field observations, classification analyses, aerial photography signatures, and topographic maps. Each polygon was assigned the NVC Community Element Global (CEGL) code of a preliminary vegetation association based on the information sources listed above. Second, third, and fourth CEGL code choices were entered in cases of uncertainty, or for polygons representing mosaics of two or more types.

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. An ArcInfo (copyright ESRI) GIS database was designed for THRO using the National Park GIS Database Design, Layout, and Procedures created by RSGIG. This was created through Arc Macro Language (AML) scripts that helped automate the transfer process and ensure that all spatial and attribute data was consistent and stored properly. Actual transfer of information from the interpreted aerial photographs to a digital, geo-referenced format involved two techniques, scanning (for the vegetation classes) and on-screen digitizing (for the land-use classes). Transferred information used to create vegetation polygon coverages and linear coverages in ArcInfo were based on quarter-quad borders. Attribute information including vegetation map unit, location, and aerial photo number was subsequently entered for all polygons. In addition, the spatial database has an FGDC-compliant metadata file.

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. An ArcInfo (copyright ESRI) GIS database was designed for THRO using the National Park GIS Database Design, Layout, and Procedures created by RSGIG. This was created through Arc Macro Language (AML) scripts that helped automate the transfer process and ensure that all spatial and attribute data was consistent and stored properly. Actual transfer of information from the interpreted aerial photographs to a digital, geo-referenced format involved two techniques, scanning (for the vegetation classes) and on-screen digitizing (for the land-use classes). Transferred information used to create vegetation polygon coverages and linear coverages in ArcInfo were based on quarter-quad borders. Attribute information including vegetation map unit, location, and aerial photo number was subsequently entered for all polygons. In addition, the spatial database has an FGDC-compliant metadata file.

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%.