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.

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.

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.

In the Prince William Sound region of Alaska, recent glacier retreat started in the mid-1800s and began to accelerate in the mid-2000s in response to warming air temperatures (Maraldo and others, 2020). Prince William Sound is surrounded by the central Chugach Mountains and consists of numerous ocean-terminating glaciers, with rapid deglaciation increasingly exposing oversteepened bedrock walls of fiords. Deglaciation may accelerate the occurrence of rapidly moving rock avalanches (RAs), which have the potential to generate tsunamis and adversely impact maritime vessels, marine activities, and coastal infrastructure and populations in the Prince William Sound region. RAs have been documented in the Chugach Mountains in the past (Post, 1967; McSaveney, 1978; Uhlmann and others, 2013), but a time series of RAs in the Chugach Mountains is not currently available. A systematic inventory of RAs in the Chugach is needed as a baseline to evaluate any future changes in RA frequency, magnitude, and mobility. This data release presents a comprehensive historical inventory of RAs in a 4600 km2 area of the Prince William Sound. The inventory was generated from: (1) visual inspection of 30-m resolution Landsat satellite images collected between July 1984 and August 2024; and (2) the use of an automated image classification script (Google earth Engine supRaglAciaL Debris INput dEtector (GERALDINE, Smith and others, 2020)) designed to detect new rock-on-snow events from repeat Landsat images from the same time period. RAs were visually identified and mapped in a Geographic Information System (GIS) from the near-infrared (NIR) band of Landsat satellite images. This band provides significant contrast between rock and snow to detect newly deposited rock debris. A total of 252 Landsat images were visually examined, with more images available in recent years compared to earlier years (Figure 1). Calendar year 1984 was the first year when 30-m resolution Landsat data were available, and thus provided a historical starting point from which RAs could be detected with consistent certainty. By 2017, higher resolution (<5-m) daily Planet satellite images became consistently available and were used to better constrain RA timing and extent. Figure 1. Diagram showing the number of usable Landsat images per year. This inventory reveals 118 RAs ranging in size from 0.1 km2 to 2.3 km2. All of these RAs occurred during the months of May through September (Figure 2). The data release includes three GIS feature classes (polygons, points, and polylines), each with its own attribute information. The polygon feature class contains the entire extent of individual RAs and does not differentiate the source and deposit areas. The point feature class contains headscarp and toe locations, and the polyline feature class contains curvilinear RA travel distance lines that connect the headscarp and toe points. Additional attribute information includes the following: location of headscarp and toe points, date of earliest identified occurrence, if and when the RA was sequestered into the glacier, presence and delineation confidence levels (see Table 1 for definition of A, B, and C confidence levels), identification method (visual inspection versus automated detection), image platform, satellite, estimated cloud cover, if the RA is lobate, image ID, image year, image band, affected area in km2, length, height, length/height, height/length, notes, minimum and maximum elevation, aspect at the headscarp point, slope at the headscarp point, and geology at the headscarp point. Topographic information was derived from 5-m interferometric synthetic aperture radar (IfSAR) Digital Elevation Models (DEMs) that were downloaded from the USGS National Elevation Dataset website (U.S. Geological Survey, 2015) and were mosaicked together in ArcGIS Pro. The aspect and slope layers were generated from the downloaded 5-m DEM with the “Aspect” and “Slope” tools in ArcGIS Pro. Aspect and slope at

In the Prince William Sound region of Alaska, recent glacier retreat started in the mid-1800s and began to accelerate in the mid-2000s in response to warming air temperatures (Maraldo and others, 2020). Prince William Sound is surrounded by the central Chugach Mountains and consists of numerous ocean-terminating glaciers, with rapid deglaciation increasingly exposing oversteepened bedrock walls of fiords. Deglaciation may accelerate the occurrence of rapidly moving rock avalanches (RAs), which have the potential to generate tsunamis and adversely impact maritime vessels, marine activities, and coastal infrastructure and populations in the Prince William Sound region. RAs have been documented in the Chugach Mountains in the past (Post, 1967; McSaveney, 1978; Uhlmann and others, 2013), but a time series of RAs in the Chugach Mountains is not currently available. A systematic inventory of RAs in the Chugach is needed as a baseline to evaluate any future changes in RA frequency, magnitude, and mobility. This data release presents a comprehensive historical inventory of RAs in a 4600 km2 area of the Prince William Sound. The inventory was generated from: (1) visual inspection of 30-m resolution Landsat satellite images collected between July 1984 and August 2024; and (2) the use of an automated image classification script (Google earth Engine supRaglAciaL Debris INput dEtector (GERALDINE, Smith and others, 2020)) designed to detect new rock-on-snow events from repeat Landsat images from the same time period. RAs were visually identified and mapped in a Geographic Information System (GIS) from the near-infrared (NIR) band of Landsat satellite images. This band provides significant contrast between rock and snow to detect newly deposited rock debris. A total of 252 Landsat images were visually examined, with more images available in recent years compared to earlier years (Figure 1). Calendar year 1984 was the first year when 30-m resolution Landsat data were available, and thus provided a historical starting point from which RAs could be detected with consistent certainty. By 2017, higher resolution (<5-m) daily Planet satellite images became consistently available and were used to better constrain RA timing and extent. Figure 1. Diagram showing the number of usable Landsat images per year. This inventory reveals 118 RAs ranging in size from 0.1 km2 to 2.3 km2. All of these RAs occurred during the months of May through September (Figure 2). The data release includes three GIS feature classes (polygons, points, and polylines), each with its own attribute information. The polygon feature class contains the entire extent of individual RAs and does not differentiate the source and deposit areas. The point feature class contains headscarp and toe locations, and the polyline feature class contains curvilinear RA travel distance lines that connect the headscarp and toe points. Additional attribute information includes the following: location of headscarp and toe points, date of earliest identified occurrence, if and when the RA was sequestered into the glacier, presence and delineation confidence levels (see Table 1 for definition of A, B, and C confidence levels), identification method (visual inspection versus automated detection), image platform, satellite, estimated cloud cover, if the RA is lobate, image ID, image year, image band, affected area in km2, length, height, length/height, height/length, notes, minimum and maximum elevation, aspect at the headscarp point, slope at the headscarp point, and geology at the headscarp point. Topographic information was derived from 5-m interferometric synthetic aperture radar (IfSAR) Digital Elevation Models (DEMs) that were downloaded from the USGS National Elevation Dataset website (U.S. Geological Survey, 2015) and were mosaicked together in ArcGIS Pro. The aspect and slope layers were generated from the downloaded 5-m DEM with the “Aspect” and “Slope” tools in ArcGIS Pro. Aspect and slope at

The Alaska Division of Geological & Geophysical Surveys (DGGS) used aerial lidar to produce a classified point cloud and high-resolution digital terrain model (DTM), digital surface model (DSM), and intensity model of the Barry Arm landslide, northwest Prince William Sound, Alaska, during near snow-free ground conditions on June 26, 2020. The survey's goal is to provide high quality and high resolution (0.10 m) elevation data to assess potential landslide movement. Aerial lidar and ground control data were collected on June 26, 2020, and subsequently processed in Terrasolid and ArcGIS. Ground control was collected on June 26, 2020, as well. This data collection is released as a Raw Data File with an open end-user license. All files can be downloaded free of charge from the Alaska Division of Geological & Geophysical Surveys website (http://doi.org/10.14509/30593).

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.