The geodatabase contains 13 relate tables that together provide updated and synchronized classifications to an existing vegetation map layer for each of the nine park units in the Great Lakes Network (GLKN) of the National Park Service (NPS) Natural Resource Inventory and Monitoring Program. The classifications include 1) vegetation types at every hierarchical level in the 2015 version of the U.S. National Vegetation Classification (USNVC) and 2) map classes that represent vegetation and land cover in the vegetation map layers. Furthermore, the tables provide a crosswalk between the two classifications (vegetation and map). Each park unit in GLKN has received, at different times over several years, vegetation data products from the NPS Vegetation Mapping Inventory (VMI) Program. However, the vegetation and map classifications were at different stages of development over these years. With this geodatabase product, having a series of already linked relate tables, the original vegetation map layer for each park unit can be linked to the updated and synchronized classification information for both vegetation types and map classes.

The Circumpolar Arctic Vegetation Map (CAVM) is a geoecological map (front) of the entire Arctic with a unified legend (back). It is the first vegetation map of an entire global biome at a comparable resolution. It was funded by the US National Science Foundation (OPP-9908-829), the US Fish & Wildlife Service, the US Geological Survey and the US Bureau of Land Management. The CAVM region is north of the climatic limit of trees and is characterized by an arctic climate, arctic flora, and tundra vegetation. It excludes tundra regions than have a boreal flora such as the boreal oceanic areas of Iceland and the Aleutian Islands and alpine tundra south of the latitudinal treeline. The map was published at 1:7.5 million scale and displays the vegetation using 15 units (CAVM Team 2003, legend details: www.arcticatlas.org/maps/themes/cp/cpvg). The methods used to make the map are described in Walker et al. 2005. The CAVM is a polygon (vector) map. The GIS data are in shapefile format, and include fields for bioclimate subzone, floristic province, lake cover, landscape, substrate chemistry and vegetation category. There is also a landscape age shapefile which was created after the publication of the CAVM (Raynolds et al. 2009) In addition, there are a number of raster maps of the same extent (the Arctic), based on satellite data from the Advanced High Resolution Radiometer (AVHRR) instruments. These include the false color-infrared and NDVI images which formed the base maps for the CAVM mapping effort (Walker et al. 2005, Raynolds et al. 2006), a recent biomass map (Raynolds et al. 2012), biomass trends (Epstein et al. 2012), NDVI trends (Bhatt et al. 2010), and Summer Warmth Index (Raynolds et al. 2008). Go to Website Link :: Toolik Arctic Geobotanical Atlas below for details on legend units, photos of map units and plant species, glossary, bibliography and links to ground data. Map Themes: AVHRR Biomass 2010, AVHRR Biomass Trend 1982-2010, AVHRR False Color Infrared 1993-1995, AVHRR NDVI 1993-1995, AVHRR NDVI Trend 1982-2010, AVHRR Summer Warmth Index 1982-2003, Bioclimate Subzone, Coastline and Treeline, Elevation, Floristic Provinces, Lake Cover, Landscape Physiography, Landscape Age, Substrate Chemistry, Vegetation Layer References CAVM Team. 2003. Circumpolar Arctic Vegetation Map, scale 1:7 500 000. Conservation of Arctic Flora and Fauna (CAFF) Map No. 1. U.S. Fish and Wildlife Service, Anchorage, Alaska. Bhatt, U. S., D. A. Walker, M. K. Raynolds, J. C. Comiso, H. E. Epstein, G. J. Jia, R. Gens, J. E. Pinzon, C. J. Tucker, C. E. Tweedie, and P. J. Webber. 2010. Circumpolar arctic tundra vegetation change is linked to sea ice decline. Earth Interactions 14:1-20. doi: 10.1175/2010EI1315.1171. Epstein, H. E., M. K. Raynolds, D. A. Walker, U. S. Bhatt, C. J. Tucker, and J. E. Pinzon. 2012. Dynamics of aboveground phytomass of the circumpolar arctic tundra during the past three decades. Environmental Research Letters 7:015506 (015512 pp). Raynolds, M. K., D. A. Walker, and H. A. Maier. 2006. NDVI patterns and phytomass distribution in the circumpolar Arctic. Remote Sensing of Environment 102:271-281. Raynolds, M. K., J. C. Comiso, D. A. Walker, and D. Verbyla. 2008. Relationship between satellite-derived land surface temperatures, arctic vegetation types, and NDVI. Remote Sensing of Environment 112:1884-1894. Raynolds, M. K. and D. A. Walker. 2009. The effects of deglaciation on circumpolar distribution of arctic vegetation. Canadian Journal of Remote Sensing 35:118-129. Raynolds, M. K. 2009. A geobotanical analysis of circumpolar arctic vegetation, climate, and substrate. PhD Thesis, University of Alaska, Fairbanks. Raynolds, M. K., D. A. Walker, H. E. Epstein, J. E. Pinzon, and C. J. Tucker. 2012. A new estimate of tundra-biome phytomass from trans-Arctic field data and AVHRR NDVI. Remote Sensing Letters 3:403-411. Raynolds, M. K., D. A. Walker, A. Balser, C. Bay, M. W. Campbell, M. M. Cherosov, F. J. A. Daniëls, P. B. Eidesen, K. A. Ermokhina, G. V. Frost, B. Jedrzejek, M. T. Jorgenson, B. E. Kennedy, S. S. Kholod, I. A. Lavrinenko, O. Lavrinenko, B. Magnússon, S. Metúsalemsson, I. Olthof, I. N. Pospelov, E. B. Pospelova, D. Pouliot, V. Y. Razzhivin, G. Schaepman-Strub, J. Šibík, M. Y. Telyatnikov, and E. Troeva. 2019. A raster version of the Circumpolar Arctic Vegetation Map (CAVM). Remote Sensing of Environment 232:111297. Walker, D. A., M. K. Raynolds, F. J. A. Daniels, E. Einarsson, A. Elvebakk, W. A. Gould, A. E. Katenin, S. S. Kholod, C. J. Markon, E. S. Melnikov, N. G. Moskalenko, S. S. Talbot, B. A. Yurtsev, and CAVM Team. 2005. The Circumpolar Arctic Vegetation Map. Journal of Vegetation Science 16:267-282.

The U.S. Geological Survey (USGS) Upper Midwest Environmental Sciences Center (UMESC) has produced the Vegetation Spatial Database Coverage (vegetation map) for the Acadia National Park Vegetation Mapping Project, USGS-NPS Vegetation Mapping Program (VMP). The vegetation map is of Acadia National Park (NP) and extended environs, providing 99,693 hectares (246,347 acres) of map data. Of this coverage, 52,872 hectares (130,650 acres) is non-vegetated ocean, bay, and estuary (53% of coverage). Acadia NP comprises 19,276 hectares (47,633 acres) of the total data coverage area (19%, 40% not counting ocean and estuary data). Over 7,120 polygons make up the coverage, each with map class description and, for vegetation classes, physiognomic feature information. The spatial database provides crosswalk information to all National Vegetation Classification System (NVCS) floristic and physiognomic levels, and to other established classification systems (NatureServe’s U.S. Terrestrial Ecological System Classification, Maine Natural Community Classification, and the USGS Land Use and Land Cover Classification). This mapping project has identified 53 NVCS associations (vegetation communities) at Acadia National Park through analyses of vegetation sample data. These associations are represented in the map coverage with 33 map classes. With all vegetation types, land use classes, and park specific categories combined, 57 map classes define the ground features within the project area (58 classes including the class for no map data). Each polygon within the spatial database map is identified with one of these map classes. In addition, physiognomic modifiers are added to map classes representing vegetation to describe the vegetation structure within a polygon (density, pattern, and height). The spatial database was produced from the interpretation of spring 1997 1:15,840-scale color infrared aerial photographs. The standard minimum mapping unit (MMU) applied is 0.5 hectares (1.25 acres). The interpreted data were transferred and automated using base maps produced from USGS digital orthophoto quadrangles. The finished spatial database is a single seamless coverage, projected in Universal Transverse Mercator, Zone 19, with datum in North American Datum of 1983. The estimated overall thematic accuracy for vegetation map classes is 80%.

The Katahdin Woods and Waters National Monument Seboeis Unit Vegetation Mapping Project was initiated in the fall of 2019 by a grant through the USGS Natural Resource Preservation Program to classify and map vegetation types of the Seboeis Unit thereby providing resource managers and biological researchers with useful baseline vegetation information. This layer provides the vegetation map for the Seboeis Unit. Information for this layer was collected in 2019 and 2020. After completion of the accuracy assessment process, 33 map classes represent the Seboeis Unit of the monument. Of the 33 map classes that represent the Seboeis Unit, 28 represent natural (including ruderal) vegetation types, consisting of 50 U.S. National Vegetation Classification (USNVC) association types. For the remaining 5 of the overall 33 map classes, 2 represent USNVC cultural types for barren areas and developed areas and 3 represent non-USNVC types for non-vegetated open water. Of the 28 map classes representing natural (including ruderal) vegetation types, 15 represent a single vegetation type (when it exists above an the minimum mapping unit [MMU]), 7 represent 2 vegetation types mapped together, 5 represent 3 vegetation types mapped together, and 1 represents 6 vegetation types mapped together. Polygon units were mapped to either a 0.5 ha or 0.25 ha minimum mapping unit, depending on vegetation type. Collectively, the spatial-database layer (vegetation map) produced for the Seboeis Unit vegetation mapping project consists of 1,261 polygons and covers 4,854.8 ha, with an average polygon size of 3.8 ha. The 28 map classes representing natural (including ruderal) vegetation types apply to 97.6% of polygons (1,231 polygons; average size of 3.9 ha) and cover 98.6% of the Seboeis Unit (4,787.5 ha). Further broken down, map classes representing natural vegetation types indicate that the Seboeis Unit is 93.2% forest and woodland (4,526.6 ha), 4.0% shrubland (195.3 ha), and 1.3% herbaceous cover (65.6 ha). Map classes representing cultural vegetation types in the USNVC apply to 1.0% of polygons (12 polygons; average size of 2.5 ha) and cover 0.6% of the Seboeis Unit (29.7 ha). Map classes representing non-vegetation open and flowing water (non-USNVC) apply to 1.4% of polygons (18 polygons; average size of 2.1 ha) and cover 0.8% of the Seboeis Unit (37.4 ha). The information in this layer is explained in depth in the report titled Vegetation Map for the Seboeis Unit of Katahdin Woods and Waters National Monument.

A map service depicting Forest Service existing vegetation polygons for Region 5.This Existing Vegetation (EVeg) polygon feature class is a CALVEG (Classification and Assessment with LANDSAT of Visible Ecological Groupings) map product from a scale of 1:24,000 to 1:100,000. The geographic extent entails the northeastern portion of CALVEG Zone 6, Central Coast. Source imagery for this layer ranges from the year 1998 to 2015. The CALVEG classification system was used for vegetation typing and crosswalked to other classification systems in this database including the California Wildlife Habitat Relationship System (CWHR).Metadata and Downloads

The Prince of Wales Existing Vegetation mapping project encompasses over 4.2 million acres of Southeastern Alaska—2.3 million of which are terrestrial. This map was designed to be consistent with the standards established in the Existing Vegetation Classification and Technical Guide (Nelson et al. 2015), and to provide baseline information to support project planning and inform land management of the Prince of Wales and surrounding islands. The final map comprises seven distinct, integrated feature layers: 1) vegetation type; 2) tree canopy cover; 3) trees per acre (TPA) for trees ≥ 1’ tall; 4) trees per acre for trees ≥ 6” diameter at breast height (dbh); 5) quadratic mean diameter (QMD) for trees ≥ 2” dbh; 6) quadratic mean diameter for trees ≥ 9” dbh; and 7) thematic tree size. The dominance type map consists of 18 classes, including 15 vegetation classes and 3 other land cover types. Continuous tree canopy cover, TPA, QMD, and thematic tree size was developed for areas classified as forest on the final vegetation type map layer. Geospatial data, including remotely sensed imagery, topographic data, and climate information, were assembled to classify vegetation and produce the maps. A semi-automated image segmentation process was used to develop the modeling units (mapping polygons), which delineate homogeneous areas of land cover. Field plots containing thematic vegetation type and tree size information were used as reference for random forest prediction models. Important model drivers included 30 cm orthoimagery collected during the height of the 2019 growing season, in addition to Sentinel 2 and Landsat 8 satellite imagery, for vegetation type prediction. Additionally, detailed tree inventory data were collected at precise field locations to develop forest metrics for Quality Level 1 (QL1) Light Detection and Ranging (LiDAR) data. LiDAR information was acquired across approximately 80% of the project’s land area. Continuous tree canopy cover and 2^nd order forest metrics (TPA and QMD) were modeled across the LiDAR coverage area, and subsequently, extrapolated to the full project extent using Interferometric Synthetic Aperture Radar (IfSAR) as the primary topographic data source.

During summer 2019, botanists with the Maine Natural Areas Program collected data from 94 vegetation plots for plant community characterization. The sampling data were entered into the National Park Service PLOTS version 4.0 (National Park Service 2018) for analyses to characterize vegetation associations in the U.S. National Vegetation Classification. An accuracy assessment was performed on the draft version of the vegetation map layer. During the summer of 2020, field crews collected data from 107 stratified and randomly selected sites for evaluating the accuracy of the vegetation map layer for those map classes representing U.S. National Vegetation Classification associations. The accuracy assessment field data were then compared to the vegetation map data. Results from the accuracy assessment study show an overall accuracy of 87.6% (kappa index of 87.0%) based on an analysis of data from 105 of the 107 accuracy assessment sites.

Alliance Level vegetation maps were commissioned for D01 HARV. The intended use was to prototype and determine the cost/benefit of making highly detailed maps for allocation of plots in a spatially balanced design across the landscape. A companion Domain 10 CPER Alliance map and prototype dataset was also part of this effort.

U.S. Bureau of Land Management (BLM) has a goal to develop fine-scale vegetation maps for all the public lands it manages in California. To help meet this goal BLM contracted Aerial Information Systems, Inc. (AIS) to conduct vegetation classification development, fine-scale vegetation mapping, and accuracy assessment (AA) of approximately 22,061 acres within Colusa and Lake counties of California, under Contract GS00F170GA-Order No.140L1221F0044. AIS subcontracted the California Native Plant Society (CNPS) to conduct classification development work needed for this project, as well as AA field data collection. The California Department of Fish and Wildlife’s (CDFW) Vegetation Classification and Mapping Program (VegCAMP) provided in-kind service to allocate AA sample sites and score the vegetation map using the AA data.The study area, referred to as Walker Ridge or Molok Luyuk, which means Condor Ridge in the Native American Patwin language of the Yocha Dehe Wintun Nation, is located in the inner North Coast Ranges, east of Clear Lake and west of the town of Williams in the Sacramento Valley. This area has a large serpentinite outcrop that contains a high diversity of plants and plant communities, and is home to dozens of threatened and endangered (T&E) plants and animals. The vegetation classification developed for the project follows Federal Geographic Data Committee (FGDC) and National Vegetation Classification Standards (NVCS). The classification is based on new and previous survey information and classification work. The map was produced applying heads-up digitizing techniques using a base of 2020 60-centimeter National Agricultural Imagery Program (NAIP) imagery (true-color and color infrared), in conjunction with ancillary data and imagery sources. Map polygons are assessed for Vegetation Type, Percent Cover, Exotics, Development Disturbance, and other attributes. The minimum mapping unit (MMU) is 1 acre. Exceptions were created for vegetation stands of special significance. In this mapping effort, riparian vegetation and wetland types were mapped to a 1/4-acre MMU. Polygons representing land use were mapped with a 1-acre MMU. There were a total of 42 mapping classes composed of 30 alliances and alliance-level types such as Provisional Alliances, Semi-natural Alliances, and Mapping Units; and 5 Miscellaneous Classes relating to features such as agriculture, water, and urban disturbance; and 7 upper-level hierarchical types, such as Macrogroup and Group. Field reconnaissance and accuracy assessment enhanced map quality. The overall accuracy assessment ratings for the final vegetation map was 89.7 percent overall fuzzy accuracy.More information can be found in the project report, which is bundled with the vegetation map published for BIOS here: https://filelib.wildlife.ca.gov/Public/BDB/GIS/BIOS/Public_Datasets/3100_3199/ds3159.zip

This webmap features the USGS GAP application of the vegetation cartography design based on NVCS mapping being done at the Alliance level by the California Native Plant Society (CNPS), the California Dept of Fish and Game (CDFG), and the US National Park Service, combined with Ecological Systems Level mapping being done by USGS GAP, Landfire and Natureserve. Although the latter are using 3 different approaches to mapping, this project adopted a common cartography and a common master crossover in order to allow them to be used intercheangably as complements to the detailed NVCS Alliance & Macrogroup Mapping being done in Calif by the California Native Plant Society (CNPS) and Calif Dept of Fish & Wildlife (CDFW). A primary goal of this project was to develop ecological layers to use as overlays on top of high-resolution imagery, in order to help interpret and better understand the natural landscape. You can see the source national GAP rasters by clicking on either of the "USGS GAP Landcover Source RASTER" layers at the bottom of the contents list.Using polygons has several advantages: Polygons are how most conservation plans and land decisions/managment are done so polygon-based outputs are more directly useable in management and planning. Unlike rasters, Polygons permit webmaps with clickable links to provide additional information about that ecological community. At the analysis level, polygons allow vegetation/ecological systems depicted to be enriched with additional ecological attributes for each polygon from multiple overlay sources be they raster or vector. In this map, the "Gap Mac base-mid scale" layers are enriched with links to USGS/USNVC macrogroup summary reports, and the "Gap Eco base scale" layers are enriched with links to the Naturserve Ecological Systems summary reports.Comparsion with finer scale ground ecological mapping is provided by the "Ecol Overlay" layers of Alliance and Macrogroup Mapping from CNPS/CDFW. The CNPS Vegetation Program has worked for over 15 years to provide standards and tools for identifying and representing vegetation, as an important feature of California's natural heritage and biodiversity. Many knowledgeable ecologists and botanists support the program as volunteers and paid staff. Through grants, contracts, and grass-roots efforts, CNPS collects field data and compiles information into reports, manuals, and maps on California's vegetation, ecology and rare plants in order to better protect and manage them. We provide these services to governmental, non-governmental and other organizations, and we collaborate on vegetation resource assessment projects around the state. CNPS is also the publisher of the authoritative Manual of California Vegetation, you can purchase a copy HERE. To support the work of the CNPS, please JOIN NOW and become a member!The CDFG Vegetation Classification and Mapping Program develops and maintains California's expression of the National Vegetation Classification System. We implement its use through assessment and mapping projects in high-priority conservation and management areas, through training programs, and through working continuously on best management practices for field assessment, classification of vegetation data, and fine-scale vegetation mapping.HOW THE OVERLAY LAYERS WERE CREATED:Nserve and GapLC Sources: Early shortcomings in the NVC standard led to Natureserve's development of a mid-scale mapping-friendly "Ecological Systems" standard roughly corresponding to the "Group" level of the NVC, which facilitated NVC-based mapping of entire continents. Current scientific work is leading to the incorporation of Ecological Systems into the NVC as group and macrogroup concepts are revised. Natureserve and Gap Ecological Systems layers differ slightly even though both were created from 30m landsat data and both follow the NVC-related Ecological Systems Classification curated by Natureserve. In either case, the vector overlay was created by first enforcing a .3ha minimum mapping unit, that required deleting any classes consisting of fewer than 4 contiguous landsat cells either side-side or cornerwise. This got around the statistical problem of numerous single-cell classes with types that seemed improbable given their matrix, and would have been inaccurate to use as an n=1 sample compared to the weak but useable n=4 sample. A primary goal in this elimination was to best preserve riparian and road features that might only be one pixel wide, hence the use of cornerwise contiguous groupings. Eliminated cell groups were absorbed into whatever neighboring class they shared the longest boundary with. The remaining raster groups were vectorized with light simplification to smooth out the stairstep patterns of raster data and hopefully improve the fidelity of the boundaries with the landscape. The resultant vectors show a range of fidelity with the landscape, where there is less apparent fidelity it must be remembered that ecosystems are normally classified with a mixture of visible and non-visible characteristics including soil, elevation and slope. Boundaries can be assigned based on the difference between 10% shrub cover and 20% shrub cover. Often large landscape areas would create "godzilla" polygons of more than 50,000 vertices, which can affect performance. These were eliminated using SIMPLIFY POLYGONS to reduce vertex spacing from 30m down to 50-60m where possible. Where not possible DICE was used, which bisects all large polygons with arbitrary internal divisions until no polygon has more than 50,000 vertices. To create midscale layers, ecological systems were dissolved into the macrogroups that they belonged to and resymbolized on macrogroup. This was another frequent source for godzillas as larger landscape units were delineate, so simplify and dice were then run again. Where the base ecol system tiles could only be served up by individual partition tile, macrogroups typically exhibited a 10-1 or 20-1 reduction in feature count allowing them to be assembled into single integrated map services by region, ie NW, SW. CNPS / CDFW / National Park Service Sources: (see also base service definition page) Unlike the Landsat-based raster modelling of the Natureserve and Gap national ecological systems, the CNPS/CDFW/NPS data date back to the origin of the National Vegetation Classification effort to map the US national parks in the mid 1990's.
These mapping efforts are a hybrid of photo-interpretation, satellite and corollary data to create draft ecological land units, which are then sampled by field crews and traditional vegetation plot surveys to quantify and analyze vegetation composition and distribution into the final vector boundaries of the formal NVC classes identified and classified. As such these are much more accurate maps, but the tradeoff is they are only done on one field project area at a time so there is not yet a national or even statewide coverage of these detailed maps.
However, with almost 2/3d's of California already mapped, that time is approaching. The challenge in creating standard map layers for this wide diversity of projects over the 2 decades since NVC began is the extensive evolution in the NVC standard itself as well as evolution in the field techniques and tools. To create a consistent set of map layers, a master crosswalk table was built using every different classification known at the time each map was created and then crosswalking each as best as could be done into a master list of the currently-accepted classifications. This field is called the "NVC_NAME" in each of these layers, and it contains a mixture of scientific names and common names at many levels of the classification from association to division, whatever the ecologists were able to determine at the time. For further precision, this field is split out into scientific name equivalents and common name equivalents.MAP LAYER NAMING: The data sublayers in this webmap are all based on the US National Vegetation Classification, a partnership of the USGS GAP program, US Forest Service, Ecological Society of America and Natureserve, with adoption and support from many federal & state agencies and nonprofit conservation groups. The USNVC grew out of the US National Park Service Vegetation Mapping Program, a mid-1990's effort led by The Nature Conservancy, Esri and the University of California. The classification standard is now an international standard, with associated ecological mapping occurring around the world. NVC is a hierarchical taxonomy of 8 levels, from top down: Class, Subclass, Formation, Division, Macrogroup, Group, Alliance, Association. The layers in this webmap represent 4 distinct programs: 1. The California Native Plant Society/Calif Dept of Fish & Wildlife Vegetation Classification and Mapping Program (Full Description of these layers is at the CNPS MS10 Service Registration Page and Cnps MS10B Service Registration Page . 2. USGS Gap Protected Areas Database, full description at the PADUS registration page . 3. USGS Gap Landcover, full description below 4. Natureserve Ecological Systems, full description belowLAYER NAMING: All Layer names follow this pattern: Source - Program - Level - Scale - RegionSource - Program = who created the data: Nserve = Natureserve, GapLC = USGS Gap Program Landcover Data PADUS = USGS Gap Protected Areas of the USA program Cnps/Cdfw = California Native Plant Society/Calif Dept of Fish & Wildlife, often followed by the project name such as: SFhill = Sierra Foothills, Marin Open Space, MMWD = Marin Municipal Water District etc. National Parks are included and may be named by their standard 4-letter code ie YOSE = Yosemite, PORE = Point Reyes.Level: The level in the NVC Hierarchy which this layer is based on: Base = Alliances and Associations Mac =

The National Park Service (NPS) Vegetation Inventory Program (VIP) is an effort to classify, describe, and map existing vegetation of national park units for the NPS Natural Resource Inventory and Monitoring (I&M) Program. The NPS VIP is managed by the NPS Inventory and Monitoring Division and provides baseline vegetation information to the NPS Natural Resource I&M Program. The USGS Upper Midwest Environmental Sciences Center, NatureServe, and NPS Mississippi National River and Recreation Area (MISS) have completed vegetation classification and mapping of MISS for the NPS VIP.

Mappers, ecologists, and botanists collaborated to identify and describe vegetation types within the U.S. National Vegetation Classification (USNVC) and to determine how best to map them by using aerial imagery. The team collected data from 132 vegetation plots within MISS to develop detailed descriptions of USNVC associations. Data from 52 verification sites were also collected to test both the dichotomous key to vegetation associations and the application of vegetation types to a sample set of map polygons. Furthermore, data from 776 accuracy assessment (AA) sites were collected (of which 757 were used to test accuracy of the vegetation map layer). These data sets led to the identification of 45 vegetation association in the USNVC at MISS.

A total of 45 map classes were developed to map the vegetation and open water of MISS, including the following: 35 map classes represent natural (including ruderal) vegetation in the USNVC, 7 map classes represent cultural vegetation (agricultural and developed) in the USNVC, and 3 map classes represent non-vegetative open-water bodies (non-USNVC). Features were interpreted from viewing color-infrared digital aerial imagery dated September and October 2012 (during peak leaf-phenology change of trees) via digital onscreen three-dimensional stereoscopic workflow systems in geographic information systems (GIS). The interpreted data were digitally and spatially referenced, thus making the spatial database layers usable in GIS. Polygon units were mapped to either a 0.5 ha or 0.25 ha minimum mapping unit, depending on vegetation type.

A geodatabase containing various feature-class layers and tables shows the locations of USNVC vegetation types (vegetation map), vegetation plot samples, verification sites, AA sites, project boundary extent, and aerial image centers. The feature-class layer and relate tables for the vegetation map provides 4,498 polygons of detailed attribute data covering 21,771.6 ha of area, with an average polygon size of 4.8 ha; the vegetation map covers the entire administrative boundary for MISS.

Summary reports generated from the vegetation map layer show map classes representing USNVC natural (including ruderal) vegetation associations apply to 4,012 polygons (89.2% of polygons) and cover 8,938.7 ha (41.1%) of the map extent. Of these polygons, the map layer shows MISS to be 27.5% forest and woodland (5,986.2 ha), 1.6% shrubland (353.6 ha), 11.2% herbaceous vegetation (2,431.8 ha), and 0.8% sparse vegetation (163.9 ha). Map classes representing USNVC cultural types apply to 415 polygons (9.2% of polygons) and cover 7,628.5 ha (35.0%) of the map extent. Map classes representing non-vegetative open-water bodies (non-USNVC) apply to 71 polygons (1.6% of polygons) and cover 5,204.4 ha (23.9%) of the map extent.

For a full report on the National Park Service Vegetation Inventory Program mapping effort, see: National Park Service Vegetation Inventory Program (pdf, 54 MB)

The Ouray National Wildlife Refuge (ONWR) was established in 1960 as an inviolate sanctuary for migratory birds and any other management purpose. In 2000, the Refuge published a Comprehensive Conservation Plan in accordance with the 1997 National Wildlife Refuge Improvement Act. The plan shifted the Refuge’s emphasis toward ecosystem-based management of all resident and migratory species. Refuge and Regional staff asked that a detailed and accurate vegetation map be developed for planning and for managing the Refuge effectively. The Bureau of Reclamation’s Remote Sensing and Geographic Information Group (RSGIS) was contracted by US Fish and Wildlife Service to map vegetation and land-use classes at ONWR using remote sensing and GIS technologies originally developed for the National Park Service’s Vegetation Mapping Program.

The diverse vegetation and complicated land-use history of Ouray National Wildlife Refuge presented a unique challenge to mapping vegetation at the plant association level of the US National Vegetation Classification. To meet this challenge, the project consisted of two linked phases: (1) vegetation classification and (2) digital vegetation map production. To classify the vegetation, we sampled representative plots located throughout the 14,025-acre (5676 ha) project area. Analysis of the plot data using ordination and clustering techniques yielded 58 distinct plant associations. To produce the digital map, we used a combination of new color-infrared aerial photography and fieldwork to interpret the complex patterns of vegetation and land-use at ONWR. Eighty-one map units were developed and the vegetation units matched to the corresponding plant associations. The interpreted map data were converted to a GIS database using ArcInfo©. Draft maps created from the vegetation classification were field-tested and revised before an independent ecologist conducted an assessment of the map’s accuracy. The accuracy assessment revealed an overall database accuracy of 75.2%.

Products developed for the Ouray National Wildlife Refuge Vegetation Mapping Project include • the final report, vegetation key, map accuracy assessment results and contingency table, and photo interpretation key; • spatial database coverages of the vegetation map, vegetation plots, accuracy assessment sites, and flight line index; • digital photos (scanned from 35mm slides) of each vegetation type; • graphics of all spatial database coverages; • Federal Geographic Data Committee-compliant metadata for all spatial database coverages and field data. 12

In addition, the Refuge and USFWS copies of this report contain • original aerial photographs of the project area; • digital data files and hard copy data sheets of the observation points, vegetation field plots, and accuracy assessment sites; • original slides of each vegetation type.

ABSTRACT: The U.S. Geological Survey Upper Midwest Environmental Sciences Center (UMESC) has produced a vegetation spatial database coverage (vegetation map) for the Acadia National Park Vegetation Mapping Project, USGS-NPS Vegetation Mapping Program (VMP). Thematic accuracy requirements of the VMP specify 80% accuracy for each map class (theme) that represents National Vegetation Classification System (NVCS) associations (vegetation communities). The UMESC selected 728 field sites, all within Acadia National Park fee and easement lands, for a thematic accuracy assessment (AA) to the vegetation map. The sites were randomly generated, stratified to map class themes that represent NVCS natural/semi-natural vegetation communities using VMP standards. Certain modifications to the process were necessary to accommodate logistical challenges. Local botanists collected field data for 724 of the sites during the 1999 field season. Thematic AA used 688 sites. Sites not used for the analysis were due to the elimination of an entire map class because of irreconcilable classification concepts (19 sites), or to other reasons including unmanageable error with GPS coordinate, duplicate site location, and incomplete field data (17 sites). Regardless of their use in the analysis, all 724 AA sites collected are represented in the Accuracy Assessment Site Spatial Database.

This web map contains data layers viewable for eighteen mid-level existing vegetation maps (1:100,000) prepared for the Tongass National Forest to provide up-to-date and more complete information about vegetative communities, structure, and patterns across the project area. Over 18 million acres were mapped through a partnership between the US Department of Agriculture Forest Service Field Services & Innovation Center – Geospatial Office (GO), the Tongass National Forest, and the Alaska Regional Office. The Tongass National Forest and their partners prepared the regional classification system, identified the desired map units (map classes) and provided general project management. GO provided project support and expertise in vegetation mapping. Maps are available for the six integrated vegetation attributes: project map group, project vegetation type, Tongass NF map group, Tongass NF vegetation type, NVC division, and NVC macrogroup. For forested areas, maps are available for the twelve forest structure metrics: tree canopy cover, tree canopy cover class, tree size, biomass (Mg/ac) for trees ≥2” diameter at breast height (DBH), crown competition factor (CCF), gross board feet (GBF), quadratic mean diameter (QMD) for trees ≥2” DBH, QMD for trees ≥9” DBH, rumple index, stand density index (SDI) for trees ≥9” DBH, trees per acre (TPA) for trees ≥1’ tall, and TPA for trees ≥6” DBH. The minimum map feature depicted on the map is 0.25 acres. The map products conform to the mid-level mapping standards referenced in the Existing Vegetation Classification, Mapping, and Inventory Technical Guide (Nelson et al. 2015). For more detailed information on mapping methodology please see the Tongass National Forest Existing Vegetation Project Report or the individual area project reports.

Aerial Information Systems, Inc. (AIS) was contracted by the Western Riverside County Regional Conservation Authority to perform an update to their original 2005 Western Riverside Vegetation Map. The project was funded through a Local Assistance Grant from the California Department of Fish and Wildlife (CDFW). The original vegetation layer was created in 2005 using a baseline image dataset created from 2000/01 Emerge imagery flown in early spring. The original map has been used to monitor and evaluate the habitat in the Western Riverside County Multi-species Habitat Conservation Plan (MSHCP). An update to the original map was needed to address changes in vegetation makeup that have occurred in the intervening years due to widespread and multiple burns in the mapping area, urban expansion, and broadly occurring vegetation succession.The update conforms to the standards set by the National Vegetation Classification System (NVCS) published in 2008 by the Federal Geographic Data Committee. (FGDC-STD-005-2008, Vegetation Subcommittee, Federal Geographic Data Committee, February 2008) The update also adheres to the vegetation types as represented in the 2008-second edition of the Manual of California Vegetation (MCV2). Extensive ground based field data both within and nearby the western Riverside County mapping area has been acquired since the completion of the project in 2005. This additional data has resulted in the reclassification of several vegetation types that are addressed in the updated vegetation map. The mapping area covers 1,017,364 acres of the original 1.2 million acres mapped in the 2005 study. The new study covers portions of the Upper Santa Ana River Valley, Perris Plain, and the foothills of the San Jacinto and Santa Ana Mountains but excludes US Forest Service land. The final geodatabase includes both an updated 2012 vegetation map and a retroactively corrected 2005 vegetation base layer. Vegetative and cartographic comparisons between the newly created 2012 image-based map and the original vegetation map produced in 2005 are described in this report.The Update mapping was performed using baseline digital imagery created in 2012 by the US Department of Agriculture – Farm Service Agency’s National Agricultural Imagery Program (NAIP). Vegetation units were mapped using the National Vegetation Classification System (NVCS) to the Alliance and Association level as depicted in the MCV2. Approximately 55% of the study area is classified to vegetated or naturally occurring sparsely vegetated types; the remaining 45% is unvegetated, with over a third (36%) in urban development and an additional 9% in agriculture. The major tasks for the Update project consisted of updating the original mapping classification to conform to the changes and refinements to the MCV2 classification, updating the existing vegetation map to 2012 conditions, retroactively correcting the 2005 vegetation interpretations, creating the final report and project metadata, and producing the final vegetation geodatabase. After completion of the original 2005 vegetation map, CDFW crosswalked the original mapping units to the NVCS hierarchical names as defined in the Manual of California Vegetation (MCV).The original crosswalk was revised during the Update effort to reflect changes in the original MCV classification as depicted in the second edition (MCV2). Changes were minor and did not result in a significant effort in the updating process. The updating process in many steps is similar to the creation of the original vegetation map. First, photo interpreters review the study area for terrain, environmental features, and probable vegetation types present. Questionable photo signatures on the new baseline imagery (2012 NAIP) were compared to the original 2000/01 Emerge imagery. Photo signatures for a given vegetation polygon were correlated between the two image datasets. Production level updates to the linework and labeling commenced following the correlation of the two baseline image datasets and the subsequent refinement of photo interpretation criteria & biogeographical descriptions of the types. Existing datasets depicting topography, fire history, climate and past vegetation gathering efforts aided photo interpreters in their delineations and floristic assignments during the updating effort. The production updating effort took approximately 11 months.

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 a USNVC association-level vegetation map that satisfied the standards of the USGS/NPS Vegetation Mapping Program, the alliance-level vegetation map developed by Agius was edited and refined onscreen in ArcGIS 9.1. The Agius (2003b) vegetation map was not developed following the USGS/NPS Vegetation Mapping Program standards and therefore could not be used as the final vegetation classification map. Polygons that represented vegetation were readily attributed to existing associations in the U.S. National Vegetation Classification. Polygons that represented intensive land uses were attributed with names modified from the Anderson Level II categories.. Because Saugus Iron Works National Historic Park is a small park with only 21 polygons, the mapping did not rely entirely on aerial photograph interpretation, but also incorporated lines sketched onto a hard-copy map on site. Using ArcGIS 9.1, polygon boundaries were drawn onscreen based on the plot data and additional field observations. Each polygon was attributed with the name of an USNVC association or an Anderson Level II (modified) land use/land cover map class based on plot data, field observations, aerial photography signatures, and topographic maps. The shapefile was projected in Universal Transverse Mercator Zone 19 North, North American Datum 1983, meters, in ArcGIS 9.1.

This map package contains information on vegetation type classes, tree canopy cover, tall shrub canopy cover, and tree size from four existing vegetation mapping projects. These maps were prepared for the Chugach National Forest to provide up-to-date and more complete information about vegetative communities, structure and patterns across the Forest. The Copper River Delta vegetation dominance type product was completed in 2013; the Kenai Peninsula data products were completed in 2017; Cordova was completed in 2021; and the Glacier project area was completed in 2022.Nearly 11 million terrestrial acres were mapped through a partnership between the Geospatial Technology and Applications Center (GTAC), Chugach National Forest, the Alaska Regional Office, and other State, Tribal and Federal agencies. The Chugach National Forest and their partners prepared the regional classification system and identified the desired map units (map classes) that characterized the existing vegetation. GTAC served as the technical lead for developing the mapping methodology that produced the final data products. A combination of field and image interpreted reference data were used to inform the map models. Federal, State, and contracted staff collected plot data on the ground, while Ducks Unlimited and GTAC personnel collected reference information from a helicopter. Classification and regression models were used to characterize modeling units (mapping polygons) with the following vegetation attributes: 1) vegetation type; 2) tree canopy cover; 3) tree size; and 4) tall shrub canopy cover. The minimum map feature depicted is 0.25 acres. Map products were designed according to National Forest Service vegetation mapping standards and are stored in Federal databases.For more detailed information on mapping methodology please see the individual project reports and the Chugach Regional Vegetation Mapping Report.

This web map contains data layers viewable for ten mid-level existing vegetation maps (1:100,000) prepared for the Tongass National Forest, Ketchikan Misty Fjords Project Area to provide up-to-date and more complete information about vegetative communities, structure, and patterns across the project area. Approximately 4.6 million acres, 3.5 million acres of which are terrestrial lands including inland waterbodies and rivers, were mapped through a partnership between the Geospatial Technology and Applications Center (GTAC), Tongass National Forest, and the Alaska Regional Office. The Tongass National Forest and their partners prepared the regional classification system, identified the desired map units (map classes) and provided general project management. GTAC provided project support and expertise in vegetation mapping.Maps are available for the following vegetation characteristics: vegetation type, tree canopy cover, trees per acre (TPA) for trees ≥ 1’ tall, trees per acre for trees ≥ 6” diameter at breast height (DBH), quadratic mean diameter (QMD) for trees ≥ 2” DBH, QMD for trees ≥ 9” DBH, thematic tree size, biomass for trees ≥ 2” DBH, gross board feet (GBF) for trees ≥ 9” DBH, and stand density index (SDI) for trees ≥ 9” DBH.The minimum map feature depicted on the map is 0.25 acres. The map products conform to the mid-level mapping standards referenced in the Existing Vegetation Classification, Mapping, and Inventory Technical Guide (Nelson et al. 2015). This map product was generated using imagery primarily acquired in 2019 – 2022, reference information collected in the summers of 2019 – 2022, and LiDAR data from 2018. Therefore, the final map can be considered indicative of the existing vegetation conditions found within the project boundary in 2022.For more detailed information on mapping methodology please see the Ketchikan Misty Fjords Existing Vegetation Project Report.

Dataset representing vegetation mapping performed by the U.S. Forest Service for the South Coast region of California. This dataset, commonly referred to as CALVEG, provides comprehensive spatial and tabular data for existing vegetation. Map attributes consist of vegetation types using the CALVEG classification system and forest structural characteristics such as tree and shrub canopy cover and tree stem diameters. Two vegetation classifications are referenced within CALVEG, “vegetation alliances,” the most detailed classification thatemphasizes species composition, and “wildlife habitat relationships” (WHR), which emphasizes vegetation structure characteristics. CITY-OWNED DATAEvery reasonable effort has been made to assure the accuracy of the data provided; nevertheless, some information may not be accurate. The City of Los Angeles assumes no responsibility arising from use of this information. THE MAPS AND ASSOCIATED DATA ARE PROVIDED WITHOUT WARRANTY OF ANY KIND, either expressed or implied, including but not limited to, the implied warranties of merchantability and fitness for a particular purpose. INVASIVE PLANT DATAUse limitationsThe USDA Forest Service makes no warranty, expressed or implied, including the warranties of merchantability and fitness for a particular purpose, nor assumes any legal liability or responsibility for the accuracy, reliability, completeness or utility of these geospatial data, or for the improper or incorrect use of these geospatial data. These geospatial data and related maps or graphics are not legal documents and are not intended to be used as such. The data and maps may not be used to determine title, ownership, legal descriptions or boundaries, legal jurisdiction, or restrictions that may be in place on either public or private land. Natural hazards may or may not be depicted on the data and maps, and users should exercise due caution. The data are dynamic and may change over time. The user is responsible to verify the limitations of the geospatial data and to use the data accordingly.EXISTING VEGETATION DATAUse limitationsThis product is reproduced from geospatial information prepared by the U.S. Department of Agriculture, Forest Service. By removing the contents of this package or taking receipt of these files via electronic file transfer methods, you understand that the data stored on this media is in draft condition. Represented features may not be in an accurate geographic location. The Forest Service makes no expressed or implied warranty, including warranty of merchantability and fitness, with respect to the character, function, or capabilities of the data or their appropriateness for any user's purposes. The Forest Service reserves the right to correct, update, modify, or replace this geospatial information without notification. For more information, contact the Remote Sensing Lab, 916-640-1256.The Forest Service uses the most current and complete data available. GIS data and product accuracy may vary. They may be developed from sources of differing accuracy; accurate only at certain scales; based on modeling or interpretation; incomplete while being created or revised; etc. Using GIS products for purposes other than those for which they were created, may yield inaccurate or misleading results. The Forest Service reserves the right to correct, update, modify or replace GIS products without notification.TERM OF USECALVEG DATADisclaimer: The U.S. Department of Agriculture, Forest Service, has prepared this geospatial information. By taking receipt of these files via electronic file transfer methods, you understand that the data stored on this media is in draft condition. Represented features may not be in an accurate geographic location. The Forest Service makes no expressed or implied warranty, including warranty of merchantability and fitness, with respect to the character, function, or capabilities of the data or their appropriateness for any user's purposes. The Forest Service reserves the right to correct, update, modify, or replace this geospatial information without notification. For more information, contact the Regional Geospatial Data Manager, (707) 562-9106.