Identifies developed backcountry trails within Denali NP. Most trails are located within the park frontcountry. The vast majority of the park backcountry is trail-less. A number of trails, however have been developed within the developed portions of the park for visitor use.

These ESRI shape files are of National Park Service tract and boundary data that were created by the Land Resources Division. Tracts are numbered and created by the regional cartographic staff at the Land Resources Program Centers and are associated to the Land Status Maps. This data should be used to display properties that NPS owns and properties that NPS may have some type of interest such as scenic easements or right of ways.

These data depict Road Segment Centerlines and attributes for roads that are managed and maintained by the National Park Service. Road data are used for many purposes including planning and management, mapping and condition assessment, routing and navigation, public information, emergency response, and research. A current, accurate representation of park roads is needed for national reporting and a variety of mapping requirements at all levels of the National Park Service and the general public. A National-level dataset allows the NPS to communicate a consistent and high-quality roads database to NPS staff, partners, visitors, and entities that produce maps and location-based services of park units. The collection, storage, and management of road-related data are important components of everyday business activities in many Federal and State land-managing agencies, road organizations, and businesses. From a management perspective, road data must often mesh closely with other types of infrastructure, resource, and facility enterprise data. For the public using paper maps, the internet, GPS or other instrumentation, standard data formats enable users to consistently and predictably identify specific trails and a core set of corresponding information. Today, digital road data are a necessity throughout a road data management life-cycle, from road planning through design, construction, operation, and maintenance. Automating, sharing, and leveraging road data through this widely accepted standard can provide a variety of important benefits: Efficiency – creating and gathering road data that are standardized and readily usable. Compatibility – compiling data from one project or discipline that can be compatible with other applications; Consistency – using the same standards, meshing data produced by one organization with that developed by another; Speed – hastening the availability of data through a reduction in duplicative efforts and lowered production costs (Applications can be developed more quickly and with more interoperability by using existing standards-compliant data); Conflict resolution – resolving conflicting road data more easily if compliant to the same standards; Reliability – improving the quality of shared road data by increasing the number of individuals who find and correct errors; and Reusability – allow maximum reuse across agencies and support objectives of EGovernment (E-Gov) initiatives and enterprise architecture.

These data depict Road Segment Centerlines and attributes for roads that are managed and maintained by the National Park Service. Road data are used for many purposes including planning and management, mapping and condition assessment, routing and navigation, public information, emergency response, and research. A current, accurate representation of park roads is needed for national reporting and a variety of mapping requirements at all levels of the National Park Service and the general public. A National-level dataset allows the NPS to communicate a consistent and high-quality roads database to NPS staff, partners, visitors, and entities that produce maps and location-based services of park units. The collection, storage, and management of road-related data are important components of everyday business activities in many Federal and State land-managing agencies, road organizations, and businesses. From a management perspective, road data must often mesh closely with other types of infrastructure, resource, and facility enterprise data. For the public using paper maps, the internet, GPS or other instrumentation, standard data formats enable users to consistently and predictably identify specific trails and a core set of corresponding information. Today, digital road data are a necessity throughout a road data management life-cycle, from road planning through design, construction, operation, and maintenance. Automating, sharing, and leveraging road data through this widely accepted standard can provide a variety of important benefits: Efficiency – creating and gathering road data that are standardized and readily usable. Compatibility – compiling data from one project or discipline that can be compatible with other applications; Consistency – using the same standards, meshing data produced by one organization with that developed by another; Speed – hastening the availability of data through a reduction in duplicative efforts and lowered production costs (Applications can be developed more quickly and with more interoperability by using existing standards-compliant data); Conflict resolution – resolving conflicting road data more easily if compliant to the same standards; Reliability – improving the quality of shared road data by increasing the number of individuals who find and correct errors; and Reusability – allow maximum reuse across agencies and support objectives of EGovernment (E-Gov) initiatives and enterprise architecture.

This is a comprehensive, updated feature class for all roads in Grand Teton NP and John D. Rockefeller, Jr. Memorial Parkway, with class, access, Federal Highway (FHWA), and Facility Management System (FMSS) attributes.

Snowmobile/snowmachine use units within Denali National Park and Preserve.

Two acre filtered (~9 pixel level) 25 mapping class land cover product from the DENA Land Cover Mapping Project. The development of the Denali NP&P landcover map involved collection and analysis of field verified datasets and the analysis and interpretation of remotely sensed imagery (satellite and aerial photography). A supervised digital image processing approach using the Maximum Likelihood (ML) classifier was performed on both Landsat TM and select SPOT XS scenes covering the study area. In addition to the detailed landcover map of 25 mapping classes, a more general 16 class landcover map was also created by combining ecologically and/or spectrally similar classes. Detailed information Technical Report volume 1 details the landcover classification and plant associations and volume 2 covers the remote sensing aspect of the project.

The LAVO transportation geodatabase provides spatial information on roads and trails in the park.

The LAVO transportation geodatabase provides spatial information on roads and trails in the park.

These data depict trail segment centerlines and attributes for trails that are managed and maintained by the National Park Service. Trail data are used for many purposes including planning and management, mapping and condition assessment, routing and navigation, public information, emergency response, and research.