Increasing rock-avalanche size and mobility in Glacier Bay National Park and Preserve, Alaska detected from 1984 to 2016 Landsat imagery
In the USA, climate change is expected to have an adverse impact on slope stability in Alaska. However, to date, there has been limited work done in Alaska to assess if changes in slope stability are occurring. To address this issue, we used 30-m Landsat imagery acquired from 1984 to 2016 to establish an inventory of 24 rock avalanches in a 5000-km2 area of Glacier Bay National Park and Preserve in southeast Alaska. A search of available earthquake catalogs revealed that none of the avalanches were triggered by earthquakes. Analyses of rock-avalanche magnitude, mobility, and frequency reveal a cluster of large (areas ranging from 5.5 to 22.2 km2), highly mobile (height/length < 0.3) rock avalanches that occurred from June 2012 through June 2016 (near the end of the 33-year period of record). These rock avalanches began about 2 years after the long-term trend in mean annual maximum air temperature may have exceeded 0 °C. Possibly more important, most of these rock avalanches occurred during a multiple-year period of record-breaking warm winter and spring air temperatures. These observations suggested to us that rock avalanches in the study area may be becoming larger because of rock-permafrost degradation. However, other factors, such as accumulating elastic strain, glacial thinning, and increased precipitation, may also play an important role in preconditioning slopes for failure during periods of warm temperatures.
KeywordsClimate change Rock avalanche Landsat Alaska Air temperature Glacier Permafrost Mobility Magnitude Frequency Probability Landslide Hazard Elastic strain
The effects of climate change have the potential to impact slope stability (e.g., Sidle and Burt 2009; Crozier 2010; Gariano and Guzzetti 2016). Adverse impacts are expected to be greatest at high altitudes and 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 (and therefore less protection for coastal bluffs from waves and currents) are likely to increase the susceptibility of slopes to landslides (e.g., Haeberli and Beniston 1998; Gruber and Haeberli 2007; Coe and Godt 2012; Huggel et al. 2012; Geertsema et al. 2013; Deline et al. 2015a; Cloutier et al. 2016). In the USA, the greatest increases in air temperature and precipitation from climate change (e.g., van Oldenborgh et al. 2013; Walsh et al. 2014; Wuebbles et al. 2014), and thus the most dramatic adverse impacts to slope stability, are expected in Alaska (Coe 2016). But, to date, conclusive evidence of changes in the frequency, magnitude, or mobility of landslides in Alaska has been elusive (e.g., Huggel et al. 2012). This situation is due, at least in part, to a paucity of systematic records on historical landslides that can be compared to data from new landslides, which is a problem in alpine and glacial environments in many parts of the world (e.g., Schneider et al. 2011; Wood et al. 2015).
In this paper, we analyze and assess our rock-avalanche inventory (Bessette-Kirton and Coe 2016) for changes in frequency, magnitude, and mobility over the 33-year period of record. Because the Glacier Bay area is tectonically active (e.g., Elliott et al. 2010), and earthquakes can trigger rock avalanches (e.g., McSaveney 1978; Jibson et al. 2006), part of our work focused on searching available historical earthquake catalogs to determine if any of the rock avalanches in our inventory were triggered by earthquakes. The discussion section of this paper presents some possible reasons for the pattern of observed changes. This paper expands on a preliminary analysis of the rock-avalanche inventory contained in Coe et al. (2017).
The study area is a glaciated peninsula located along the transform boundary of the Pacific and North American plates. The plate boundary is marked by the strike-slip Fairweather fault (Pflaker et al. 1978, Fig. 1) which accommodates a large portion of the relative motion between the plates through dextral slip of about ~ 43 mm/year (Elliott et al. 2010). Elevations in the area range from sea level up to 4670 m at Mount Fairweather at the US/Canadian border (Fig. 1). Much of the study area is covered by ice, either in the form of valley glaciers or from the Brady ice field. In the last 250 years, the area has been undergoing rapid uplift (up to 30 mm/year) caused primarily by viscoelastic rebound from post-Little Ice Age (LIA) deglaciation (Larsen et al. 2005). Glacier Bay proper (a fjord, Fig. 1) is a result of post-LIA deglaciation (e.g., Connor et al. 2009).
Rock slides and rock avalanches in Alaska have long been of interest to scientists and land managers because of their ability to cause glaciers to advance (e.g., Field 1968; McSaveney 1975) and generate hazardous tsunamis (e.g., Petley 2016b). In the Glacier Bay region, a large, earthquake-triggered rock slide in 1958 entered Lituya Bay on the west side of the study area (Fig. 1) and produced a tsunami that killed two people (Miller 1960). At Tidal Inlet, just outside the study area to the east (Fig. 1), a large active rock slide has the potential to generate waves greater than 10 m in the western arm of Glacier Bay near the mouth of Tidal Inlet (Wieczorek et al. 2007). Within the last 5 years, documentation of rock avalanches has begun because of potential links to climate change (e.g., Geertsema 2012; Geertsema et al. 2013).
For our inventory mapping, we used Landsat imagery available from the U.S. Geological Survey (USGS) EarthExplorer website (USGS 2017a). Specifically, we used short-wave infrared bands (band 5, Landsat 5 and 7, and band 6, Landsat 8) for mapping (Bessette-Kirton and Coe 2016) because short-wave infrared wavelengths penetrate thin clouds and discriminate changes in ground moisture content (see USGS 2017b). We found that the short-wave infrared bands were most effective for identifying rock avalanches on glaciated terrain in the oceanic climate of southeast Alaska. Individual short-wave infrared band images and multiband false-color images were used to identify and delineate rock avalanches. Band combinations 453 (Landsat 5/7) and 564 (Landsat 8) were found to be most effective for differentiating between snow/ice and bare ground.
Rock-avalanche data from Bessette-Kirton and Coe (2016), listed from oldest to youngest. Rock avalanche #5 is the Lituya Mountain avalanche (Geertsema 2012), avalanche #3 is the Mount La Perouse avalanche (Petley 2014), and avalanche # 20 is the Lamplugh Glacier avalanche (Petley 2016a; Bessette-Kirton 2017). All rock avalanches terminated on glaciers. Aspect for each rock avalanche was measured from a single 5-m DEM cell and may or may not be reflective of the overall rock-avalanche travel direction
Range in possible dates of occurrence, or exact date if available (month/day/year)
Rock-avalanche ID number
Latitude/longitude at the center of head scarp
Total area (km2, including scar, travel path, and deposit)
Aspect (slope direction) at point of maximum elevation near center of head scarp (degrees)
58°49′22.99″N, 137° 30′ 40.43″ W
58° 53′ 17.42″ N, 137° 35′ 56.11″ W
58° 49′ 23.33″ N, 137° 30′ 39.69″ W
58° 47′ 25.32″ N, 137° 21′ 29.15″ W
58° 38′ 49.07″ N, 137° 4′ 50.08″ W
58° 49′ 22.43″ N, 137° 16′ 37.11″ W
58° 44′ 40.64″ N, 137° 22′ 22.60″ W
58° 38′ 35.38″ N, 137° 6′ 0.82″ W
58° 57′ 9.48″ N, 137° 12′ 24.92″ W
58° 47′ 27.76″ N, 137° 21′ 7.06″ W
58° 51′ 36.87″ N, 136° 59′ 21.81″ W
58° 51′ 47.72″ N, 137° 11′ 44.99″ W
58° 57′ 37.33″ N, 137° 2′ 10.27″ W
58° 38′ 51.10″ N, 137° 4′ 52.47″ W
58° 47′ 37.52″ N, 137° 26′ 34.60″ W
58° 47′ 26.20″ N, 137° 21′ 10.24″ W
58° 33′ 40.81″ N, 137° 4′ 24.19″ W
58° 44′ 49.26″ N, 137° 17′ 45.71″ W
58° 36′ 47.18″ N, 137° 16′ 15.69″ W
58° 36′ 47.38″ N, 137° 16′ 15.83″ W
58° 50′ 22.05″ N, 137° 21′ 26.33″ W
58° 51′ 26.37″ N, 137° 14′ 48.23″ W
58° 37′ 52.53″ N, 137° 1′ 30.36″ W
58°43′ 53.21″ N, 136°53′ 35.95″ W
Our inventory may not record all of the rock avalanches that have occurred since 1984. We make this statement because it is possible that snow and/or cloud cover prevented us from identifying and mapping some small (~< 0.5 km2) rock avalanches, especially those that might have occurred in winter months at elevations above the snowline. We are reasonably confident that we did not miss rock avalanches larger than ~ 0.5 km2 because deposits from those rock avalanches are visible in Landsat images for multiple years after they occur. Additionally, in several cases (as noted in Bessette-Kirton and Coe 2016), rock-avalanche head scarps were not clearly visible in the imagery because of shadowing, or a lack of contrast between ground disturbed by the rock avalanche, and undisturbed snow/ice or bare rock. In these cases, the head scarp location was approximated based on the source area topography in the 5-m DEM.
As estimates of magnitude and mobility are needed for hazard and risk assessments, we used our inventory, and the methods described in Coe et al. (2004), to estimate the annual exceedance probabilities for specific magnitude and mobility values. These estimates provide initial magnitude/frequency and mobility/frequency relations for the study area. However, because our inventory is likely a minimum record, our estimated recurrence intervals are probably too large and our annual exceedance probabilities are probably too small.
To illustrate the impact that the last cluster (cluster 3, ongoing) of large, highly mobile rock avalanches has had on hazard estimates in the study area, we established two sets of magnitude/frequency and mobility/frequency relations. The first set (Fig. 7d, e) is based on all of the data in the 33-year period, and the second set (Fig. 7d, e) is based only on data from the 28-year period prior to the start of the last cluster (i.e., June 11, 2012). The difference in the magnitude/frequency relations for the two periods of record indicates that annual probability of exceeding various avalanche sizes has increased between 3 and 14% (Fig. 7d). For example, the annual probability of having an avalanche larger than 1 km2 increased from 13% for the 28-year period of record to 24% for the 33-year period of record. The differences in mobility/frequency relations for the two periods indicate that the annual probability of having mobility values from 0.2 to 0.7 (lower H/L values indicate higher mobility) has increased between 15 and 17% (Fig. 7e). These estimates of probability may be overly influenced by clustering that distorts the record because the record length is relatively short. Continued systematic inventory mapping in the study area is needed to fully understand the significance of clustering. However, with the data that we currently have available, rock avalanches in the third cluster are clearly unusual because of their large size and low H/L values.
Comparison to other historical rock avalanches on glaciers
Data for other historical rock avalanches within the study area. We presume that these rock avalanches were not triggered by earthquakes because the original sources do not identify earthquake triggers. No data are available for cells that are blank
Volume (× 106 m3)
Height (H, m)
Length (L, m)
Evans and Clague (1999)
N58° 47′/W137° 10′
N58° 56′/W137° 13′
N58° 53′/W137° 40′
WSW, aspect of source area was ~ 260°
In comparison to the worldwide data set of 56 rock avalanches compiled by Deline et al. (2015b), the Lamplugh Glacier rock avalanche ranks first in area and tied for the fourth smallest H/L. This statement is qualified by the fact that the Deline et al. (2015b) compilation includes some of the rock avalanches from publications described in the previous two paragraphs, includes 21 rock avalanches without documented areas, and gives area as the surface area of the deposits only. Our area for the Lamplugh Glacier rock avalanche (22.19 km2) includes both the source (~ 1 km2) and deposit (~ 21 km2) areas. The 1970 Nevados Huascarán rock avalanche in Peru had a similar area (22.00 km2) to the Lamplugh Glacier rock avalanche. The next largest rock avalanche listed by Deline et al. (2015b) is the 10.21-km2 (deposit only) McGinnis Glacier North rock avalanche of Jibson et al. (2006). In terms of H/L values, the 1967 Steinholtsjokull Glacier rock avalanche in Iceland and the 2002 Kolka-Karmadon rock avalanche in Russia had H/L values smaller than the Lamplugh Glacier rock avalanche.
Our results indicate that the probability of large (> 5 km2), highly mobile (H/L < 0.3) rock avalanches has increased in the Glacier Bay study area since June, 2012. The question is: why did large rock avalanches become more common? An additional, related question is: what factor or factors controlled the timing of rock-avalanche clusters? Because we have excluded earthquakes as the cause of any rock avalanches in our inventory, an exploration of other factors that could induce changes in the effective stress in rock outcrops in glaciated environments is needed. Four possible factors include debuttressing of rock slopes from thinning of glaciers, increased precipitation, changes in regional crustal strain, and degradation of rock permafrost.
A recent analysis of glacial thinning in Glacier Bay National Park indicates that thinning between 1995 and 2011 was most pronounced in glacial ablation zones and near glacier termini (Loso et al. 2014) at elevations lower than our rock-avalanche source areas. Additionally, a longer-term study of glacier surface elevation changes from 1948 to 2000 showed both increases and decreases in elevation (from ~− 2 to ~+ 2 m) in accumulation zones near rock-avalanche source areas (Larsen et al., 2007), which suggests to us that changes in snowfall and glacier thicknesses were probably not factors that influenced the timing or size of rock avalanches. Recent work on the Brady Glacier in the southeastern part of the study area indicated that average glacier equilibrium-line altitude measured from 2003 to 2011 (745 m) was about 145 m higher than for measurement periods from 1961 to 1962 and 1976 to 1984 (~ 600 m, Pelto et al. 2013), which suggests increasing air temperatures at progressively higher elevations.
In regard to the possible influence of changing regional crustal strain on rock-avalanche occurrence, McSaveney et al. (2015) hypothesized that an observed increase in rock-avalanche frequency in the Southern Alps of New Zealand correlates with elastic strain that has been accumulating in the crust since the last great earthquake. The hypothesis is that relatively loose, fractured rock near the surface is breaking off (as rock avalanches) more frequently because the fit with underlying rock is becoming progressively worse as elastic strain accumulates in the crust. In the Glacier Bay region, with ongoing post-LIA uplift and regional-tectonic strain, elastic strain is undoubtedly accumulating. However, two characteristics of our rock avalanches do not fit well with accumulating elastic strain being the primary control on rock-avalanche occurrence. Specifically, the north to northeast slope aspects of 75% of rock-avalanche source areas, and the predominant spring and summer dates of occurrence (see Table 1), do not fit well with the accumulating strain hypothesis of McSaveney et al. (2015). We would expect both of these characteristics to be more broadly distributed if rock-avalanche occurrence was primarily controlled by accumulating strain. Regarding the apparent strong seasonal control on rock-avalanche occurrence, we acknowledge that this observation may be biased because we may be missing small rock avalanches that occurred in the fall and winter seasons, and we may have misdated a few large avalanches that occurred in the fall and winter because they became snow-covered and were not identified until spring and summer when the snow melted off them. Accumulating elastic strain is likely a conditioning factor that weakens rock masses in the Glacier Bay region, but a different factor probably controls the timing and size of rock avalanches.
We hypothesize that degradation of rock permafrost is the primary factor that controlled the timing and size of rock avalanches in the Glacier Bay region. Existing literature on this topic highlights permafrost degradation caused by warming air temperatures as the most likely cause of changes in rock-avalanche and rock-fall activity in many areas of the world (e.g., Schär et al. 2004; Geertsema et al. 2006; Harris et al. 2009; Deline et al. 2011; Ravanel and Deline 2011; Fischer et al. 2013), but attributing specific events to permafrost degradation is difficult, especially without monitoring data at the precise locations of rock-slope failures (Allen et al. 2011; Huggel et al. 2012). Even so, recent work on the degradation of soil permafrost in Alaska suggests that the areal extent of near-surface permafrost will decline by 16 to 24% by the end of the twenty-first century (Jafarov et al. 2012; Pastick et al. 2015).
Gaining a better understanding of the processes by which permafrost in steep-rock slopes degrades and leads to rock failures is a topic of current research (e.g., Hasler et al. 2012; Krautblatter et al. 2012). Existing work indicates that subsurface conduction and advection of heat can degrade permafrost in rock (e.g., Gruber and Haeberli 2007; Noetzli and Gruber 2009). In particular, advection through the movement of water in fractures can create pathways where deep (tens of meters) thawing can occur along fractures leading to an increase in effective stress, a reduction in rock-mass strength, and destabilization of large volumes of rock (e.g., Gruber and Haeberli 2007; Fischer et al. 2010; Hasler et al. 2011). Within this context, our observation that rock avalanches preferentially initiated from north- to northeast-facing slopes (Fig. 6b) was unexpected. Work by Gruber et al. (2004) suggests that slopes with these aspects likely have a larger extent of rock permafrost (compared to south-facing slopes) and may be preferentially susceptible to failure during warm months of the year. Gruber et al. (2004) found that north-facing slopes in the European Alps experienced a greater number of rock failures than south-facing slopes during the summer of the 2003 heat wave. They attributed this observation to south-facing slopes regularly experiencing larger subsurface temperature fluctuations than north-facing slopes. Thus, the anomalously warm air temperatures of 2003 did not impact them as much as north-facing slopes, which had more extensive rock permafrost and were not calibrated to anomalously warm air temperatures. Indeed, in our study area, an examination of the dates of occurrence in Table 1 suggests that rock avalanches may predominantly occur during the spring and summer months.
There are no monitoring sites where rock temperatures and hydrologic conditions are being recorded in our study area. We therefore have to extrapolate from available air temperature data to make interpretations. Permafrost degradation is highly sensitive to air temperature (e.g., Deline et al. 2015a), and there has been some previous success in identifying air temperature patterns prior to large rock avalanches in Alaska and the European Alps (Huggel et al. 2010). Huggel et al. (2010) found that there were unusually warm temperatures (well above freezing and up to 8.5 °C above long-term average temperatures) in the weeks or days before avalanches, and that prior to some of the slope failures, there were sudden drops in temperature (usually below freezing) after warm periods in the hours to days before the avalanches.
In the vicinity of our study area, there are few meteorological stations, and those that do exist tend to have relatively short periods of record and are located at elevations at or near sea level. In contrast to the elevations of these stations, the mean elevation of the head scarps of the rock avalanches in our inventory (see data in Bessette-Kirton and Coe 2016) is 1968 m asl. Given this situation, we analyzed meteorological data from two National Atmospheric and Oceanic Administration (NOAA) stations that have relatively long periods of records and relatively close proximity to our study area. The two stations were the Glacier Bay station (station ID: COOP 503294) near Gustavus (Fig. 1) and the Juneau International Airport station (station ID: COOP 504100), respectively, located about 75 and 150 km southeast of the center of the study area. The Glacier Bay station is at an elevation of 4.2 m asl and has a record from 1966 to 2016. But the data are incomplete with about 35 years missing from the annual temperature summary records provided by the National Climatic Data Center (NCDC). The Juneau station is at an elevation of 1.5 m and has records from 1942 to 2016. Data from the Juneau station are more complete than Glacier Bay, with only 8 years missing from annual summary data.
At the Glacier Bay station, the climatic pattern is similar to Juneau (Fig. 10c, d), with one important exception. At Glacier Bay, the MAMT trendline for data projected to 1968 m asl exceeded 0 °C in about 2010. The exceptionally large rock avalanches began in 2012 with Lituya Mountain (Table 1, Fig. 7, the third cluster of activity in Fig. 7a). Of course, the sparseness and projection (to an elevation of 1968 m) of the data from the Glacier Bay station make the position and slope of the trendline, and the timing of the 0 °C crossover, inexact and conjectural. Even so, existing literature (e.g., Davies et al. 2001; Krautblatter et al. 2013) indicates that strength of ice in rock can decrease with warming between rock temperatures of − 5 and 0 °C. Therefore, the established warming trends in this area of Alaska are likely more important than the position and timing of maximum air temperatures rising above 0 °C.
Some additional climatological data for the study area are available from the North American Freezing Level Tracker (NAFLT), which was developed by the Western Regional Climate Center (WRCC) and provides historical data on the elevation of the freezing level (0 °C) in North America (see data at WRCC 2017). NAFLT identifies the elevation at which 0 °C is first encountered when progressing downwards from the upper atmosphere. Air temperatures are taken from mean daily temperature profiles derived from four, 6-h temperature averages from a National Centers for Environmental Protection (NCEP)/National Center for Atmospheric Research (NCAR) Global Reanalysis product (Kistler et al. 2001) with a grid spacing of 2.5° and data availability from 1948 to present. Freezing elevations at specific geographic locations are interpolated from the 2.5° grid. Average elevations of freezing levels for varying lengths of time can be computed and compared to a long-term mean value.
Figure 11 also reveals that, beginning in 1980, there are a greater number of years (21 of 37, 57%) with January elevations above average compared to years with January elevations below average (16 of 37, 43%). This pattern does not exist for post-1980 July elevations where the number of years with freezing elevations above and below average is nearly evenly split (18 above average, 19 below average). Additionally, the freezing elevation for January 2014 (the approximate center of the third cluster) is the highest on record. Also, the only two periods with five consecutive years of above average freezing elevations correspond with the first (1984–1986) and the last (2012–2016) rock-avalanche clusters. These results suggest to us that the timing of rock-avalanche clusters, and the increase in rock-avalanche magnitude and mobility, is determined more by winter temperatures than by summer temperatures. Presumably, warmer than normal winter temperatures weaken rock masses that then fail when temperatures approach or exceed 0 °C in the late spring and summer.
These results fit with existing literature that indicates that trends in air temperature increases in Alaska are more pronounced in winter (Arendt et al. 2009; Wendler and Shulski 2009). In regard to the third rock-avalanche cluster from 2012 to 2016, the US 2016 annual climate report (NOAA 2017) states that each of the 3 years from 2014 to 2016 were the three warmest on record for the State of Alaska, with 2016 being the warmest, 2014 the second warmest, and 2015 tied for third place (with 2002). The average winter temperature for Alaska for the December 2015 to February 2016 period was 10.6 °F (5.94 °C) above average and set a new record (NOAA 2017). Walsh et al. (2017) note that the exceptional warmth in the 2015/2016 winter was most pronounced for the January through April time period. The record-breaking, multiyear and winter-season warmth is the most likely explanation for increase in rock-avalanche size in the third cluster. Given that these recent large rock avalanches likely have deep (> 10 m) failure surfaces (e.g., see volume estimates for the Lituya Mountain and Lamplugh rock avalanches in Geertsema (2012) and Bessette-Kirton (2017), respectively), prolonged warming may be needed for the transmission of heat and/or water to the depth of the failure surfaces. This statement is supported by Krautblatter et al. (2013) who proposed a conceptual model based on experimental results which suggests that rock-mass strength decreases as rock-permafrost slopes warm and that these changes can occur over time frames from months to millennia. Regardless of our imprecise understanding of the exact processes responsible for rock-slope failures due to warming temperatures, the observed increase in large, highly mobile rock avalanches in the Glacier Bay study area indicates that a critical temperature threshold was most likely exceeded, at least for the third cluster from 2012 to 2016.
Our interpretation is that the third rock-avalanche cluster was primarily caused by rock-permafrost degradation from the cumulative effect of long-term warming and the prolonged, record-breaking warmth of 2014–2016. We recognize and acknowledge, however, that accumulating elastic strain, glacial thinning, and increased precipitation could be contributing factors that conditioned the slopes for failure. An application of the principle of Occam’s razor, which asserts that the simplest explanation for a phenomenon is more likely to be accurate than more complicated explanations, suggests that these rising and record-breaking temperatures should be considered the primary driving force for the observed increases in rock-avalanche size and mobility in the Glacier Bay region. Even so, continued monitoring of rock-avalanche activity in the study area should be done to critically assess the long-term reliability of the interpretations and conclusions from this study.
Our study of 24 rock avalanches which occurred in the western part of Glacier Bay National Park and Preserve between 1984 and 2016 indicates that the probability of occurrence of large (areas > 5 km2), highly mobile (H/L < 0.3) rock avalanches has increased by at least a factor of 2 in the last 5 years (2012–2016). These large rock avalanches began to occur approximately 2 years after the long-term trend in mean annual maximum air temperature is thought to have exceeded 0 °C. Possibly more important, however, most of these large rock avalanches occurred during a multiple-year period of record-breaking winter and spring air temperatures. We suggest that large rock avalanches in the study area may have been caused by rock-permafrost degradation. However, we recognize that other factors, such as accumulating elastic strain, glacial thinning, and increased precipitation, may also play an important role in preconditioning the slopes for failure during warm temperatures.
The observations and results presented here provide baseline information on rock-avalanche characteristics that can be compared to future avalanche characteristics. Rock-avalanche activity in the study area should continue to be monitored to critically assess the long-term reliability of the interpretations and conclusions from this study. We acknowledge that the mapped rock-avalanche polygons that form the basis of this paper may be different, and less accurate, than polygons that could be mapped from higher-resolution satellite, aerial, and handheld imagery. We specifically chose not to use the highest-resolution imagery because we desired a long-term inventory that was unbiased by increasing image resolution. New mapping could create an inventory that fully utilizes recently available high-resolution imagery.
We thank Mauri McSaveney, Dennis Staley, Rex Baum, and an anonymous reviewers for their critical reviews of this paper. Douglas Sprinkel and Patrick Burkhart reviewed a preliminary version of this paper and Janet Slate provided helpful editorial suggestions. The U.S. Geological Survey Landslide Hazards Program provided support for this research. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
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