U.S. Geological Survey Glacier Project 20190905 tabular digital data, vector digital data, raster digital data Geodetic Data for USGS Glaciers: Orthophotos, Digital Elevation Models, Glacier Boundaries and Surveyed Positions ver 4.0, May 2025 Anchorage, Alaska U.S. Geological Survey, Alaska Science Center Suggested Citation: U.S. Geological Survey Glacier Project, 2019, Geodetic data for USGS glaciers: orthophotos, digital elevation models, glacier boundaries and surveyed positions (ver 4.0, May 2025): U.S. Geological Survey data release, https://doi.org/10.5066/P9R8BP3K https://doi.org/10.5066/P9R8BP3K U.S. Geological Survey Glacier Project 2016 website online U.S. Geological Survey, Alaska Science Center This is a link to the U.S. Geological Survey (USGS) glacier research project website. Users will find a description of glacier-related research and links to associated data products. https://doi.org/10.5066/P9AGXQSR This data release provides geodetic measurements collected since the mid-1940s to characterize the surface elevation, area, and motion of glaciers studied by the U.S, Geological Survey. The primary glaciers of focus are the Benchmark Glaciers of North America which include Gulkana, Wolverine, and Lemon Creek Glaciers in Alaska, Sperry Glacier in Montana, and South Cascade Glacier in Washington state (USA). The data include: historic and contemporary glacier boundary outlines, point data from GNSS surveys, Digital Elevation Models (DEM), and orthorectified aerial photos and satellite imagery (Orthos). This data release is updated periodically. The "versionHistory.txt" file included with this data release describes updates made in each version. These data were generated for the purpose of measuring glacier area, surface elevation, and velocity. 1948 2021 observed In work As needed -148.95 -113.75 63.35 48.62 USGS Metadata Identifier USGS:ASC226 ISO 19115 Topic Category GeoScientificInformation Boundaries ClimatologyMeteorologyAtmosphere Elevation Environment NASA GCMD Earth Science Keyword Thesaurus Cryosphere Glaciers/Ice Sheets Glaciers Ablation Zones/Accumulation Zones Glacier Elevation/Ice Sheet Elevation Glacier Mass Balance/Ice Sheet Mass Balance USGS CSA Biocomplexity Thesaurus Glaciology USGS Thesaurus Snow and ice cover Glaciation Glaciology USGS Geographic Names Information System (GNIS) Gulkana Glacier Wolverine Glacier Sperry Glacier Lemon Creek Glacier South Cascade Glacier Montana Alaska Washington No access constraints. No use constraints. These data are marked with a Creative Common CC0 1.0 Universal License and are in the public domain. It is requested that this USGS data release be cited for any subsequent publications that reference or utilize these data. Users are advised to read the dataset's metadata thoroughly to understand appropriate use and data limitations. USGS Benchmark Glacier Project U.S. Geological Survey, Alaska Science Center Mailing and Physical

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Anchorage Alaska 99508 USA 907-786-7000 gs-ak_asc_datamanagers@usgs.gov USGS Glacier Project O'Neel, S. McNeil, C.J. Sass, L.C. Florentine, C.E. Baker, E.H. Peitzsch, E.H. McGrath, D. Fountain, A.G. Fagre, D. 2019 journal article Journal of Glaciology 65(253):850-866 online Cambridge University Press O'Neel, S., McNeil, C.J., Sass, L.C., Florentine, C.E., Baker, E.H., Peitzsch, E.H., McGrath, D., Fountain, A.G., Fagre, D., 2019. Reanalysis of the US Geological Survey Benchmark Glaciers: long-term insight into climate forcing of glacier mass balance. Journal of Glaciology 65(253):850-866. https://doi.org/10.1017/jog.2019.66 https://doi.org/10.1017/jog.2019.66 Enderlin, E.M. Elkin, C.M. Gendreau, M. Marshall, H.P. O'Neel, S. McNeil, C.J. Florentine, C. Louis Sass, L. 2022 journal article Remote Sensing of Environment 283:113307 online Elsevier Enderlin, E.M., Elkin, C.M., Gendreau, M., Marshall, H.P., O'Neel, S., McNeil, C.J., Florentine, C., Louis Sass, L., 2022. Uncertainty of ICESat-2 ATL06- and ATL08-derived snow depths for glacierized and vegetated mountain regions. Remote Sensing of Environment 283:113307. https://doi.org/10.1016/j.rse.2022.113307 https://doi.org/10.1016/j.rse.2022.113307 Knuth, F. Shean, D. Bhushan, S. Schwat, E. Alexandrov, O. McNeil, C.J. Dehecq, A. Florentine, C. O'Neel, S. 2022 journal article Remote Sensing of Environment 285:113379 online Elsevier Knuth, F., Shean, D., Bhushan, S., Schwat, E., Alexandrov, O., McNeil, C.J., Dehecq, A., Florentine, C., O'Neel, S., 2023. Historical Structure from Motion (HSfM): Automated processing of historical aerial photographs for long-term topographic change analysis. Remote Sensing of Environment 285:113379. https://doi.org/10.1016/j.rse.2022.113379 https://doi.org/10.1016/j.rse.2022.113379 Florentine, C. 2019 journal article U.S. Geological Survey Fact Sheet 2019–3068 online U.S. Geological Survey Florentine, C., 2019, Glacier retreat in Glacier National Park, Montana (ver. 1.1, December 2019): U.S. Geological Survey Fact Sheet 2019–3068. https://doi.org/10.3133/fs20193068 https://doi.org/10.3133/fs20193068 The geodetic data are comprised of location and elevation information; the accuracy is described in the positional accuracy statement (below). Missing data are denoted with the code "na" in tabular data, or a background nodata value assigned within the tagged information of each GeoTiff. Data gaps are described more fully in the entity-attribute section of this metadata record, in the entity definitions. Complete data are provided here for the calculation of glacier area, surface elevation, and velocity for published analyses of the U.S. Geological Survey’s Glacier Project. Orthos - Orthos have sub-meter scale pixel size. Absolute uncertainty of geolocation of entire products is typically <30m in the x and/or y direction. DEMs - absolute accuracy of DEMs geolocation of entire products is typically <30m in the x and/or y direction. Relative accuracy is investigated in detail, by comparing and minimizing changes in off-glacier, stable rock areas through the timeseries of DEMs. Thus, relative uncertainty is well-quantified (described in O'Neel et al. 2019), but absolute uncertainty is not explicitly well constrained. Glacier Boundaries – Overall uncertainties in glacier boundaries and the areas they cover are best estimated using the inverse power law uncertainty function presented by Pfeffer et al. 2014. Survey Points - Uncertainty within the local coordinate system is less than 20 cm and the local coordinate system is known within 10 cm. Nolan, M. Post, A.S. Hauer, W. Zinck, A. O'Neel, S. 2017 remote-sensing imagery online Arctic Data Center Nolan, M., Post, A.S., Hauer, W., Zinck, A., O'Neel, S., 2017. Photogrammetric scans of aerial photographs of North American glaciers. Arctic Data Center https://doi.org/10.18739/A2VH5CJ8K https://doi.org/10.18739/A2VH5CJ8K remote-sensing imagery Unknown observed Nolan et al 2017 Scanned aerial imagery, acquired by Austin Post and the USGS between 1958 and 1999 published in the Arctic Data Center Post, A. Unknown remote-sensing imagery remote-sensing imagery Unknown observed Post, unpublished Scanned aerial imagery, acquired by Austin Post and the USGS. The imagery is unpublished in USGS archives. These Orthos represents the first publication the imagery. Larsen, C. Unknown remote-sensing imagery remote-sensing imagery Unknown observed Larsen, unpublished Aerial imagery acquired via fixed wing aircraft using a Nikon D810 camera by Chris Larsen Maxar Unknown remote-sensing imagery remote-sensing imagery Unknown observed Worldview Worldview imagery available for scientific use via https://www.maxar.com U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Unknown remote-sensing imagery online U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) https://doi.org/10.5066/F7610XKM https://earthexplorer.usgs.gov/ remote-sensing imagery Unknown observed EROS - Aerial Photo Single Frames Archived aerial photo imagery. U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Unknown remote-sensing imagery online U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) https://earthexplorer.usgs.gov/ remote-sensing imagery Unknown observed Landsat Archived Landsat imagery. U.S. Department of Defense Unknown remote-sensing imagery remote-sensing imagery Unknown observed U.S. Department of Defense, classified Classified aerial and satellite photography. USGS Unknown remote-sensing imagery http://www.gina.alaska.edu/ remote-sensing imagery Unknown observed ifSAR Interferometric synthetic aperture radar (ifSAR) data used to delineate glacier boundaries. Johnson, A. 1980 document USGS Professional Paper 1180 online U.S. Geological Survey Johnson, A., 1980. Grinnell and Sperry Glaciers, Glacier National Park, Montana: a record of vanishing ice: U.S. Geological Survey Professional Paper 1180, 29 p. https://doi.org/10.3133/pp1180 https://doi.org/10.3133/pp1180 publication Unknown observed Johnson 1980, topographic map Topographic map showing historical glacial boundaries. METHODS - GEODETIC PRODUCTS (DEM and ORTHO): Acquisition and processing techniques have evolved since the mid-20th century. While most products used photogrammetry to provide DEMs and Orthos, some recent DEMS (after 2014) have employed Light Detection and Ranging (LiDAR). In many cases, an Ortho coincides with a DEM produced from the same imagery. However, in some cases research grade DEMs were not viable due to poor camera geometries (e.g. Knuth et al., 2023). For LiDAR derived products, DEMs are only available without any coinciding Ortho. ANALOG RECOVERY (Scanning): Analog recovery refers to the scanning and digitizing of original topographic maps following methods described by Sibson, 1981 and Florentine et al., 2018. Products derived using these methods are labeled "Scanning" under the Technique column of the metadata. AERIAL IMAGERY (HSfM, SfM): Aerial Imagery refers to airborne optical stereo imagery acquired over glaciers in North America since the mid-1940s. This imagery has been processed using Structure from Motion methods (SfM), using two different sub-processes. The first means of processing these data is Historical Structure from Motion (HSfM)(Knuth et al., 2023), due to the of lack exterior (i.e., camera location and position) and interior (i.e., camera focal length and radial lens distortion) information available for historical aerial imagery. HSfM algorithms provide means to optimize both exterior and interior camera orientations based on either ground control points (GCPs) or Iterative Closest Point (ICP) co-registration. For GCPs, stable features (e.g. boulders, buildings, intersecting rock joints) visible in both aerial imagery and high-resolution georeferenced images (typically satellite imagery) are used. For ICP co-registration, bare ground control areas are automatically defined using the National Land Cover Dataset (Dewitz, 2023) and Randolph Glacier Inventory (RGI Consortium, 2017). Additionally, focal lengths if physically printed on aerial imagery are incorporated into the processing to optimized camera calibrations and locations, tying SfM point clouds and the resulting DEMs and ortho images to the landscape. See Knuth et al. (2023) for further details on HSfM techniques. Products derived using these methods are labeled "HSfM" under the Technique column of the metadata. The second SfM sub-process used to process aerial imagery has been used for recent aerial imagery. Since 2014, exterior and interior camera information are known, hence eliminating the need for GCP of ICP steps described above under HSfM. The remaining processing steps are otherwise identical following photo alignments, dense cloud derivation, DEM gridding, and orthophoto mosaicking. These aerial imagery datasets were obtained via a Nikon D810 camera with a Distagon 25 mm f/2.0 ZF.2 Lens, or a Nikon D850 camera with a Zeiss 25 mm installed in a Cessna 180 with a camera port. A Trimble R7 GPS connected to an externally mounted Sensor Systems L1/L2 antenna recorded raw GPS data at 5 Hz for aircraft positioning. The camera remote flash port was used to trigger event markers in the Trimble R7 data recording, thereby precisely timing each shutter actuation. Products derived using these methods are labeled "SfM" under the Technique column of the metadata. For all DEMs produced from aerial imagery, no interpolation of the dense cloud was performed, yielding areas containing "no_data" values which are specified in the tagged information of each Geotiff. For Ortho imagery interpolation of the dense cloud was performed allowing for continuous ortho mosaicking where imagery was collected. AERIAL LIGHT DETECTION AND RANGE (LIDAR): Since 2015, consumer-grade LiDAR platforms, coupled to precision global positioning systems have been used for elevation data acquisitions. LiDAR data collected over Wolverine Glacier were acquired via a Riegl VQ-580 ii laser scanner utilizing a Applanix 610 Global Network Satellite System mounted on the bottom of a Cessna 180. These data were finally processed using commercial software (e.g. Applanix POSPac; Riegl RiProcess; QTModeler) to process a final DEM, with no interpolation/extrapolation applied to unresolved areas (e.g., areas of inadequate last-return data). More details on processing LiDAR data into DEMs, and specifically the 2015 LiDAR derived DEM covering Glacier National Park we refer to Pelto et al., 2019. Products derived using these methods are labeled "LiDAR" under the Technique column of the metadata. SATELLITE IMAGERY (ASP, SOCET SET): Commercially sourced satellite imagery (e.g., Maxer) was processed using the open source automated stereogrammetry software Ames Stereo Pipeline (ASP) (Shean et al., 2016). Classified satellite imagery (i.e., National Technical Means) was processed using commercially available software (SOCET SET). DEMs derived from classified sources are made publicly available herein, while the ortho images remain classified and hence, not publicly available. DEMs generated by SOCET SET photogrammetry software contain interpolated areas where elevations cannot be directly resolved from the classified imagery due to poor lighting of surface texture. These areas can be easily identified by inspecting hillshade files derived from the DEM. For commercially obtained satellite imagery, processed using ASP, unresolved areas resulting from poor lighting or surface texture, are not interpolated within of DEMs. Unknown METHODS - GLACIER BOUNDARIES: Glacier boundaries were either digitized from originally interpreted and delineated glacier extent drawn on topographic maps (Johnson, 1980) or directly interpreted and manually delineated from Ortho imagery. For those glacier boundaries that were manually delineated from Ortho imagery, delineation occurred along well-defined regions of the glacier margin (e.g., debris bands or between barren ground and ice) using imagery described in the preceding text. This step was sufficient for glaciers that occupied a well-constrained basin. However, glaciers with ice divides that are shared with other glaciers (Taku), required an extra step. For these glaciers, which also tended to be positioned in perennially snow-covered areas, glacier flow velocity fields, produced and described in Burgess et al. 2013, were used to define glacier boundaries; glacier outlines were defined along divergent velocity fields (Keinholz et al., 2015). In these locations, we assumed ice divides were stationary and did not move through time. Additional outlines for Glacier National Park in 1966, 1998, 2005, and 2015 originally published by Fagre et al. (2017) have been included here and revised in some cases to address issues such as fragmentation, and ensure consistency across all years. For each glacier boundary, attributes contain the year and specific date that the boundary represents, and planar metric area. Additionally, for USGS Benchmark Glaciers (Gulkana, Wolverine, Lemon Creek, Sperry, and South Cascade) the length of the glacier measured along a centerline profile is provided. Unknown METHODS - GLOBAL NAVIGATION SATELLITE SYSTEM (GNSS): Global Navigation Satellite System (GNSS) location data was collected on mass balance stakes installed on a given glacier. Two Trimble GNSS receivers were used to collect simultaneous data at a local survey monument (or base station) and at the survey site. A single receiver was used at Lemon Creek Glaciers which are located within 10 km of a Continuously Operating Reference Station (CORS). Stop-and-go position observations were collected at and around index sites with a minimum 30-seconds of data at each stop; all other observations are static occupations with a minimum 8 minutes of data. The local survey monument location is fixed using the average from Online Positioning User Service (OPUS) positions of the base station files. Maximum baseline length (distance between GNSS receivers) is less than 10 km. Positions are reported in the local UTM zone for a given glacier, WGS-84, with ellipsoid heights. The base station positions associated with local survey monuments were processed using the Online Positioning Service (OPUS) provided by NOAA's National Geodetic Survey. These files generally cover 6–12 hr occupations. Multiple files are averaged to determine the local survey monument location, and the RMSE of those positions is used to estimate the uncertainty in local survey monument position. Survey point locations are processed against the local survey monument location. We processed baselines using precise ephemerides in Trimble Business Center. We calculated mean positions from the baseline length and direction relative to the local base-station. Observations without coincident local base station data and any positions with RMSE greater than 20 cm horizontally and 50 cm vertically do not meet initial quality control criteria and are rejected for use in analysis. Subsequent quality control checks include checks for logical consistency. For example, stake observations were inspected to make sure the name was correct; names were corrected if the correct name could be determined from the time, position, and field notes.The observation was removed if the correct name could not be determined. Repeat surveys of stakes were inspected to make sure the stake appeared to flow down-glacier. Velocities from multiple surveys on the same stake were plotted and inspected for plausibility. Observations with implausible flow directions (e.g. flowing up hill) and velocities (e.g. increase by an order of magnitude) were removed from the final dataset. These omitted measurements were associated with spring (April or May) surveys of older stakes that field notes suggested were badly bent. Unknown LITERATURE CITED: Burgess, E., Forster, R., Larsen, C., 2013. Flow velocities of Alaskan glaciers. Nature Communications 4:2146. https://doi.org/10.1038/ncomms3146 Cogley, J., Hock, R., Rasmussen, L., Arendt, A., Bauder, A., Braithwaite, R., Jansson, P., Kaser, G., Möller, M., Nicholson, L. et al., 2011. Glossary of glacier mass balance and related terms, IHP-VII technical documents in hydrology No. 86, IACS Contribution No. 2. UNESCO-IHP, Paris Dewitz, J., 2023. National Land Cover Database (NLCD) 2021 Products: U.S. Geological Survey data release, https://doi.org/10.5066/P9JZ7AO3 Fagre, D., McKeon, L., Dick, K., Fountain, A., 2017. Glacier margin time series (1966, 1998, 2005, 2015) of the named glaciers of Glacier National Park, MT, USA: U.S. Geological Survey data release, https://doi.org/10.5066/F7P26WB1 Falgout, J.T., Gordon, J., USGS Advanced Research Computing, USGS Yeti Supercomputer: U.S. Geological Survey, https://doi.org/10.5066/F7D798MJ Florentine, C., Harper, J., Fagre, D., Moore, J., Peitzsch, E., 2018. Local topography increasingly influences the mass balance of a retreating cirque glacier. The Cryosphere 12:2109-2122. https://doi.org/10.5194/tc-12-2109-2018 Florentine, C., Sass, L., McNeil, C., Baker, E., O'Neel, S., 2023. How to handle glacier area change in geodetic mass balance. Journal of Glaciology 69(278):2169-2175. https://doi.org/10.1017/jog.2023.86 Johnson, A., 1980. Grinnell and Sperry Glaciers, Glacier National Park, Montana. A record of vanishing ice: U.S. Geological Survey Professional Paper 1180, 29p. https://doi.org/10.3133/pp1180 Kienholz, C., Herreid, S., Rich, J., Arendt, A., Hock, R., Burgess, E., 2015. Derivation and analysis of a complete modern-date glacier inventory for Alaska and northwest Canada. Journal of Glaciology 61(227):403-420. https://doi.org/10.3189/2015JoG14J230 Kienholz, C., Hock, R., Truffer, M., Arendt, A., Arko, S., 2016. Geodetic mass balance of surge‐type Black Rapids Glacier, Alaska, 1980-2001-2010, including role of rockslide deposition and earthquake displacement. Journal of Geophysical Research: Earth Surface 121(12):2358-2380. https://doi.org/10.1002/2016JF003883 Knuth, F., Shean, D., Bhushan, S., Schwat, E., Alexandrov, O., McNeil, C., Dehecq, A., Florentine, C., O'Neel, S., 2023. Historical Structure from Motion (HSfM): Automated processing of historical aerial photographs for long-term topographic change analysis. Remote Sensing of Environment 285:113379. https://doi.org/10.1016/j.rse.2022.113379 Nolan, M., Post, A., Hauer, W., Zinck, A., O'Neel, S., 2017. Photogrammetric scans of aerial photographs of North American glaciers. Arctic Data Center. https://doi.org/10.18739/A2VH5CJ8K O'Neel, S., Hood, E., Arendt, A., Sass L., 2014. Assessing streamflow sensitivity to variations in glacier mass balance: Climatic Change 123(2):329–341 https://doi.org/10.1007/s10584-013-1042-7 O'Neel, S., McNeil, C.J., Sass, L.C., Florentine, C.E., Baker, E.H., Peitzsch, E.H., McGrath, D., Fountain, A.G., Fagre, D.B., 2019. Reanalysis of the US Geological Survey Benchmark Glaciers: Long-term insight into climate forcing of glacier mass balance. Journal of Glaciology 63(253):850-866. https://doi.org/10.1017/jog.2019.66 Pelto, B.M., Menounos, B., Marshall, S.J., 2019. Multi-year evaluation of airborne geodetic surveys to estimate seasonal mass balance, Columbia and Rocky Mountains, Canada. Cryosphere 13(6):1709–1727. https://doi.org/10.5194/tc-13-1709-2019 Pfeffer, W.T., Arendt, A.A., Bliss, A., et al., 2014. The Randolph Glacier Inventory: a globally complete inventory of glaciers. Journal of Glaciology. 60(221):537-552. https://doi.org/10.3189/2014JoG13J176 RGI Consortium, 2017. Randolph Glacier Inventory – A Dataset of Global Glacier Outlines, Version 6.0. Boulder, Colorado, USA: National Snow and Ice Data Center. https://doi.org/10.7265/N5-RGI-60 Sevara, C., 2013. Top secret topographies: recovering two and three-dimensional archaeological information from historic reconnaissance datasets using image-based modelling techniques. International Journal of Heritage in the Digital Era 2(3):395-418. https://doi.org/10.1260/2047-4970.2.3.395 Shean, D., Alexandrov, O., Moratto, Z., Smith, B., Joughin, I., Porter, C., Morin P., 2016. An automated, open-source pipeline for mass production of digital elevation models (DEMs) from very-high-resolution commercial stereo satellite imagery. ISPRS Journal of Photogrammetry and Remote Sensing 116:101-117. https://doi.org/10.1016/j.isprsjprs.2016.03.012 Sibson, R., 1981. A brief description of natural neighbor interpolation. In: Barnett, V., ed., Interpreting Multivariate Data, John Wiley and Sons, New York, pp 21-36. Van Beusekom, A., O'Neel, S., March, R., Sass, L., Cox, L., 2010. Re-analysis of Alaskan Benchmark Glacier Mass-Balance Data Using the Index Method: U.S. Geological Survey, Scientific Investigations Report 2010–5247, 16p. https://doi.org/10.3133/sir20105247 Verhoeven, G., Taelman, D., Vermeulen, F., 2012. Computer vision-based orthophoto mapping of complex archaeological sites: the ancient quarry of Pitaranha (Portugal–Spain). Archaeometry 54(6):1114-1129. https://doi.org/10.1111/j.1475-4754.2012.00667.x Zemp, M., Thibert, E., Huss, M., Stumm, D., Rolstad Denby, C., Nuth, C., Nussbaumer, S., Moholdt, G., Mercer, A., Mayer, C., Joerg, P., Jansson, P., Hynek, B., Fischer, A., Escher-Vetter, H., Elvehoy, H., Andreassen, L., 2013. Reanalysing glacier mass balance measurement series. The Cryosphere 7(4):1227-1245. https://doi.org/10.5194/tc-7-1227-2013 Unknown Vector Area chain 50 Transverse Mercator 0.9996 -147.0 0.0 500000.0 0.0 coordinate pair 1 1 meters World Geodetic System of 1984 (WGS84) World Geodetic System of 1984 (WGS84) 6378137 298.257223563 World Geodetic System of 1984 (WGS84) 0.5 0.01 meters Explicit elevation coordinate included with horizontal coordinates USGS_Glacier_DEMOrtho_Metadata.xlsx Table with source information for each image used to derive glacier boundaries, DEMs, and Orthos. Presented in an Excel (XLSX) formatted spreadsheet. The data are also provided geospatially in Esri Shapefile and KML formats. Author defined Date Date of the source image acquisition. Author defined Date of the source image acquisition (mm/dd/yyyy). Year Year of the source image acquisition. Author defined Year of the source image acquisition. Filename Region and date of the DEM or Ortho. Blank cells indicate that neither a DEM or Ortho is provided. A vector geospatial glacier boundary is provided in the "USGS_Glacier_Boundaries_shp" file included in this data release. Author defined Filename of the DEM or Ortho. DEM_Pixel_Size Pixel size; raster spatial resolution, in square meters Author defined Pixel size; raster spatial resolution, in square meters Ortho_Pixel_Size Pixel size; raster spatial resolution, in square meters Author defined Pixel size; raster spatial resolution, in square meters Benchmark_Glacier Name of the USGS Benchmark Glacier within each DEM or Ortho. Blank cells indicate that the image does not include a USGS Benchmark Glacier. Author defined Name of the USGS Benchmark Glacier within each DEM or Ortho. Other_Glaciers Name(s) of any other glaciers within each DEM or Ortho. Blank cells indicate that the image does not include other glaciers. Author defined Name(s) of any other glaciers within each DEM or Ortho. Region General geographic region of the glacier. Author defined Deltas The glacier is located in the Delta Mountains; the eastern subrange of the Alaska Range; east of the Delta River, Alaska. Author defined EasternKenai The glacier is located in the eastern portion of the Kenia Peninsula; east of the Seward Highway and south of Portage, Alaska. Author defined JuneauIcefield The glacier is located in the Juneau Icefield; the glaciated region of southeast Alaska, USA and northwest British Columbia, Canada; east of Juneau, south of the Klondilke Highway, west of Atlin Lake, and north of the Taku River. Author defined Cascades The glacier is located in the North Cascade Mountains; the portion of the Cascade Mountain Range of western North America within the state of Washington. Author defined GlacierNationalPark The glacier is located in Glacier National Park, Montana. Author defined Technique Method of DEM creation. Blank cells indicate that no DEM was produced. Author defined ASP Ames Stereo Pipeline (ASP) used to generate DEMs from satellite imagery. Author defined HSfm Historical Structure from motion (HSfm) techniques used to create DEM. Author defined LiDAR Aerial Light Detection and Range (LiDAR) techniques used to create DEM. Author defined Scanning DEM derived from scanned topographic maps. Author defined Sfm Structure from motion (Sfm) techniques used to create DEM. Author defined Socet Set Commercially available software named SOCET SET used to generate DEMs from classified imagery. Author defined Platform Type of imagery used to produce the DEM and Ortho. Blank cells indicate that there is no DEM or Ortho. Author defined aerial Aerial imagery was used to produce the DEM and Ortho. Author defined satellite Satellite imagery used to produce the DEM and Ortho. Author defined Source The source imagery used to produce the DEM and Ortho. Author defined The source imagery used to produce the DEM and Ortho. DEM_Technician Name of the technician who produced the DEM or Ortho. Blank cells indicate that no DEM or Ortho was produced. Author defined Name of the technician who produced the DEM or Ortho. Boundary Whether a glacier boundary vector polygon was produced from the source image. Author defined Yes A glacier boundary vector polygon was produced from the source image. Author defined No No glacier boundary vector polygon was produced from the source image. Author defined Source_Imagery_Access Web lin to access the source data, if available. Author defined Web lin to access the source data, if available. DEM_download Clickable link to directly download the DEM. Author defined Clickable link to directly download the DEM. Ortho_download Clickable link to directly download the Ortho. Author defined Clickable link to directly download the Ortho. UTM_EPSG EPSG code for the UTM zone in which the glacier is located. Author defined EPSG code for the UTM zone in which the glacier is located. USGS_Glacier_Boundaries_shp ZIP package containing vector geospatial data of glacier boundaries, either digitized from original topographic maps (Johnson, 1980) or manually delineated along well-defined regions of the glacier margin. Attribute tables include the name of the glacier, the glacier boundary for each year, the specific date of imagery acquisition, glacier area, and glacier length. Presented in both ESRI shapefile (SHP) and Keyhole Markup Language (KML) formats. Files are named following the convention: [Glacier]_Glacier_Boundaries.shp (.kml) Author defined Glacier Name of the glacier. Author defined Name of the glacier. Region General geographic region of the glacier. Author defined Deltas The glacier is located in the Delta Mountains; the eastern subrange of the Alaska Range; east of the Delta River, Alaska. Author defined EasternKenai The glacier is located in the eastern portion of the Kenia Peninsula; east of the Seward Highway and south of Portage, Alaska. Author defined JuneauIcefield The glacier is located in the Juneau Icefield; the glaciated region of southeast Alaska, USA and northwest British Columbia, Canada; east of Juneau, south of the Klondilke Highway, west of Atlin Lake, and north of the Taku River. Author defined Cascades The glacier is located in the North Cascade Mountains; the portion of the Cascade Mountain Range of western North America within the state of Washington. Author defined GlacierNationalPark The glacier is located in Glacier National Park, Montana. Author defined Year Year that source image of the glacier margin was taken. Author defined 1948 2021 Year (YYYY) Date Specific date of imagery acquisition (YYYY/MM/DD) Author defined 1948/07/05 2021/10/05 Date (YYYY/MM/DD) Area Glacier area on referenced date Author defined 0.81 19.22 Square kilometers (km2) 0.01 Area Area of the USGS Glacier. Author defined 0.02 727.12 Square kilometers (km2) 0.01 Length Length of the USGS Benchmark Glacier along centerline. Blank cells indicate that the glacier is not a USGS Benchmake Glacier. Author defined 1.24 54.65 Kilometers (km) 0.01 USGS_Glacier_GNSS.csv Table with point observations at mass balance stakes. Data include mass balance stake point location in XYZ space measured by Global Navigation Satellite System (GNSS), surface height measurement, and measurement date. Presented in a Comma Separated Value (CSV) formatted table. Author defined Glacier Name of the glacier. Author defined Name of the glacier. Region General geographic region of the glacier. Author defined Deltas The glacier is located in the Delta Mountains; the eastern subrange of the Alaska Range; east of the Delta River, Alaska. Author defined EasternKenai The glacier is located in the eastern portion of the Kenia Peninsula; east of the Seward Highway and south of Portage, Alaska. Author defined JuneauIcefield The glacier is located in the Juneau Icefield; the glaciated region of southeast Alaska, USA and northwest British Columbia, Canada; east of Juneau, south of the Klondilke Highway, west of Atlin Lake, and north of the Taku River. Author defined Cascades The glacier is located in the North Cascade Mountains; the portion of the Cascade Mountain Range of western North America within the state of Washington. Author defined GlacierNationalPark The glacier is located in Glacier National Park, Montana. Author defined Stake_name Labeled name of the stake. Author defined Labeled name of the stake. Site Name of the mass balance site, or name of the survey object. Author defined Name of the mass balance site, or name of the survey object. Year Year that the stake or installation was placed. Author defined 2012 2021 Year Date Year month day when the stake or object was surveyed. Author defined 4/23/2015 8/31/2021 Date (mm/dd/yyyy) Survey_surface_height The surface height on the mass balance stake. This represents the distance from the bottom of the stake, which is drilled into the glacier below the snow/ice surface, to the glacier (snow or ice) surface on the stake at the time of survey. Author defined 0.7 16.82 meters 0.01 Easting UTM coordinate in the X direction of the stake. Author defined 393282.96 397183.98 meters 0.01 Northing UTM coordinate in the Y direction of the stake. Author defined 6695144.17 6700910.9 meters 0.01 Elevation Elevation at the glacier or land surface expressed as a height above the ellipsoid Author defined 550.66 1547.9 Meters 0.01 UTM_EPSG EPSG code for the UTM zone in which the glacier is located. Author defined EPSG code for the UTM zone in which the glacier is located. Latitude Latitude of the stake. Author defined 60.378874 60.4308681 Decimal degrees (WGS84) 0.000001 Longitude Longitude of the stake. Author defined -148.9383815 -148.8671773 Decimal degrees (WGS84) 0.000001 LatLon_EPSG EPSG code for WGS84 geographic coordinates. Author defined EPSG code for WGS84 geographic coordinates. Digital Elevation Models (DEM) Digital Elevation Models (DEM) of glaciers, derived from aerial stereo photography, historic topographic maps, high-resolution satellite imagery. The images are compressed (ZIP) for individual download in the 'Child Item' labeled Digital Elevation Models (DEM). Provided in GeoTIFF format. Individual files are named according to the date of image acquisition, following the convention [region]_ [yyyymmdd]_DEM.tif. Author defined Orthorectified images (Orthos) Orthorectified images (Orthos) of glaciers, derived from aerial stereo photography, historic topographic maps, high-resolution satellite imagery. The images are compressed (ZIP) for individual download in the 'Child Item' labeled Orthos. Provided in GeoTIFF format. Individual files are named according to the date of image acquisition, following the convention [region]_ [yyyymmdd]_Ortho.tif. Author defined U.S. Geological Survey USGS ScienceBase Team Mailing and Physical

Denver Federal Center, Building 810, Mail Stop 302

Denver Colorado 80225 USA 1-888-275-8747 sciencebase@usgs.gov The U.S. Geological Survey, Alaska Science Center is the authoritative source of these data, distributed by ScienceBase (a USGS Trusted Digital Repository). Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey, no warranty expressed or implied is made regarding the display or utility of the data for other purposes or on all computer systems, nor shall the act of distribution constitute any such warranty. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. TIF, SHP, KML, CSV Raster geospatial data in GeoTIFF format, vector geospatial data in SHP and KML formats, tabular data in CSV format; FGDC metadata in XML and HTML formats. https://doi.org/10.5066/P9R8BP3K None 20250517 U.S. Geological Survey, Alaska Science Center Mailing and Physical

4210 University Drive

Anchorage Alaska 99508 USA 907-786-7000 gs-ak_asc_datamanagers@usgs.gov FGDC Content Standard for Digital Geospatial Metadata (CSDGM) FGDC-STD-001-1998