The Gap Analysis Program (GAP) produces data and tools that help meet critical national challenges such as biodiversity conservation, renewable energy development, climate change adaptation, and infrastructure investment. The GAP national land cover includes data on the vegetation and land-use patterns of the United States, including Alaska, Hawaii, and Puerto Rico. This national dataset combines land cover data generated by regional GAP projects with Landscape Fire and Resource Management Planning Tools (LANDFIRE) data (http://www.landfire.gov/). LANDFIRE is an interagency vegetation, fire, and fuel characteristics mapping program, sponsored by the U.S. Department of the Interior and the U.S. Department of Agriculture Forest Service.

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. 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.

LANDFIRE's (LF) 2020 update (LF 2020) Existing Vegetation Type (EVT) represents the current distribution of the terrestrial ecological systems classification developed by NatureServe for the western hemisphere. In this context, a terrestrial ecological system is defined as a group of plant community types that tend to co-occur within landscapes with similar ecological processes, substrates, and/or environmental gradients. EVT also includes ruderal or semi-natural vegetation types within the U.S. National Vegetation Classification [(NVC) https://usnvc.org/]. See the EVT product page (https://www.landfire.gov/evt.php) for more information about ecological systems and NVC. EVT is mapped using decision tree models, field data, Landsat imagery, topography, and biophysical gradient data. Decision tree models are developed separately for tree, shrub, and herbaceous lifeforms which are then used to produce a lifeform specific EVT product. These models are generated for each Environmental Protection Agency (EPA) Level III Ecoregion (https://www.epa.gov/eco-research/ecoregions). Riparian, alpine, sparse, and other site-specific EVTs are constrained by predetermined masks. Urban and developed areas are derived from the National Land Cover Database (NLCD), and the Microsoft Building Footprint dataset, whereas agricultural lands originate from the Cropland Data Layer (CDL) and the California Statewide Crop Mapping layer. Burnable developed classes are identified from building footprint dataset thresholds. LF 2020 retains circa 2016 EVT labels except where shifts in urban, recently disturbed, agriculture, and developed ruderal classes occurred for 2020. EVT is no longer synchronized in ST-SIM outputs for disturbed areas in LF 2020. LF uses EVT as an input for LF 2020 Fuel Vegetation Type (FVT).These data have been made publicly available from an authoritative source other than this Atlas and data should be obtained directly from that source for any re-use. See the original metadata from the authoritative source for more information about these data and use limitations. The authoritative source of these data can be found at the following location: LANDFIRE Program: Data Product Mosaic DownloadsBoundary Source: LANDFIRE 2020 Existing Vegetation Type (EVT) CONUS

The GAP/LANDFIRE National Terrestrial Ecosystems represents a highly thematically detailed land cover map of the U.S. The GAP/LANDFIRE National Terrestrial Ecosystems dataset is produced by the U.S. Geological Survey in collaboration with the LANDFIRE Program. The GAP and LANDFIRE produce data and tools that help meet critical national challenges such as biodiversity conservation, fire and fuels modeling, renewable energy development, climate change adaptation, and infrastructure investment. The GAP National Terrestrial Ecosystems - Ver 3.0 is a 2011 update of the National Gap Analysis Program Land Cover Data - Version 2.2 for the conterminous U.S. The map legend includes types described by NatureServe's Ecological Systems Classification (Comer et al. 2002) as well as land use classes described in the National Land Cover Dataset 2011 (Homer et al. 2015). These data cover the entire continental U.S. and are a spatially continuous data layer. These raster data have a 30 m x 30 m cell resolution. National GAP Land Cover combines ecological system data from previous GAP projects in the Southwest , Southeast, and Northwest United States with recently updated California data. For Alaska and areas of the continental United States where ecological system-level GAP data has not yet been developed, data from the LANDFIRE project were used. This approach allowed GAP mappers to construct a seamless representation of ecological system distributions across the conterminous United States. Currently LANDFIRE is leading a remap effort based on 2016 Landsat imagery as well as new field data. In addition to the Ecological Systems Classification maps can be rendered using the Federal Geographic Data Committee’s National Vegetation Classification System at the Group level and higher.

This raster dataset is a detailed (1-acre minimum), hierarchically organized vegetation cover map produced by computer classification of combined two-season pairs of early-1990s Landsat 4/5 Thematic Mapper (TM) satellite imagery, as part of the Upper Midwest Gap Analysis Program (UMGAP)( http://www.umesc.usgs.gov/reports_publications/psrs/psr_1999_04.html ) of the U.S. Geological Survey. Units of analysis were Minnesota Ecological Classification System (ECS)( http://www.dnr.state.mn.us/ecs/index.html ) subsections subdivided by TM scenes. GAP typology and classification protocols are closely comparable across Minnesota, Wisconsin and Michigan.

LANDFIRE's (LF) 2020 update (LF 2020) Existing Vegetation Type (EVT) represents the current distribution of the terrestrial ecological systems classification developed by NatureServe for the western hemisphere. In this context, a terrestrial ecological system is defined as a group of plant community types that tend to co-occur within landscapes with similar ecological processes, substrates, and/or environmental gradients. EVT also includes ruderal or semi-natural vegetation types within the U.S. National Vegetation Classification [(NVC) https://usnvc.org/]. See the EVT product page (https://www.landfire.gov/evt.php) for more information about ecological systems and NVC. EVT is mapped using decision tree models, field data, Landsat imagery, topography, and biophysical gradient data. Decision tree models are developed separately for tree, shrub, and herbaceous lifeforms which are then used to produce a lifeform specific EVT product. These models are generated for each Environmental Protection Agency (EPA) Level III Ecoregion (https://www.epa.gov/eco-research/ecoregions). Riparian, alpine, sparse, and other site-specific EVTs are constrained by predetermined masks. Urban and developed areas are derived from the National Land Cover Database (NLCD), and the Microsoft Building Footprint dataset, whereas agricultural lands originate from the Cropland Data Layer (CDL) and the California Statewide Crop Mapping layer. Burnable developed classes are identified from building footprint dataset thresholds. LF 2020 retains circa 2016 EVT labels except where shifts in urban, recently disturbed, agriculture, and developed ruderal classes occurred for 2020. EVT is no longer synchronized in ST-SIM outputs for disturbed areas in LF 2020. LF uses EVT as an input for LF 2020 Fuel Vegetation Type (FVT).These data have been made publicly available from an authoritative source other than this Atlas and data should be obtained directly from that source for any re-use. See the original metadata from the authoritative source for more information about these data and use limitations. The authoritative source of these data can be found at the following location: LANDFIRE Program: Data Product Mosaic DownloadsBoundary Source: LANDFIRE 2020 Existing Vegetation Type (EVT) CONUS

The GAP/LANDFIRE National Terrestrial Ecosystems data represents a detailed vegetation and land cover classification for the Conterminous U.S., Alaska, Hawaii, and Puerto Rico.GAP/LF 2011 Ecosystems for the Conterminous U.S. is an update of the National Gap Analysis Program Land Cover Data - Version 2.2. Alaska ecosystems have been updated by LANDFIRE to 2012 conditions (LANDFIRE 2012). Hawaii and Puerto Rico data represent the 2001 time-frame (Gon et al. 2006, Gould et al. 2008). The classification scheme used for the Alaska and the lower 48 states is based on NatureServe's Ecological System Classification (Comer et al. 2003), while Puerto Rico and Hawaii's map legend are based on island specific classification systems (Gon et al. 2006, Gould et al. 2008).

The Gap Analysis Project (GAP) Analytical Database represents a synthesis of three core datasets for the conterminous U.S. Specifically 1) the GAP/LANDFIRE National Terrestrial Ecosystems_2011; 2) the Protected Areas Database of the United States (PAD-US) 1.4; and 3) the Species Ranges and Habitat Distribution Models for all terrestrial vertebrates. This database provides a mechanism to efficiently obtain summary statistics of those for a variety of spatial extents, including US states, US counties, Landscape Conservation Cooperation Network Areas, EPA's Level III-IV Ecoregions of the United States, and Level I-III Ecoregions of North America and 12-digit (6th level) hydrologic units.

A vegetation and land cover map for North Dakota was created as part of the North Dakota Gap Analysis Project for the U. S. Geological Survey's National Gap Analysis Program. Vegetation and land cover was mapped from a multi-temporal analysis of May, July, and September Landsat Thematic Mapper images acquired from August 1992 to September 1998. Natural and semi-natural vegetation categories are cross-walked and described with reference to the National Vegetation Classification System. Digital National Wetland Inventory data produced by the U.S. Fish and Wildlife Service was used in mapping wetlands.

Constraints:
The data provide a coarse generalized abstraction of the geographic distribution of land cover circa 1998 for North Dakota. These data were produced for an intended application at the state and at the national scale by aggregation of the data with GAP analysis products from other states. These data may not be appropriate for local or large-scale analyses (>1:100,000 scale). Notification of the use of the data and acknowledgement of the U.S. Geological Survey would be appreciated in products derived from the use of the data. Not to be used for navigation, for informational purposes only. See full disclaimer for more information.

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 Gap Analysis Program (GAP) is an element of the U.S. Geological Survey (USGS). GAP helps to implement the Department of Interior?s goals of inventory, monitoring, research, and information transfer. GAP has three primary goals: 1 Identify conservation gaps that help keep common species common; 2 Provide conservation information to the public so that informed resource management decisions can be made; and 3 Facilitate the application of GAP data and analysis to specific resource management activities. To implement these goals, GAP carries out the following objectives: --Map the land cover of the United States --Map predicted distributions of vertebrate species for the U.S. --Map the location, ownership and stewardship of protected areas --Document the representation of vertebrate species and land cover types in areas managed for the long-term maintenance of biodiversity --Provide this information to the public and those entities charged with land use research, policy, planning, and management --Build institutional cooperation in the application of this information to state and regional management activities. GAP provides the following data and web services: The Protected Areas Database of the United States (PAD-US) is a geodatabase that illustrates and describes public land ownership, management and other conservation lands, including voluntarily provided privately protected areas. The PADUS GAP Status Layer web service can be found at http://gis1.usgs.gov/arcgis/rest/services/gap/PADUS_Status/MapServer . The Land Cover Data creates a seamless data set for the contiguous United States from the four regional Gap Analysis Projects and the LANDFIRE project. The 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 . In addition 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 The GAP species range data show a coarse representation of the total areal extent of a species or the geographic limits within which a species can be found (Morrison and Hall 2002). The GAP species distribution models represent the areas where species are predicted to occur based on habitat associations. A full report documenting the parameters used in each species model can be found via: http://gis1.usgs.gov/csas/gap/viewer/species/Map.aspx Web map services for species distribution models can be accessed from: http://gis1.usgs.gov/arcgis/rest/services/NAT_Species_Birds http://gis1.usgs.gov/arcgis/rest/services/NAT_Species_Mammals http://gis1.usgs.gov/arcgis/rest/services/NAT_Species_Amphibians http://gis1.usgs.gov/arcgis/rest/services/NAT_Species_Reptiles A table listing all of GAP's available web map services can be found here: http://gapanalysis.usgs.gov/species/data/web-map-services/

This layer contains detailed land cover data representing ecological systems. These data were developed by NatureServe and are "intended to represent recurring groups of biological communities that are found in similar physical environments and are influenced by similar dynamic ecological processes, such as fire or flooding. They are intended to provide a classification unit that is readily mappable, often from remote imagery, and readily identifiable by conservation and resource managers in the field." -- NatureServeFrom the USGS GAP Analysis Program Website: "National GAP Land Cover Data provide information on the distribution of native vegetation types, modified and introduced vegetation, developed areas, and agricultural areas of the United States. For all areas of the county except Hawaii, native vegetation areas are classified to the Ecological System types developed by NatureServe. Ecological Systems provide detailed information on the vegetative communities of an area that is not available in most other regional or national land cover products. This level of thematic detail makes possible the construction of wildlife habitat distribution models, and the construction of complicated hydrology and fire dynamics models, and many other applications. Information about land cover is a key component of effective conservation planning and the management of biological diversity as it is used to build predictive models of wildlife distribution and biodiversity across large geographic areas. When used in conjunction with protected areas data (PAD-US), land cover data can be used to identify habitat types that may be under-protected so management activities can be adjusted. These maps and data can be used to identify those places in the country with sufficient good quality habitat to support wildlife, a key step in developing sound conservation plans."Dataset SummaryThis layer contains data from the USGS CAP Land Cover dataset. These data include detailed vegetation and land use patterns for the continental United States. The dataset incorporates the Ecological System classification system developed by NatureServe to represent natural and semi-natural land cover. The 590 land use classes in the data set can be displayed at three levels of detail, from general (8 classes) to most detailed. The Land Cover Data Set can be used to identify those places in the country with sufficient good quality habitat to support wildlife, a key step in developing sound conservation plans.Additional resources:Ecological Systems of the United States, A Working Classification of the U.S. Terrestrial SystemsLandcover Data and Modeling from the USGS National Gap Analysis Program (GAP) | Land Cover Data PortalLink to source metadataWhat can you do with this layer?This layer has query, identify, and export image services available. The layer is restricted to an 24,000 x 24,000 pixel limit, which represents an area of nearly 450 miles on a side.This layer is part of a larger collection of landscape layers that you can use to perform a wide variety of mapping and analysis tasks.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. Following the vegetation data analysis, the vegetation cover-type map was edited and refined to develop a preliminary association-level vegetation map. Using ArcView 3.2, polygon boundaries were revised onscreen based on the plot data, field observations, classification analyses, aerial photography signatures, and topographic maps. Each polygon was assigned the name of a preliminary vegetation association based on the five information sources listed above. A mirror stereoscope type F-71 and a Bausch and Lomb zoom stereoscope were used to interpret the aerial photography signatures. The field-collected “true” or “reference” GPS coordinates for the remaining 41 points were compared to the coordinates obtained from the mosaic viewed in ArcMap.

Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

The data covers three time periods (1970-1999), (2035-2064), and (2070-2099) for 59 vegetation types based on a hybrid vegetation map derived from the GAP vegetation classification system (http://gapanalysis.usgs.gov/gaplandcover/) together with climate covariates (historic), and environmental covariates driven by MC2, a dynamic global vegetation model (DGVM). Current climate data was based on PRISM (www.prism.oregonstate.edu/). Future climate data was based on downscaled projections (4km) developed by the Multivariate Adaptive Constructed Analogs (MACA) project. Models were trained using data from Oregon, Washington, California, and Nevada. Areas representing developed/urban, developed/open space, pasture/hay, and cropland/agriculture in the GAP layer were kept the same in future periods and any other veg types were masked out from areas represented by any of these anthropogenic classes.

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. In areas of the county (central U.S., Northeast) that have not yet been covered by a regional Gap Analysis Project, data from the Landfire project was used. In 2009 Landfire data was combined by the Landscope project into one uniform coverage. This compiled data was the data pulled into this project. 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). 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.

Constraints:
The data provide a coarse generalized abstraction of the geographic distribution of land cover circa 1998 for North Dakota. These data were produced for an intended application at the state and at the national scale by aggregation of the data with GAP analysis products from other states. These data may not be appropriate for local or large-scale analyses (>1:100,000 scale). Notification of the use of the data and acknowledgement of the U.S. Geological Survey would be appreciated in products derived from the use of the data. Not to be used for navigation, for informational purposes only. See full disclaimer for more information.

Remotely sensed land cover datasets have been increasingly employed in studies of wildlife habitat use. However, meaningful interpretation of these datasets is dependent on how accurately they estimate habitat features that are important to wildlife. We evaluated the accuracy of the GAP dataset, which is commonly used to classify broad cover categories (e.g., vegetation communities) and LANDFIRE datasets, which are classify narrower cover categories (e.g., plant species) and structural features of vegetation. To evaluate accuracy, we compared classification of cover types and estimates of percent cover and height of sagebrush (Artemisia spp.) derived from GAP and LANDFIRE datasets to field-collected data in winter habitats used by greater sage-grouse (Centrocercus urophasianus). Accuracy was dependent on the type of dataset used as well as the spatial scale (point, 100-m, 1-km and 5-km) and biological level (community versus dominant species) investigated. GAP datasets had the highest overall classification accuracy of broad sagebrush cover types (46.1%) compared to LANDFIRE datasets for narrower cover types (43.8% community-level; 42.6% species-level). Percent cover and height were not accurately estimated in the LANDFIRE dataset. Our results suggest that researchers must be cautious when applying GAP or LANDFIRE datasets to classify narrow categories of land cover types or to predict percent cover or height of sagebrush within sagebrush-dominated landscapes. We conclude that ground-truthing is critical for successful application of land cover datasets in landscape-scale evaluations and management planning, particularly when wildlife use relatively rare habitat types compared to what is available.

This reference contains the imagery data used in the completion of the baseline vegetation inventory project for the NPS park unit. Orthophotos, raw imagery, and scanned aerial photos are common files held here. Color infrared, stereo pair 1:12,000 scale aerial photography for a digital orthophoto mosaic of Delaware Water Gap National Recreation Area was acquired from overflights on March 28, April 7, and April 11, 2002, during leaf-off conditions, by Kucera International. The photography, a total of 1,047 air photos that cover the park as well as a relatively large buffer area outside the park, was delivered to the National Park Service, quality checked, accepted as provided, and sent to North Carolina State University.

USGS 2010 GAP Landcover Updated: Dec 07, 2013GAP data were downloaded from the USGS Gap site, then redesigned into boundary based overlay symbology with separate labelling services, for use at 3 basic scale ranges: Base Scale 0-144k, mid scale 250k to 4m
and an outer scale 9m to 36m. This is a complete set of tiles for the southwest regionThe GAP national land cover data version 2 provides detailed information on the vegetation of the United States using consistent satellite base data and classification systems. This allows data users to make conservation or land use planning decisions for the entire range of a habitat type across administrative boundaries.

The second version of the GAP land cover data combines ecological system data from
previous GAP projects in the Southwest, Southeast, and Northwest United States with
recently updated California data. For Alaska ,and areas of the continental United
States, where ecological system-level GAP data has not yet been developed, data
from the LANDFIRE project used. This approach allowed GAP mappers to construct a
seamless representation of ecological system distributions across the continental
United States and Alaska. In Hawaii, data created by the Hawaii GAP project was
used. This data set uses a classification system developed by the project for Hawaii
and not the ecological system.


The Alaska and Continental U.S. portion of the data set contains 680 Ecological
systems and 28 land use, introduced vegetation or disturbed classes. The Hawaii
data contains 28 natural vegetation classes and nine land use, introduced vegetation
or disturbed classes.


Frequently, this high number of classes provides a level of detail that exceeds
a user’s needs. To accommodate these users, we have crosswalked the ecological system
level data to the five highest levels of the National Vegetation Classification
System( NVC). The vegetation features used to distinguish these classes range from
growth form, and climate regimes at the Class level to regional differences in substrate
and hydrology at the Macrogroup level (Table 1; http://biology.usgs.gov/npsveg/nvcs.html).
The NVC levels provide the user with a variety of options allowing the choice of
making a map of the Continental U.S. with eleven classes at the NVC Class level
to 583 classes at the Ecological system level.


Features used to delineate National Vegetation Classification (NVC) levels:

Class dominant general growth forms adapted to basic moisture, temperature, and/or substrate or aquaticSubclass global macroclimatic factors driven primarily by latitude and continental position, or reflect overriding substrate or aquatic conditionsFormation global macroclimatic conditions as modified by altitude, seasonality of precipitation, substrates, hydrological conditionsDivision continental differences in mesoclimate, geology, substrates, hydrology, disturbance regimesMacrogroup sub-continental to regional differences in mesoclimate, geology, substrates, hydrology, disturbance regimesGap Analysis Program (GAP) Land Cover ViewerThis 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. 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.