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

USGS Imagery Only is a tile cache base map service of orthoimagery in The National Map visible to the 1:9,028 zoom scale. Orthoimagery data is typically high resolution aerial 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 and Landsat imagery data sources are 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 collected with "leaf-on" conditions. 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. For Alaska, 10-meter resolution SPOT imagery is provided for viewing. The National Map download client allows free downloads of public domain, 1-meter resolution orthoimagery in JPEG 2000 (jp2) format for the conterminous United States. However, the 10-meter Alaska orthoimagery data will not be available for direct download from the National Map due to license restrictions. For additional information on orthoimagery, go to https://nationalmap.gov/ortho.html.

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.

Suggested use: Use this basemap for large scale mapping when high resolution color infrared 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 Cache Level 19Image BandsCIRSpatial Resolution50cm or betterAccuracy5m 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_cir_cache/MapServer/WMSServer?request=GetCapabilities&service=WMSWMTS version of this data:https://geoportal.alaska.gov/arcgis/rest/services/ahri_2020_cir_cache/MapServer/WMTS/1.0.0/WMTSCapabilities.xml

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 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 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 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.

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.

The National Geospatial-Intelligence Agency (NGA) and the National Science Foundation (NSF) partnered with the University of Minnesota and other members of the academic research community, private sector, and international partners to create this first-ever publicly available, high-resolution, satellite-based elevation data map of the Arctic. The 3-D digital elevation models, or DEMs, are the product of the ArcticDEM project, which was created after a January 2015 executive order calling for enhanced coordination of national efforts in the Arctic. This site hosts web maps, map viewers, other DEM exploratory tools, nautical charts, sailing directions and infographics, and a downloadable Pan-Arctic map with mission-specific data layers. ArcticDEM encompasses all land area north of 60° north latitude as well as all territory of Greenland, the State of Alaska in its entirety, and the Kamchatka Peninsula of the Russian Federation. This site supports the past U.S. Chair of the Arctic Council and the U.S. Presidential Executive Order on Enhancing Coordination of National Efforts in the Arctic

NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the National Tsunami Hazard Mitigation Program's (NTHMP) efforts to improve community preparedness and hazard mitigation. These integrated bathymetric-topographic DEMs are used to support tsunami and coastal inundation mapping. Bathymetric, topographic, and shoreline data used in DEM compilation are obtained from various sources, including NGDC, the U.S. National Ocean Service (NOS), the U.S. Geological Survey (USGS), the U.S. Army Corps of Engineers (USACE), the Federal Emergency Management Agency (FEMA), and other federal, state, and local government agencies, academic institutions, and private companies. DEMs are referenced to various vertical and horizontal datums depending on the specific modeling requirements of each State. For specific datum information on each DEM, refer to the appropriate DEM documentation. Cell sizes also vary depending on the specification required by modelers in each State, but typically range from 8/15 arc-second (~16 meters) to 8 arc-seconds (~240 meters).This is an ArcGIS image service showing color shaded relief visualizations of high-resolution digital elevation models (DEMs) of U.S. coastal regions. NOAA's National Geophysical Data Center (NGDC) builds and distributes high-resolution coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. They can be used for modeling of coastal processes (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness. DEMs included in this visualization: High-resolution DEMs of select U.S. coastal communities and surrounding areas. Most are at a resolution of 1/3 to 1 arc-second (approx 10-30 m); U.S. Coastal Relief Model: A 3 arc-second (approx 90 m) comprehensive view of the conterminous U.S. coastal zone, Puerto Rico, and Hawaii; Southern Alaska Coastal Relief Model: A 24 arc-second (approx. 500 m) model of Southern Alaska, spanning the Bering Sea, Aleutian Islands, and Gulf of Alaska. This map service can be used as a basemap. It has a transparent background, so it can also be shown as a layer on top of a different basemap. Please see NGDC's corresponding DEM Footprints map service for polygon footprints and more information about the individual DEMs used to create this composite view.A map service showing the location and coverage of land and seafloor digital elevation models (DEMs) available from NOAA's National Geophysical Data Center. NOAA's National Geophysical Data Center (NGDC) builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. They can be used for modeling of coastal processes (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness. Layers available in the map service: Layers 1-4: DEMs by Category (includes various DEMs, both hosted at NGDC, and elsewhere on the web); Layers 6-11: NGDC DEM Projects (DEMs hosted at NGDC, color-coded by project); Layer 12: All NGDC Bathymetry DEMs (All bathymetry or bathy-topo DEMs hosted at NGDC).

This is a tiled collection of the 3D Elevation Program (3DEP) and is 1/3 arc-second (approximately 10 m) 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. The seamless 1/3 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 1/3 arc-second DEM layer provides coverage of the conterminous United States, Hawaii, Puerto Rico, other territorial islands, and in limited areas of Alaska. The seamless 1/3arc-second DEM is available as pre-staged current and historical products tiled in GeoTIFF format. The seamless 1/3 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 (YYYMMDD) when they were produced. 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 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.

The November 30, 2018, magnitude (Mw) 7.1 Anchorage, Alaska earthquake triggered substantial ground failure throughout Anchorage and surrounding areas (Grant and others, 2020; Jibson and others, 2020). The earthquake was an intraslab event with a focal depth of about 47 km and an epicenter about 16 km north of the city of Anchorage. Peak ground accelerations reached ∼30% g. Despite the relatively low severity of most of the ground failure occurrences, geotechnical damage to buildings and structures was widespread (Franke and others, 2019). Here, we present an inventory of the earthquake-triggered ground failure based on information compiled from numerous data sources. The inventory is comprised of 886 points that each correspond to the _location of earthquake triggered ground failure associated with the 2018 event (Figure 1). For each instance of ground failure, the direct observation is reported and, where possible, is categorized based on the process interpreted to have caused it. For example, an observation of a rock fall would be categorized as a landslide. Similarly, a sand boil would be categorized as evidence of liquefaction. Where possible, the features were more precisely mapped with an additional polygon (n=179) and or line feature (n=32). To determine the existence and _location of ground failure features, we relied on a variety of mapping methods and data sources. As such, the certainty in the mapping of each feature within the inventory varies (Figure 2). Details on how uncertainty is reported as well as the methods and data sources used are discussed in the following sections. Data and Methods The inventory was compiled using a variety of different sources and methods with varying levels of success (Martinez and others, 2021). To convey this, the overall mapping certainty for each feature within the inventory is determined by assigning a semi-quantitative grade for categories related to the certainty of the existence of the feature, the positional accuracy of the mapped feature, and the mapped delineation quality. Those categories are denoted as presence, _location, and delineation certainty in the inventory attribute table. Confidence grade definitions, and all other inventory attributes, are described in Table 1. As previously mentioned, we relied on a variety of methods and data sources to develop the ground failure inventory. We primarily relied on field observation data and information shared from federal, state, and local agencies. These data sources were particularly helpful where remotely sensed data were not available or insufficient for mapping ground failure. Here, we summarize how remotely sensed data were used and in which ways they were advantageous or insufficient. High resolution digital elevation models (DEMs) are typically used to develop high-quality ground failure inventories. We began our ground failure mapping efforts by differencing high resolution pre- and post-earthquake lidar derived DEMs from the Alaska Department of Natural Resources (AK DNR) Division of Geological and Geophysical Surveys (DGGS) elevation portal (DGGS Elevation Portal (alaska.gov)). The pre- and post-earthquake DEMs used to identify and map the extent of ground failure in this study had an areal overlap of approximately 321 km2. These data cover only a small portion of the area that experienced moderate to severe shaking during the earthquake (60,690 km2) as estimated from the USGS ShakeMap. In regions lacking sufficient DEM coverage we used Normalized Difference Vegetation Index (NDVI) differencing to identify and map ground failure. NDVI maps are derived from multispectral imagery and display the relative health or existence of vegetation in a landscape. For this study, NDVI maps were derived using imagery from the European Space Agency’s Sentinel-2 (S2) Multispectral Instrument (MSI) (Drusch and others, 2012). Ground failure that is severe enough to disturb vegetation can be mapped by differencing pre- and post- earthquake NDVI maps. However, efforts to create NDVI maps of the landscape following the earthquake were hindered due to snowfall that began to accumulate shortly after the earthquake (2 December 2018). To overcome this limitation, we used Google Earth Engine (Gorelick and others, 2017) to create composites of multispectral images of the summers (May 1 to July 30) before and after the earthquake instead. The image composites were then used to create NDVI maps that were differenced to determine where there were any significant changes in vegetation that could potentially correspond to ground failure. While the resolution of the data used for the NDVI differencing (10-m) is lower than that used for DEM differencing (1-m) it is advantageous as it is available globally, and thus, for the entire earthquake affected region of Southcentral, Alaska. Despite the advantage of globally available NDVI data, the method is still limited in its ability to detect smaller and more subtle vegetation changes. Our comparisons may also include some landslides that were not triggered by the earthquake but happened in the time spanned by the images. When possible, satellite and aerial imagery alone were also used to map ground failure features. However, in most instances the imagery alone was inadequate for mapping because many features were not visible in available satellite imagery. In addition, the ground surface was obscured in satellite imagery as a result of snow fall that occurred shortly after the earthquake. Some features, such as large road cracks, were not visible following snowmelt as they were quickly repaired by The Alaska Department of Transportation and Public Facilities. Other ephemeral features, such as sand boils or cracks on tidal flats, were no longer visible in satellite imagery after snowmelt and several tidal cycles. Remotely sensed data alone were found to be insufficient for mapping ground failure associated with this event (see Martinez and others, 2021). In addition to the limitations of remotely sensed data, the aforementioned snowfall that occurred immediately after the earthquake obscured large swaths of land and subsequently hindered efforts to gather ground failure observations while in the field. Thus, in addition to the remotely sensed data, the inventory was supplemented with field observations gathered by U.S. Geological Survey scientists shortly after the event (Grant and others, 2020), information on earthquake damage supplied from federal (FEMA Region X), state (The Alaska Department of Transportation and Public Facilities) and local agencies (Municipality of Anchorage, Kenai Peninsula Borough, Matanuska-Susitna Borough Department of Emergency Services, 673 Civil Engineers Squadron at the Joint Base Elmendorf-Richardson, Anchorage Fire Station 12) as well as compiled social media information and data from literature on the 2018 earthquake event. Using the data mentioned above, we inferred which ground failure process to assign to each ground failure _location based on contextual information such as the environment and presence of evidence that suggests ground failure may have occurred. We assigned the “landslide” process to locations where there are indications of the downhill movement of material. A modified classification scheme based on Keefer (1984) was used to classify the observed landslide features within our inventory (see Table 1 for landslide classification scheme). Evidence that liquefaction processes may have occurred include the presence of ground cracks, sand boils, lateral spreads, the settlement of structures, and rapid soil flows. In cases where direct evidence of liquefaction is lacking (i.e., sand boils), the classification is based on proximity to identified sand boils. Liquefaction was interpreted to be the process for observed lateral spreading features parallel to water bodies. Low-lying features on flat slopes (e.g., settlement alone) for which there is no direct evidence to suggest that liquefaction occurred are given the label “Liquefaction (Ambiguous)” to reflect the uncertain nature in their process designation. Despite the use of supplemental data, the inventory is still considered incomplete, with varying levels of completeness throughout the region. Adverse environmental conditions including snow fall, limited daylight hours, a large earthquake-affected area, and accessibility constraints limited the extent to which both field and remotely sensed observations could be reliably used to compile a ground failure inventory. To communicate this variability in inventory completeness and quality, Figure 2 displays the region, highlighted in white, in which direct observations of ground failure were made in addition to where high-resolution pre- and post-earthquake lidar data are available. This higher-confidence mapping region displays where the inventory is considered complete and high quality due to the nature of the data (i.e., direct observations, high-quality lidar) used for mapping in this region. To minimize human error, two co-authors carefully reviewed the inventory for inconsistencies and errors. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. References Cited: Drusch, M., Del Bello, U., Carlier, S., Colin, O., Fernandez, V., Gascon, F., Hoersch, B., Isola, C., Laberinti, P., Martimort, P., Meygret, A., Spoto, F., Sy, O., Marchese, F., and Bargellini, P., 2012, Sentinel-2: ESA’s Optical High-Resolution Mission for GMES Operational Services: Remote Sensing of Environment, v. 120, p. 25–36. https://doi.org/10.1016/j.rse.2011.11.026 Franke, K.W., Koehler, R., Beyzaei, C.Z., Cabas, A., Christie, S., Dickenson, S., Pierce, I., Stuedlein, A., and Yang, Z., 2019, Geotechnical Engineering Reconnaissance of the 30 November 2018 Mw 7.1 Anchorage, Alaska Earthquake, Version 2.0: Geotechnical Extreme Events Reconnaissance Association. Gorelick,

USGS Imagery Topo is a tile cache base map of orthoimagery in The National Map and US Topo vector data visible to the 1:9,028 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. 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.

These data provide an accurate high-resolution shoreline compiled from imagery of Nome, AK . This vector shoreline data is based on an office interpretation of imagery that may be suitable as a geographic information system (GIS) data layer. This metadata describes information for both the line and point shapefiles. The NGS attribution scheme 'Coastal Cartographic Object Attribute Source Tabl...

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.

No description is available. Visit https://dataone.org/datasets/ess-dive-c79d1ae7f247469-20241011T153612029 for complete metadata about this dataset.

The dataset represents microtopographic characterization of the ice-wedge polygon landscape in Barrow, Alaska. Three microtopographic features are delineated using 0.25 m high resolution digital elevation dataset derived from LiDAR. The troughs, rims, and centers are the three categories in this classification scheme. The polygon troughs are the surface expression of the ice-wedges that are in lower elevations than the interior polygon. The elevated shoulders of the polygon interior immediately adjacent to the polygon troughs are the polygon rims for the low center polygons. In case of high center polygons, these features are the topographic highs. In this classification scheme, both topographic highs and rims are considered as polygon rims. The next version of the dataset will include more refined classification scheme including separate classes for rims ad topographic highs. The interior part of the polygon just adjacent to the polygon rims are the polygon centers.

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.

Using airborne hyperspectral remote sensing data from NASA Airborne Visible-Infrared Imaging Spectrometer- Next Generation (AVIRIS-NG) platforms in a region near NGEE-Arctic intensive watersheds at Seward peninsula of Alaska, high resolution (5m) maps of plant community distribution were developed and included in this data collected. AVIRIS-NG data collected over 2017-2019 period were used to develop deep neural networks, trained using vegetation plot observations collected at NGEE-Arctic watersheds at Kougarok, Council and Teller. A hierarchical vegetation classification scheme consisting of six classes at Level I, and 16 classes at Level II contained in two .txt files were used to developed the plant community maps for the region. Two geospatial raster data files (.tif) at both thematic levels are shared in this data collection. Data files in this collection use Alaska Albers Equal Area projection. Readme files available in three formats (*.html, *.md, *.pdf) and one *.png visualization map.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).