Suggested use: Use tiled Map Service for large scale mapping when high resolution color imagery is needed.A web app to view tile and block metadata such as year, sensor, and cloud cover can be found here. CoverageState of AlaskaProduct TypeTile CacheImage BandsRGBSpatial Resolution50cmAccuracy5m CE90 or betterCloud Cover<10% overallOff Nadir Angle<30 degreesSun Elevation>30 degreesWMS version of this data: https://geoportal.alaska.gov/arcgis/services/ahri_2020_rgb_cache/MapServer/WMSServer?request=GetCapabilities&service=WMSWMTS version of this data:https://geoportal.alaska.gov/arcgis/rest/services/ahri_2020_rgb_cache/MapServer/WMTS/1.0.0/WMTSCapabilities.xml

This data set contains high-resolution QuickBird imagery and geospatial data for the entire Barrow QuickBird image area (156.15° W - 157.07° W, 71.15° N - 71.41° N) and Barrow B4 Quadrangle (156.29° W - 156.89° W, 71.25° N - 71.40° N), for use in Geographic Information Systems (GIS) and remote sensing software. The original QuickBird data sets were acquired by DigitalGlobe from 1 to 2 August 2002, and consist of orthorectified satellite imagery. Federal Geographic Data Committee (FGDC)-compliant metadata for all value-added data sets are provided in text, HTML, and XML formats. Accessory layers include: 1:250,000- and 1:63,360-scale USGS Digital Raster Graphic (DRG) mosaic images (GeoTIFF format); 1:250,000- and 1:63,360-scale USGS quadrangle index maps (ESRI Shapefile format); an index map for the 62 QuickBird tiles (ESRI Shapefile format); and a simple polygon layer of the extent of the Barrow QuickBird image area and the Barrow B4 quadrangle area (ESRI Shapefile format). Unmodified QuickBird data comprise 62 data tiles in Universal Transverse Mercator (UTM) Zone 4 in GeoTIFF format. Standard release files describing the QuickBird data are included, along with the DigitalGlobe license agreement and product handbooks. The baseline geospatial data support education, outreach, and multi-disciplinary research of environmental change in Barrow, which is an area of focused scientific interest. Data are provided on four DVDs. This product is available only to investigators funded specifically from the National Science Foundation (NSF), Office of Polar Programs (OPP), Arctic Sciences Section. An NSF OPP award number must be provided when ordering this data.

This dataset contains vegetation community maps at 20 cm resolution for three landscapes near the Toolik Lake research area in the northern foothills of the Brooks Range, Alaska, USA. The maps were built using a Random Forest modeling approach using predictor layers derived from airborne lidar data and high-resolution digital airborne imagery collected in 2013, and vegetation community training data collected from 800 reference field plots across the lidar footprints in 2014 and 2015. Vegetation community descriptions were based on the commonly used classifications of existing Toolik area vegetation maps.

This is a tiled collection of the 3D Elevation Program (3DEP) covering Alaska only, and is 5-meter resolution. The 3DEP data holdings serve as the elevation layer of The National Map, and provide foundational elevation information for earth science studies and mapping applications in the United States. Scientists and resource managers use 3DEP data for hydrologic modeling, resource monitoring, mapping and visualization, and many other applications. The elevations in this DEM represent the topographic bare-earth surface. USGS standard 5-meter DEMs are produced exclusively from interferometric synthetic aperture radar (Ifsar) source data of 5-meter or higher resolution. Five-meter DEM surfaces are seamless within collection projects, but, not necessarily seamless across projects. This DEM is delivered in the original resolution, with the original spatial reference. All elevation units have been converted to meters. These data may be used as the source of updates to the seamless 1/3 arc-second DEM layer, which serves as the elevation layer of The National Map. Other 3DEP products are nationally seamless DEMs in resolutions of 1 and 2 arc seconds. These seamless DEMs were referred to as the National Elevation Dataset (NED) from about 2000 through 2015 at which time they became the seamless DEM layers under the 3DEP program and the NED name and system were retired. Other 3DEP products in Alaska include lidar point cloud and interferometric synthetic aperture radar (Ifsar) digital surface models and intensity images. All 3DEP products are public domain.

This product set contains high-resolution Interferometric Synthetic Aperture Radar (IFSAR) imagery and geospatial data for the Barrow Peninsula (155.39 - 157.48 deg W, 70.86 - 71.47 deg N) and Barrow Triangle (156.13 - 157.08 deg W, 71.14 - 71.42 deg N), for use in Geographic Information Systems (GIS) and remote sensing software. The primary IFSAR data sets were acquired by Intermap Technologies from 27 to 29 July 2002, and consist of Orthorectified Radar Imagery (ORRI), a Digital Surface Model (DSM), and a Digital Terrain Model (DTM). Derived data layers include aspect, shaded relief, and slope-angle grids (floating-point binary and ArcInfo grid format), as well as a vector layer of contour lines (ESRI Shapefile format). Also available are accessory layers compiled from other sources: 1:250,000- and 1:63,360-scale USGS Digital Raster Graphic (DRG) mosaic images (GeoTIFF format); 1:250,000- and 1:63,360-scale USGS quadrangle index maps (ESRI Shapefile format); a quarter-quadrangle index map for the 26 IFSAR tiles (ESRI Shapefile format); and a simple polygon layer of the extent of the Barrow Peninsula (ESRI Shapefile format). Unmodified IFSAR data comprise 26 data tiles across UTM zones 4 and 5. The DSM and DTM tiles (5 m resolution) are provided in floating-point binary format with header and projection files. The ORRI tiles (1.25 m resolution) are available in GeoTIFF format. FGDC-compliant metadata for all data sets are provided in text, HTML, and XML formats, along with the Intermap License Agreement and product handbook. The baseline geospatial data support education, outreach, and multi-disciplinary research of environmental change in Barrow, which is an area of focused scientific interest. Data are provided on five DVDs, available through licensing only to National Science Foundation (NSF)-funded investigators. An NSF award number must be provided when ordering data.

Advanced Very High Resolution Radiometer (AVHRR) data were obtained from the USGS Global AVHRR 10-day composite data. (http://edcdaac.usgs.gov/1KM/1kmhomepage.asp) (Markon et al. 1995). Glaciers and oceans were masked out using information from the Digital Chart of the World (ESRI 1993). The image is composed of 1 x 1-km pixels. The color of each pixel was determined by its reflectance at the time of maximum greenness, selected from 10-day composite images from 11 July to 30 August 1993 and 1995. These intervals cover the vegetation green-up-to-senescence period during two relatively warm years when summer-snow cover was at a minimum in the Arctic. Maximum greenness was determined from the normalized difference vegetation index (NDVI). Vegetation greenness is calculated as: NDVI = (NIR - R) / (NIR + R), where NIR is the spectral reflectance in the AVHRR near-infrared channel (0.725-1.1 µ, channel 2) where light-reflectance from the plant canopy is dominant, and R is the reflectance in the red channel (0.58 to 0.68 µ, channel 1), the portion of the spectrum where chlorophyll absorbs maximally. The resulting image shows the Arctic with minimum snow and cloud cover. The channel 1 and channel 2 values were then stacked to create as a false-color CIR image (RGB = ch. 2, ch. 1, ch. 1). Back to Circumpolar Arctic Vegetation Map 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 Map, Elevation, Floristic Provinces, Lake Cover, Landscape Physiography, Landscape Age, Substrate Chemistry, Vegetation References Markon, C. J., M. D. Fleming, and E. F. Binnian. 1995. Characteristics of vegetation phenology over the Alaskan landscape using AVHRR time-series data. Polar Record 31:179-190.

This webmap includes all data layers relevant to 2020 forest health surveys in Alaska, including damage polygons mapped with high-resolution Worldview satellite imagery and road and trail routes along which major damage was mapped to replace the cancelled aerial detection survey.We conducted ground surveys along roads and trails, mapping major damage at regular intervals. These surveys covered approximately 2.4 million acres. Our goal was to capture notable symptom observations, approximating what would be mapped during our annual aerial survey, thereby providing damage locations to hone our remote-sensing tools and techniques. As in recent years, we also recorded damage that is indecipherable from the air using the Survey123 app (displayed in our Ground Survey Dashboard).Based on locations with known forest damage, we evaluated damage signatures in high-resolution satellite imagery. This approach enabled us to map similar damage across broader and less accessible swaths of the landscape. High-resolution (< 1m) Worldview 2 and Worldview 3 satellite imagery captured June to September 2020 was requested through both Digital Globe and the USGS using their CRSSP Imagery Derived Requirements (CIDR) imagery request tool. Available imagery was mosaicked (overlaid and positioned) in ArcPro software to create basemaps, which were then imported into our standard aerial survey mapping software on mobile tablets.Finally, surveyors systematically scanned 5.8 million forested acres of imagery for forest damage. Using the same methods as aerial survey, they circled damage areas, attributing them with the damage agent, plant host, and damage severity. Imagery quality varied. Overall, damage was more difficult to see in imagery compared to what can be seen from the plane at 1000-1500ft above the ground. Some agents that cause relatively homogenous color change to the tree canopy (e.g., spruce beetle and hemlock sawfly) were easier to pick up in the imagery compared to more subtle or scattered damage that can be mapped from a survey plane. Using both road and remote-sensing surveys, we mapped about 345,000 acres of damage across the 8.2 million acres surveyed, presented in the Alaska Forest Damage Map.

USGS Imagery Only is a tile cache base map of orthoimagery in The National Map visible to the 1:18,000 scale. Orthoimagery data are typically high resolution images that combine the visual attributes of an aerial photograph with the spatial accuracy and reliability of a planimetric map. USGS digital orthoimage resolution may vary from 6 inches to 1 meter. In the former resolution, every pixel in an orthoimage covers a six inch square of the earth's surface, while in the latter resolution, one meter square is represented by each pixel. Blue Marble: Next Generation source is displayed at small to medium scales. However, the majority of the imagery service source is from the National Agriculture Imagery Program (NAIP) for the conterminous United States. The data is 1-meter pixel resolution with "leaf-on". Collection of NAIP imagery is administered by the U.S. Department of Agriculture's Farm Service Agency (FSA). In areas where NAIP data is not available, other imagery may be acquired through partnerships by the USGS. The National Map program is working on acquisition of high resolution orthoimagery (HRO) for Alaska and Hawaii. Most of the new Alaska imagery data will not be available in this service due to license restrictions. The National Map viewer allows free downloads of public domain, 1-meter resolution orthoimagery in JPEG 2000 (jp2) format for the conterminous United States, with many urban areas and other locations at 1-foot (or better) resolution also in JPEG 2000 (jp2) format. For scales below 1:18,000, use the dynamic USGS Imagery Only Large service, https://services.nationalmap.gov/arcgis/rest/services/USGSImageOnlyLarge/MapServer.

This dataset contains estimates for aboveground shrub biomass and uncertainty at high spatial resolution (0.80-m) across three research areas near Toolik Lake, Alaska. The estimates for August of 2013 were generated and mapped using Random Forest modeling with input variables of optimized LiDAR-derived canopy volume and height, mean NDVI from 4-band RGB color and near-IR orthophotographs, and harvested biomass data. Uncertainty in the final shrub biomass maps was quantified by producing separate maps showing the coefficient of variation (CV) of the Random Forest map estimates. Shrub biomass was harvested at Toolik Lake in 2014 and used to optimize inputs and validate the final model and these biomass data are also provided.

The Vegetation Technical Working Group (VTWG) of the Alaska Geospatial Council developed Standards for Production of Alaska Vegetation Map Version 1.1 (August 2022) to set technical goals for the production of a vegetation map that consistently covers all of Alaska with high spatial and ecological resolution. We compared vegetation maps and mapping frameworks with statewide coverage to the standards to determine the most appropriate map to select as the implementation of a statewide map and found that the AKVEG Map is the only map or mapping framework that fulfills all VTWG goals.

This dataset is a comprehensive inventory of Alaskan buildings, storage tanks, and roads that were: (1) detected from 0.5 meter resolution satellite imagery of communities (acquired between 2018-2023) and (2) supplemented by OpenStreetMap data. We created HABITAT (High-resolution Arctic Built Infrastructure and Terrain Analysis Tool), a deep learning-based, high-performance computing-enabled mapping pipeline to automatically detect buildings and roads from high-resolution Maxar satellite imagery across the Arctic region. Shapefiles beginning with "HABITAT_AK" contain only the post-processed deep learning predictions. Shapefiles beginning with "HABITAT_OSM" contain the post-processed deep learning predictions supplemented by OpenStreetMap data. The HABITAT pipeline is based on a ResNet50-UNet++ semantic segmentation architecture trained on a training dataset comprised of building and road footprint polygons manually digitized from Maxar satellite imagery across the circumpolar Arctic (including Alaska, Russia, and Canada). The code is made available at https://github.com/PermafrostDiscoveryGateway/HABITAT. From imagery of 285 Alaskan communities acquired between 2018-2023, we detected approximately 250,000 buildings and storage tanks (comprising a 41.76 million square meter footprint) and 15 million meters of road. Building (including storage tanks) footprint polygons and road centerlines were strictly mapped within the boundaries of Alaskan communities (both incorporated places and census designated places). After the deep learning model detected building and road footprints, post-processing was performed to smooth out building footprints, extract centerlines from road footprints, and remove falsely-detected infrastructure. In particular, a buffer is created around developed land cover identified by the 2016 Alaska National Land Cover Database map, and model predictions that fall outside of the buffer are assumed to be confused with non-infrastructure land cover. Finally, we selected buildings and roads from the OpenStreetMap Alaska dataset (downloaded in June 2024 from https://download.geofabrik.de/) that do not intersect with any deep learning predictions to generate a merged OSM and HABITAT infrastructure dataset. This merged product comprises a total building footprint of 53 million square meters and a road network of 63,744 km across the state of Alaska.

Remote sensing maps of plant functional type (PFT) fractional cover (FCover), dominant PFT, and FCover uncertainty derived from NASA's Airborne Visible / Infrared Imaging Spectrometer - Next Generation (AVIRIS-NG). The AVIRIS-NG imaging spectroscopy data (380-2510 nm) was collected as a part of the collaboration between NASA's Arctic-Boreal Vulnerability Experiment (ABoVE; Miller et al., 2019) and DOE's Next Generation Ecosystem Experiment in the Arctic (NGEE-Arctic). This package includes maps of the NGEE-Arctic Council watershed on the Seward Peninsula, Alaska, created using AVIRIS-NG imagery collected on July 9th, 2019. The map data and metadata are provided as GeoTIFF (.tif), ENVI image (.dat), and text (*.txt, *hdr) formats. Additional map quicklooks are provided as *.pdf files and GIS *.kml files. These datasets are provided in support of Yang et al., (2023), "Integrating Very-High-Resolution UAS Data and Airborne Imaging Spectroscopy to Map the Fractional Composition of Arctic Plant Functional Types in Western Alaska". The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

This is a tiled collection of the 3D Elevation Program (3DEP) and is 2 arc-second (approximately 60 m) resolution covering Alaska. The elevations in this Digital Elevation Model (DEM) represent the topographic bare-earth surface. The 3DEP data holdings serve as the elevation layer of The National Map, and provide foundational elevation information for earth science studies and mapping applications in the United States. Scientists and resource managers use 3DEP data for hydrologic modeling, resource monitoring, mapping and visualization, and many other applications. The seamless 2 arc-second DEM layers are derived from diverse source data that are processed to a common coordinate system and unit of vertical measure. These data are distributed in geographic coordinates in units of decimal degrees, and in conformance with the North American Datum of 1983 (NAD 83). All elevation values are in meters and, over the continental United States, are referenced to the North American Vertical Datum of 1988 (NAVD88). The seamless 2 arc-second DEM layer provides coverage of the Alaska only. The seamless 2 arc-second DEM is available as pre-staged current and historical products tiled in GeoTIFF format. The seamless 2 arc-second DEM layer is updated continually as new data become available in the current folder. Previously created 1 degree blocks are retained in the historical folder with an appended date suffix (YYYYMMDD) when they were produced. Other 3DEP products are nationally seamless DEMs in resolutions of ⅓ and 1 -arc-second. These seamless DEMs were referred to as the National Elevation Dataset (NED) from about 2000 through 2015 at which time they became the seamless DEM layers under the 3DEP program and the NED name and system were retired. Other 3DEP products include one-meter DEMs produced exclusively from high resolution light detection and ranging (lidar) source data and five-meter DEMs in Alaska as well as various source datasets including the lidar point cloud and interferometric synthetic aperture radar (Ifsar) digital surface models and intensity images. All 3DEP products are public domain.

This dataset contains vegetation community maps at 20 cm resolution for three landscapes near the Toolik Lake research area in the northern foothills of the Brooks Range, Alaska, USA. The maps were built using a Random Forest modeling approach using predictor layers derived from airborne lidar data and high-resolution digital airborne imagery collected in 2013, and vegetation community training data collected from 800 reference field plots across the lidar footprints in 2014 and 2015. Vegetation community descriptions were based on the commonly used classifications of existing Toolik area vegetation maps.

These data are orthorectified radar intensity images (ORI) derived from interferometric synthetic aperture radar (ifsar) data. An ORI is a high-resolution image derived from ifsar which has geometric distortions removed. Unlike optical imagery, ifsar can be collected in cloudy conditions. The USGS performs minimal quality assurance and no reprocessing of the ORI data. USGS distributes the ORI data as received from the contractors, partners or contributing entities.

This dataset represent a map of the high center (HC) and low center (LC) polygon boundaries delineated from high resolution LiDAR data for the arctic coastal plain at Barrow, Alaska. The polygon troughs are considered as the surface expression of the ice-wedges. The troughs are in lower elevations than the interior polygon. The trough widths were initially identified from LiDAR data, and the boundary between two polygons assumed to be located along the lowest elevations on trough widths between them.

Two active landslides at and near the retreating front of Barry Glacier at the head of Barry Arm Fjord in southern Alaska could generate tsunamis if they failed rapidly and entered the water of the fjord. Landslide A, at the front of the glacier, is the largest, with a total volume estimated at 455 M m3. Historical photographs from Barry Arm indicate that Landslide A initiated in the mid twentieth century, but there was a large pulse of movement between 2010 and 2017 when Barry Glacier thinned and retreated from about 1/2 of the toe of Landslide A. Interferometric synthetic aperture radar (InSAR) investigations of the area between May and November, 2020, revealed a second, smaller landslide (referred to as Landslide B) on the south-facing slope about 2 km up the glacier from Landslide A. Landslide-generated tsunami modeling in 2020 used a worst-case scenario where the entire mass of Landslide A (about 455 M m3) would rapidly enter the water. The use of multiple landslide volume scenarios in future tsunami modeling efforts would be beneficial in evaluating tsunami risk to communities in the Prince William Sound region. Herein, we present a map of landslide structures and kinematic elements within, and adjacent to, Landslides A and B. This map could form at least a partial basis for discriminating multiple volume scenarios (for example, a separate scenario for each kinematic element). We mapped landslide structures and kinematic elements at scale of 1:1000 using high-resolution lidar data acquired by the Alaska Division of Geological and Geophysical Surveys (DGGS) on June 26, 2020 and high resolution bathymetric data acquired by the National Oceanic and Atmospheric Administration (NOAA) in August, 2020. The predominate structures in both landslides are uphill- and downhill-facing normal fault scarps. Uphill-facing scarps dominate in areas where downslope extension from sliding has been relatively low. Downhill-facing scarps dominate in areas where downlslope extension from sliding has been relatively high. Strike-slip and oblique-slip faults form the boundaries of major kinematic elements. Four major kinematic elements, herein named the Kite, the Prow, the Core, and the Tail, are within, or adjacent to Landslide A. One major kinematic element, herein named the Wedge, forms Landslide B. Kinematic element boundaries are a result of cumulative, differential patterns and amounts of movement that began at inception of the landslides. Elements and/or their boundaries may change location as the landslides continue to evolve. Kinematic elements mapped in 2020 may or may not reflect patterns of historical short-term, episodic movement, or patterns of movement in the future. We were not able to field check our mapping in 2020 because of travel restrictions due to the COVID-19 pandemic. We hope to field check the mapping in the summer of 2021. In this data release, we include GIS files for the structural and kinematic map; metadata files for mapped structural features; and portable document files (PDFs) of a location map, and the structural and kinematic map at a scale of 1:5000. Lidar and bathymetric data used to map landslide structures will be released by DGGS and NOAA in 2021.

These data were automated to provide an accurate high-resolution historical shoreline of Kink Arm - Anchorage, Alaska suitable as a geographic information system (GIS) data layer. These data are derived from shoreline maps that were produced by the NOAA National Ocean Service including its predecessor agencies which were based on an office interpretation of imagery and/or field survey. The...

This high resolution LiDAR dataset of the village of Nuiqsut is part of a series of 2013 LiDAR and imagery collections by EPSCoR Northern Test Case. This LiDAR was collected at 8 points per meter (ppm) over the village of Nuiqsut as part of a broader area coverage to go with the high density collection over the Northern Test Case focus area of Crea Creek (link below) The data products contain a 1 meter Digital Elevation Model (DEM) and raw LAS files. For data download access contact support@gina.alaska.edu. In the future this data will also be available for download at: http://maps.dggs.alaska.gov/elevationdata

This dataset contains vegetation community maps at 20 cm resolution for three landscapes near the Toolik Lake research area in the northern foothills of the Brooks Range, Alaska, USA. The maps were built using a Random Forest modeling approach using predictor layers derived from airborne lidar data and high-resolution digital airborne imagery collected in 2013, and vegetation community training data collected from 800 reference field plots across the lidar footprints in 2014 and 2015. Vegetation community descriptions were based on the commonly used classifications of existing Toolik area vegetation maps.