The effects of climate change have the potential to impact slope stability. Negative impacts are expected to be greatest at high northerly latitudes where degradation of permafrost in rock and soil, debuttressing of slopes as a result of glacial retreat, and changes in ocean ice-cover are likely to increase the susceptibility of slopes to landslides. In the United States, the greatest increases in air temperature and precipitation are expected to occur in Alaska. In order to assess the impact that these environmental changes will have on landslide size (magnitude), mobility, and frequency, inventories of historical landslides are needed. These inventories provide baseline data that can be used to identify changes between historical and future landslide magnitude, mobility, and frequency. This data release presents GIS and attribute data for an inventory of rock avalanches in a 5000 sq. km area of western Glacier Bay National Park and Preserve, Alaska. We created the inventory from 30 m resolution Landsat imagery acquired from June 1984 to September 2016. For each calendar year, we visually examined a minimum of one Landsat image obtained between the months of May and October. We examined a total of 104 Landsat images. The contrast between the spectral signatures of freshly exposed rock avalanche source areas and deposits and surrounding, undisturbed snow and ice is typically significant enough to detect surficial changes. We identified and mapped rock avalanches by locating areas with 1) high contrast compared to surrounding snow and ice, 2) different spectral signatures between successive Landsat images, and 3) lobate forms typical of rock-avalanche deposits. Using these criteria, we mapped a total of 24 rock avalanches ranging in size from 0.1 to 22 km2. Attribute data for each rock avalanche includes: a date, or range in possible dates, of occurrence; the name of the Landsat image(s) used to identify and map the avalanche; the total area covered by the rock avalanche (including the source area and deposit); the maximum travel distance measured along a curvilinear centerline (L); and the change in elevation between the start and end points of the centerline (H). We also include a table containing a list of all the Landsat images examined. We acknowledge that our mapped polygons will be different, and less accurate, than polygons that could be mapped from higher-resolution satellite, aerial, and hand-held imagery. We specifically chose not to use high resolution imagery because we desired a long-term historical inventory that was unbiased by changes in image resolution. Eventually, new mapping should be done to create an inventory that fully utilizes recently available high-resolution imagery. Data included in this release form the basis of an interpretive paper available in the conference proceedings of the 3rd North American Symposium on Landslides held in Roanoke, Virginia in June, 2017.

Glacial retreat and mountain-permafrost degradation resulting from rising global temperatures have the potential to impact the frequency and magnitude of landslides in glaciated environments. In the Saint Elias Mountains of southeast Alaska, the presence of weak sedimentary and metamorphic rocks and active uplift resulting from the collision of the Yakutat and North American tectonic plates create landslide-prone conditions (Winkler et al., 2000). We used Landsat imagery to create an inventory of large (>0.1 square km) rock avalanches that occurred along the south flank of the Saint Elias Mountains between 1984 and 2019 as a baseline for present and future changes in landslide magnitude and frequency. This data release presents geographic information system (GIS) and attribute data for 220 rock avalanches in a 3700 square km area of the Saint Elias Mountains, Alaska. Map data consist of polygons delineating total rock avalanche areas (StEliasRockAvalanches.shp), headscarp points (StEliasRockAvHS.shp), and travel distance lines (StEliasRockAvTD.shp). Attribute data for mapped rock avalanches include area (undifferentiated source and deposit areas), travel distance (L), fall height (H), ratio of H/L, and headscarp location (latitude, longitude), elevation, slope, and aspect. Attribute data also include the event date range and information on the Landsat images used to identify and map each rock avalanche. Data are provided as point, line, and polygon shape files (.shp). We also include information on the Landsat images that were used for rock avalanche identification and mapping (LandsatImagery.csv). References: Winkler, G.R., MacKevett, E.M., Plafker, G. Jr., Richter, D.H., Rosenkrans, D.S., and Schmoll, H.R. (2000). A geologic guide to Wrangell-Saint Elias National Park and Preserve, Alaska, A tectonic collage of northbound terranes. U.S. Geological Survey Professional Paper 1616. Reston: U.S. Geological Survey, 166 p.

Glacial retreat and mountain-permafrost degradation resulting from rising global temperatures have the potential to impact the frequency and magnitude of landslides in glaciated environments. In the Saint Elias Mountains of southeast Alaska, the presence of weak sedimentary and metamorphic rocks and active uplift resulting from the collision of the Yakutat and North American tectonic plates create landslide-prone conditions (Winkler et al., 2000). We used Landsat imagery to create an inventory of large (>0.1 square km) rock avalanches that occurred along the south flank of the Saint Elias Mountains between 1984 and 2019 as a baseline for present and future changes in landslide magnitude and frequency. This data release presents geographic information system (GIS) and attribute data for 220 rock avalanches in a 3700 square km area of the Saint Elias Mountains, Alaska. Map data consist of polygons delineating total rock avalanche areas (StEliasRockAvalanches.shp), headscarp points (StEliasRockAvHS.shp), and travel distance lines (StEliasRockAvTD.shp). Attribute data for mapped rock avalanches include area (undifferentiated source and deposit areas), travel distance (L), fall height (H), ratio of H/L, and headscarp location (latitude, longitude), elevation, slope, and aspect. Attribute data also include the event date range and information on the Landsat images used to identify and map each rock avalanche. Data are provided as point, line, and polygon shape files (.shp). We also include information on the Landsat images that were used for rock avalanche identification and mapping (LandsatImagery.csv). References: Winkler, G.R., MacKevett, E.M., Plafker, G. Jr., Richter, D.H., Rosenkrans, D.S., and Schmoll, H.R. (2000). A geologic guide to Wrangell-Saint Elias National Park and Preserve, Alaska, A tectonic collage of northbound terranes. U.S. Geological Survey Professional Paper 1616. Reston: U.S. Geological Survey, 166 p.

Starting in 2003, the U.S. Geological Survey (USGS) Northern Rocky Mountain Science Center in West Glacier, MT, in collaboration with the National Park Service, collected avalanche observations along the Going to the Sun Road during the spring road-clearing operations. The spring road-clearing along Going to the Sun Road utilized a team of avalanche specialists from the USGS and Glacier National Park to communicate the potential avalanche hazard to crews working to clear the road of snow in preparation for summer visitation. The operations typically begin around April 1st and continue through mid-June each year. The dataset includes all of the specific details collected for each avalanche occurrence and conforms to SWAG (American Avalanche Association, 2016. Snow, Weather and Avalanches: Observation Guidelines for Avalanche Programs in the United States (3rd ed). Victor, ID). The records should be viewed as estimates of avalanche characteristics due to the fact that many of the avalanches are too distant or are too dangerous to accurately assess.

Starting in 2003, the U.S. Geological Survey (USGS) Northern Rocky Mountain Science Center in West Glacier, MT, in collaboration with the National Park Service, collected avalanche observations along the Going to the Sun Road during the spring road-clearing operations. The spring road-clearing along Going to the Sun Road utilized a team of avalanche specialists from the USGS and Glacier National Park to communicate the potential avalanche hazard to crews working to clear the road of snow in preparation for summer visitation. The operations typically begin around April 1st and continue through mid-June each year. The dataset includes all of the specific details collected for each avalanche occurrence and conforms to SWAG (American Avalanche Association, 2016. Snow, Weather and Avalanches: Observation Guidelines for Avalanche Programs in the United States (3rd ed). Victor, ID). The records should be viewed as estimates of avalanche characteristics due to the fact that many of the avalanches are too distant or are too dangerous to accurately assess.

The use of high-resolution remotely sensed imagery can be an effective way to obtain quantitative measurements of rock-avalanche volumes and geometries in remote glaciated areas, both of which are important for an improved understanding of rock-avalanche characteristics and processes. We utilized the availability of high-resolution (~0.5 m) WorldView satellite stereo imagery to derive digital elevation data in a 100 km2 area around the 28 June 2016 Lamplugh rock avalanche in Glacier Bay National Park and Preserve, Alaska. We used NASA Ames Stereo Pipeline, an open-source software package available from NASA, to produce one pre- and four post-event digital elevation models (DEMs) of the area surrounding the Lamplugh rock avalanche. This data release includes five raster elevation datasets (2-m resolution) in GeoTIFF format that have been orthrectified to the Universal Transverse Mercator (UTM) coordinate system (zone 7N). Elevations are measured in reference to the World Geodetic System 1984 (WGS84) ellipsoid. Because the study area is remote and difficult to access, ground control was not available to assess the absolute accuracy of DEMs. The DEMs have not been precisely co-registered. Data contained in this release include a pre-event DEM from 15 June 2016, and post-event DEMs from 16 July 2016, 27 August 2016, 27 September 2016, and 28 September 2016. The filenames for these DEMs are 20160615_LamplughDEM.tif, 20160716_LamplughDEM.tif, 20160827_LamplughDEM.tif, 20160927_LamplughDEM.tif, and 20160928_LamplughDEM.tif, respectively. We also provide a CSV file (Lamplugh_DEM_Image_Notes.csv) that contains the acquisition date, satellite platform, image identification number, resolution, off-nadir angle, and notes on image quality for each stereo pair used to generate DEMs.

The use of high-resolution remotely sensed imagery can be an effective way to obtain quantitative measurements of rock-avalanche volumes and geometries in remote glaciated areas, both of which are important for an improved understanding of rock-avalanche characteristics and processes. We utilized the availability of high-resolution (~0.5 m) WorldView satellite stereo imagery to derive digital elevation data in a 100 km2 area around the 28 June 2016 Lamplugh rock avalanche in Glacier Bay National Park and Preserve, Alaska. We used NASA Ames Stereo Pipeline, an open-source software package available from NASA, to produce one pre- and four post-event digital elevation models (DEMs) of the area surrounding the Lamplugh rock avalanche. This data release includes five raster elevation datasets (2-m resolution) in GeoTIFF format that have been orthrectified to the Universal Transverse Mercator (UTM) coordinate system (zone 7N). Elevations are measured in reference to the World Geodetic System 1984 (WGS84) ellipsoid. Because the study area is remote and difficult to access, ground control was not available to assess the absolute accuracy of DEMs. The DEMs have not been precisely co-registered. Data contained in this release include a pre-event DEM from 15 June 2016, and post-event DEMs from 16 July 2016, 27 August 2016, 27 September 2016, and 28 September 2016. The filenames for these DEMs are 20160615_LamplughDEM.tif, 20160716_LamplughDEM.tif, 20160827_LamplughDEM.tif, 20160927_LamplughDEM.tif, and 20160928_LamplughDEM.tif, respectively. We also provide a CSV file (Lamplugh_DEM_Image_Notes.csv) that contains the acquisition date, satellite platform, image identification number, resolution, off-nadir angle, and notes on image quality for each stereo pair used to generate DEMs.

Landslide-generated tsunamis pose significant hazards, but developing models to assess these hazards presents unique challenges. George and others (2017) present a new methodology in which a depth-averaged two-phase landslide model (D-Claw) is used to simulate all stages of landslide dynamics and subsequent tsunami generation, propagation, and inundation. Because the model describes the evolution of solid and fluid volume fractions, it treats both landslides and tsunamis as special cases of a more general class of phenomena. Therefore, the landslide and tsunami can be seamlessly and efficiently simulated as a single-layer continuum with evolving solid-grain concentrations, and with wave generation via mass displacement and direct longitudinal momentum transfer: dominant physical mechanisms that are unresolved with traditional modeling approaches. To test their methodology, George and others (2017) used D-Claw to model a large subaerial landslide and resulting tsunami that occurred on October, 17, 2015, in Taan Fiord near the terminus of Tyndall Glacier, Alaska. Modeled shoreline inundation patterns compare well with observations derived from satellite imagery. This data release contains topographic datasets used to model the landslide and a Normalized difference vegetation index (NDVI) change image used to assess the model results. These data are intended to accompany the journal article by George and others (2017): George, D.L., Iverson, R.M., and Cannon, C.M., 2017, New methodology for computing tsunami generation by subaerial landslides: application to the 2015 Tyndall Glacier Landslide, Alaska, Geophysical Research Letters, 44, doi:10.1002/2017GL074341.

Pluvials can have dramatic impacts on the shoreline bluffs of Lake Michigan due to increases in both shallow subsurface moisture conditions related to the prolonged wet weather pattern and wave erosion as the lake level rises. These changes can result in an increased frequency and magnitude of slope failures. During the most recent pluvial, the monthly average level of Lake Michigan rose 1.9 m from a record low in January 2013 to a near record high in June-July 2020. To assess the impacts on coastal bluffs from slope failures during the recent pluvial, an inventory of landslides was completed, including slope failures active during the early part of the pluvial, on the coastal bluffs of North Manitou Island, part of the Sleeping Bear Dunes National Lakeshore in Michigan. Landslides were mapped using high-resolution orthoimagery, collected in April 2012, and high-resolution topography derived from a LiDAR data set, collected in December 2014. This data release presents geographic information system (GIS) data, provided as line and polygon shapefiles (.shp), depicting landslides and related landforms and features. Polygon map data delineates the areas of deposits, source areas, and related landforms (such as alluvial fans and colluvial aprons). Scarps (such as headscarps and minor scarps) are presented as hachured line data. An attribute file is included providing a definition of the mapped units and a brief description of the approach used in the mapping.

Pluvials can have dramatic impacts on the shoreline bluffs of Lake Michigan due to increases in both shallow subsurface moisture conditions related to the prolonged wet weather pattern and wave erosion as the lake level rises. These changes can result in an increased frequency and magnitude of slope failures. During the most recent pluvial, the monthly average level of Lake Michigan rose 1.9 m from a record low in January 2013 to a near record high in June-July 2020. To assess the impacts on coastal bluffs from slope failures during the recent pluvial, an inventory of landslides was completed, including slope failures active during the early part of the pluvial, on the coastal bluffs of North Manitou Island, part of the Sleeping Bear Dunes National Lakeshore in Michigan. Landslides were mapped using high-resolution orthoimagery, collected in April 2012, and high-resolution topography derived from a LiDAR data set, collected in December 2014. This data release presents geographic information system (GIS) data, provided as line and polygon shapefiles (.shp), depicting landslides and related landforms and features. Polygon map data delineates the areas of deposits, source areas, and related landforms (such as alluvial fans and colluvial aprons). Scarps (such as headscarps and minor scarps) are presented as hachured line data. An attribute file is included providing a definition of the mapped units and a brief description of the approach used in the mapping.