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.

This dataset combines the work of several different projects to create a seamless data set for the contiguous United States. Data from four regional Gap Analysis Projects and the LANDFIRE project were combined to make this dataset. In the northwestern United States (Idaho, Oregon, Montana, Washington and Wyoming) data in this map came from the Northwest Gap Analysis Project. In the southwestern United States (Colorado, Arizona, Nevada, New Mexico, and Utah) data used in this map came from the Southwest Gap Analysis Project. The data for Alabama, Florida, Georgia, Kentucky, North Carolina, South Carolina, Mississippi, Tennessee, and Virginia came from the Southeast Gap Analysis Project and the California data was generated by the updated California Gap land cover project. The Hawaii Gap Analysis project provided the data for Hawaii. In areas of the county (central U.S., Northeast, Alaska) that have not yet been covered by a regional Gap Analysis Project, data from the Landfire project was used. Similarities in the methods used by these projects made possible the combining of the data they derived into one seamless coverage. They all used multi-season satellite imagery (Landsat ETM+) from 1999-2001 in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-natural vegetation. Vegetation classes were drawn from NatureServe's Ecological System Classification (Comer et al. 2003) or classes developed by the Hawaii Gap project. Additionally, all of the projects included land use classes that were employed to describe areas where natural vegetation has been altered. In many areas of the country these classes were derived from the National Land Cover Dataset (NLCD). For the majority of classes and, in most areas of the country, a decision tree classifier was used to discriminate ecological system types. In some areas of the country, more manual techniques were used to discriminate small patch systems and systems not distinguishable through topography. The data contains multiple levels of thematic detail. At the most detailed level natural vegetation is represented by NatureServe's Ecological System classification (or in Hawaii the Hawaii GAP classification). These most detailed classifications have been crosswalked to the five highest levels of the National Vegetation Classification (NVC), Class, Subclass, Formation, Division and Macrogroup. This crosswalk allows users to display and analyze the data at different levels of thematic resolution. Developed areas, or areas dominated by introduced species, timber harvest, or water are represented by other classes, collectively refered to as land use classes; these land use classes occur at each of the thematic levels. Raster data in both ArcGIS Grid and ERDAS Imagine format is available for download at http://gis1.usgs.gov/csas/gap/viewer/land_cover/Map.aspx Six layer files are included in the download packages to assist the user in displaying the data at each of the Thematic levels in ArcGIS. In adition to the raster datasets the data is available in Web Mapping Services (WMS) format for each of the six NVC classification levels (Class, Subclass, Formation, Division, Macrogroup, Ecological System) at the following links. http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Class_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Subclass_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Formation_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Division_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Macrogroup_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_Ecological_Systems_Landuse/MapServer

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 =

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 2015) 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.

This web map 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.

The Department of Defense and the other desert managers are developing and organizing scientific information needed to better manage the natural resources of the Mojave Desert. One product from this endeavor is the Central Mojave Vegetation Map (developed by US Dept of Interior, USGS Western Ecological Research Center and Southwest Biological Science Center) that displays vegetation and other land cover types in the eastern Mojave of California. Map labels represent alliances and groups of alliances as described by the U.S. National Vegetation Classification. The nominal minimum mapping unit is 5 hectares. Each map unit is labeled by a primary land cover type and a secondary type where applicable. In addition, the source of data for labeling each map unit is also identified in the attribute table for each map unit. Data were developed using field visits, 1:32,000 aerial photography, SPOT satellite imagery, and predictive modeling.

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.

description: 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 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.

The National Park Service (NPS), in conjunction with the Biological Resources Division BRD) of the U.S. Geological Survey (USGS), has implemented a program to "develop a uniform hierarchical vegetation methodology" at a national level. The program will also create a geographic information system (GIS) database for the parks under its management. The purpose of the data is to document the state of vegetation within the NPS service area during the 1990's, thereby providing a baseline study for further analysis at the Regional or Service-wide level. The vegetation at Devils Tower National Monument was mapped using 1:16,000 scale U.S. Forest Service Color Aerial Photography acquired July 29, 1993. The mapping classification used two separate classification systems. All natural vegetation used the National Vegetation Classification System (NVCS) as a base. The vegetation classification was created after extensive on site sampling and numerical analysis. The vegetation map units were derived from the vegetation classification. Other non-natural or cultural mapping units used the Anderson Level II classification system. The mapped area includes a buffer around the Monument boundary.

This mapping effort originates from a long-term vegetation monitoring program that is part of a larger Inventory and Monitoring (I&M) program started by the National Park Service (NPS). I&M goals are, among others, to map the vegetation of all national parks and monuments and provide a baseline inventory of vegetation. The I&M program currently works in close cooperation with the Biological Resources Division (BRD) of the United States Geological Survey (USGS). The USGS/BRD continues overall management and oversight of all ongoing mapping efforts in close cooperation with the NPS.

The purposes of the mapping effort are varied and include the following: Provides support for NPS Resources Management. Promotes vegetation-related research for both NPS and USGS/BRD. Provides support for NPS Planning and Compliance. Adds to the information base for NPS Interpretation. Assists in NPS Operations.

The geographic extent of the data set is Devils Tower National Monument and about a 2 mile environs around Monument Boundaries - Black Hills, Wyoming, USA.

Information was obtained from "http://biology.usgs.gov/npsveg/deto/metadetospatial.html" and converted to NASA Directory Interchange Format.

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.

Coastwide vegetation surveys have been conducted multiple times over the past 50 years (e.g., Chabreck and Linscombe 1968, 1978, 1988, 1997, 2001, and 2013) by the Louisiana Department of Wildlife and Fisheries (LDWF) in support of coastal management activities. The last survey was conducted in 2013 and was funded by the Louisiana Coastal Protection and Restoration Authority (CPRA) and the U.S. Geological Survey (USGS) as a part of the Coastal Wetlands Planning, Protection, and Restoration Act (CWPPRA) monitoring program. These surveys provide important data that have been utilized by federal, state, and local resource managers. The surveys provide information on the condition of Louisiana’s coastal marshes by mapping plant species composition and vegetation change through time. During the summer of 2021, the U.S. Geological Survey, Louisiana State University, and the Louisiana Department of Wildlife and Fisheries jointly completed a helicopter survey to collect data on 2021 veget ...

This dataset provides 30m resolution maps of the fraction of green vegetation within tidal marshes for six estuarine regions of the conterminous United States: Cape Cod, MA; Chesapeake Bay, MD; Everglades, FL; Mississippi Delta, LA; San Francisco Bay, CA; and Puget Sound, WA. Maps were derived from a 1m classification of 2013 to 2015 National Agriculture Imagery Program (NAIP) images as tidal marsh green vegetation, non-vegetation, and open water. Using this high-resolution map, the percent of each class within Landsat pixel extents was calculated to produce a 30m fraction of green vegetation map for each region.

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.

The map shows the 8-class vegetation cover developed from Landsat TM data used for the SICS area.

Yukon Flats National Wildlife Refuge (YKF NWR) and Koyukuk NWR (KUK NWR), U.S. Fish and Wildlife Service (USFWS), initiated a project with the U.S. Geological Survey Earth Resources Observation and Science (EROS) Center to acquire map products needed for moose habitat assessment. The objective of this work was to create a suite of products which included: Estimated Vegetation Heights, probability of Willow Estimates, and Vegetation Type Maps. These products are based on spectral characteristics found in bands 2 through 7 of Landsat 8 OLI scenes processed to surface reflectance, acquired in summer of 2013, and late winter of 2014. Training data was collected by fixed wing aircraft and helicopter by USFWS refuge staff, and extrapolated by the methods described. This project, “ Yukon Flats NWR willow mapping” (PI: Delia Vargas Kretsinger) was funded through the USFWS Inventory and Monitoring program via an Interagency Agreement between the USGS EROS and the USFWS – Alaska Regiona ...

This shapefile is an vegetation map of Colonial National Historical Park, Virginia. It was developed by The Virginia Department of Conservation and Recreation, Division of Natural Heritage in cooperation with North Carolina State University's Center for Earth Observation for the Northeast Region of the National Park Service. The data was created following general guidelines set forth by the USGS-NPS Vegetation Mapping Program. Map classes are crosswalked to the U.S. National Vegetation Classification (USNVC) or level II of the Andersons land use land cover classification system. Crosswalks to the USNVC were determined on September 27, 2007. The map is based on field work performed in the summers of 2003-2005 and photo interpretation of aerial photo mosaics produced by North Carolina State University Center for Earth Observation from photography obtained in October 2001 and March 2002.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for American Memorial Park. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. To produce the spatial database and map layer, 0.6-meter, 4-band Quickbird satellite imagery from 2006 was provided by PACN. By comparing the signatures on the imagery to field and ground data 27 map classes (16 vegetated, three barren, and eight land-use / land-cover) were developed and directly crosswalked or matched to their corresponding NVC 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 48 independent accuracy assessment points.