Title: Snow and Avalanche Science - Highlights of applied avalanche research and forecasting
Remote Sensing Tools Advance Avalanche Research Active
The USGS Snow and Avalanche Project (SNAP) uses remotely sensed technologies to understand snowpack changes that influence water storage, recreation, avalanche hazard and acts as a driver of landscape change. Satellites, uninhabited aerial systems (UAS), and structure-from-motion (SfM) photogrammetry are some of the tools scientists use to collect high resolution imagery that supports ongoing snow science research and provides practical new tools that advance avalanche forecasting and benefit resource management.
Remote Sensing Provides New Perspective
Scientists from diverse disciplines utilize remote sensing tools to provide a birds-eye view of the landscape and efficiently collect valuable high resolution data. For snow scientists and avalanche forecasters, knowing the distribution of snow across the landscape in relation to weather events is critically important, but challenging to obtain due to complex terrain, inherent risks, and spatial limitations. Remote sensing tools provide comprehensive data and a safer alternative to collecting snow depth and distribution information over a variety of spatial scales. The USGS Snow and Avalanche Project (SNAP) employs a variety of remote sensing techniques to support studies that focus on how avalanches act as both a hazard and a driver of landscape change. Ongoing research include these remote sensed applications:
- Uninhabited Aerial Systems (UAS), commonly known as “drones,” are used to photograph complex mountain terrain as the first step in creating high resolution maps of snow surface elevation. A map of snow depth is created by comparing the snow surface elevation at different times, known as “differencing.” Data collected this way in short intervals, such as before and after storm or wind events, provides avalanche specialists with detailed snow depth information critical for avalanche forecasting. At longer intervals and larger spatial scales, such as over a winter season in a mountain range, differencing maps created from UAS provides resource managers with detailed estimates of landscape scale snowpack as an indicator of water storage and flood risk. Scientists also use UAS to capture imagery of the spatial extent of avalanche activity over a given area.
- Structure from Motion (SfM) Photogrammetry is a method that approximates three dimensional structure from high resolution photography and location information to create digital elevation or surface models. Images captured by UAS are processed using SfM to provide scientists with high spatial resolution mapping of complex terrain to study snow distribution and avalanche processes.
- Lidar which stands for Light Detection and Ranging, is a technique that uses a pulsed laser to measure distances to create high resolution three dimensional elevation maps to compare snow depth change and detailed vegetation mapping in avalanche paths to assess changes in vegetation associated with different avalanche occurrence intervals.
- Satellite imagery, which now spans decades, provides scientists with a record of landscape change. USGS scientists evaluate the efficacy of using satellite imagery to create a regional chronology of avalanche disturbance to complement research on avalanche frequency and magnitude. The use of pattern recognition techniques applied to remotely sensed products can be used to examine changes in vegetation within and around avalanche paths to provide a measure of avalanche frequency.
The application of these technologies to snow science provides researchers with spatial data at multiple scales, from a single slope or known hazard zone, to a full watershed scale where snowpack data are used in regional hydrologic analyses. Scientists working on the USGS SNAP continue to explore innovative ways to use these rich sources of data to expand the understanding of snow on the landscape and advance avalanche forecasting.
Additional Resources:
Below are other science projects associated with this project.
Science in Glacier National Park
Going-to-the-Sun Road Avalanche Forecasting Program
Snow and Avalanche Research
Below are data or web applications associated with this project.
2020 winter timeseries of UAS derived digital surface models (DSMs) from the Hourglass study site, Bridger Mountains, Montana, USA
Avalanche occurrence records along the Going-to-the-Sun Road, Glacier National Park, Montana from 2003-2023 (ver. 3.0, July 2023)
Tree ring dataset for a regional avalanche chronology in northwest Montana, 1636-2017
Below are multimedia items associated with this project.
Title: Snow and Avalanche Science - Highlights of applied avalanche research and forecasting
Below are publications associated with this project.
Climate drivers of large magnitude snow avalanche years in the U.S. northern Rocky Mountains
A regional spatio-temporal analysis of large magnitude snow avalanches using tree rings
Research Note: How old are the people who die in avalanches? A look into the ages of avalanche victims in the United States (1950-2018)
Detecting snow depth change in avalanche path starting zones using uninhabited aerial systems and structure from motion photogrammetry
Identifying major avalanche years from a regional tree-ring based avalanche chronology for the U.S. Northern Rocky Mountains
On the exchange of sensible and latent heat between the atmosphere and melting snow
Case study: 2016 Natural glide and wet slab avalanche cycle, Going-to-the-Sun Road, Glacier National Park, Montana, USA
Using structure from motion photogrammetry to examine glide snow avalanches
Examining spring wet slab and glide avalanche occurrence along the Going-to-the-Sun Road corridor, Glacier National Park, Montana, USA
Time lapse photography as an approach to understanding glide avalanche activity
Timing of wet snow avalanche activity: An analysis from Glacier National Park, Montana, USA.
Avalanche ecology and large magnitude avalanche events: Glacier National Park, Montana, USA
Below are news stories associated with this project.
- Overview
The USGS Snow and Avalanche Project (SNAP) uses remotely sensed technologies to understand snowpack changes that influence water storage, recreation, avalanche hazard and acts as a driver of landscape change. Satellites, uninhabited aerial systems (UAS), and structure-from-motion (SfM) photogrammetry are some of the tools scientists use to collect high resolution imagery that supports ongoing snow science research and provides practical new tools that advance avalanche forecasting and benefit resource management.
Remote Sensing Provides New Perspective
Scientists from diverse disciplines utilize remote sensing tools to provide a birds-eye view of the landscape and efficiently collect valuable high resolution data. For snow scientists and avalanche forecasters, knowing the distribution of snow across the landscape in relation to weather events is critically important, but challenging to obtain due to complex terrain, inherent risks, and spatial limitations. Remote sensing tools provide comprehensive data and a safer alternative to collecting snow depth and distribution information over a variety of spatial scales. The USGS Snow and Avalanche Project (SNAP) employs a variety of remote sensing techniques to support studies that focus on how avalanches act as both a hazard and a driver of landscape change. Ongoing research include these remote sensed applications:
- Uninhabited Aerial Systems (UAS), commonly known as “drones,” are used to photograph complex mountain terrain as the first step in creating high resolution maps of snow surface elevation. A map of snow depth is created by comparing the snow surface elevation at different times, known as “differencing.” Data collected this way in short intervals, such as before and after storm or wind events, provides avalanche specialists with detailed snow depth information critical for avalanche forecasting. At longer intervals and larger spatial scales, such as over a winter season in a mountain range, differencing maps created from UAS provides resource managers with detailed estimates of landscape scale snowpack as an indicator of water storage and flood risk. Scientists also use UAS to capture imagery of the spatial extent of avalanche activity over a given area.
- Structure from Motion (SfM) Photogrammetry is a method that approximates three dimensional structure from high resolution photography and location information to create digital elevation or surface models. Images captured by UAS are processed using SfM to provide scientists with high spatial resolution mapping of complex terrain to study snow distribution and avalanche processes.
- Lidar which stands for Light Detection and Ranging, is a technique that uses a pulsed laser to measure distances to create high resolution three dimensional elevation maps to compare snow depth change and detailed vegetation mapping in avalanche paths to assess changes in vegetation associated with different avalanche occurrence intervals.
- Satellite imagery, which now spans decades, provides scientists with a record of landscape change. USGS scientists evaluate the efficacy of using satellite imagery to create a regional chronology of avalanche disturbance to complement research on avalanche frequency and magnitude. The use of pattern recognition techniques applied to remotely sensed products can be used to examine changes in vegetation within and around avalanche paths to provide a measure of avalanche frequency.
The application of these technologies to snow science provides researchers with spatial data at multiple scales, from a single slope or known hazard zone, to a full watershed scale where snowpack data are used in regional hydrologic analyses. Scientists working on the USGS SNAP continue to explore innovative ways to use these rich sources of data to expand the understanding of snow on the landscape and advance avalanche forecasting.
Additional Resources:
- Science
Below are other science projects associated with this project.
Science in Glacier National Park
Glacier National Park (GNP) is considered a stronghold for a large diversity of plant and animal species and harbors some of the last remaining populations of threatened and endangered species such as grizzly bear and bull trout, as well as non threatened keystone species such as bighorn sheep and black bear. The mountain ecosystems of GNP that support these species are dynamic and influenced by...Going-to-the-Sun Road Avalanche Forecasting Program
As the most popular attraction in Glacier National Park (GNP), the Going-to-the-Sun Road traverses scenic alpine zones and crosses the Continental Divide at Logan Pass (2026m or 6,647' elevation). The Park closes a 56km (34.8 mile) section of the road each winter due to inclement weather, heavy snowfall, and avalanche hazards. Annual spring opening of the road is a highly anticipated event for...Snow and Avalanche Research
Snow scientists with the USGS are unraveling specific weather, climate, and snowpack factors that contribute to large magnitude avalanches in an effort to understand these events as both a hazard and a landscape–level disturbance. The Snow and Avalanche Project (SNAP) advances our understanding of avalanche-climate interactions and wet snow avalanches, and improves public safety through innovative... - Data
Below are data or web applications associated with this project.
2020 winter timeseries of UAS derived digital surface models (DSMs) from the Hourglass study site, Bridger Mountains, Montana, USA
Unmanned Aerial System (UAS) flights were conducted over the headwaters of the South Fork of Brackett Creek in the Bridger Mountains of SW Montana during the winter of 2020. The flights collected overlapping imagery focused on a steep mountain couloir study site known locally as "the Hourglass." Structure from motion (SfM) photogrammetry was used to process the collected imagery and create digitalAvalanche occurrence records along the Going-to-the-Sun Road, Glacier National Park, Montana from 2003-2023 (ver. 3.0, July 2023)
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 PTree ring dataset for a regional avalanche chronology in northwest Montana, 1636-2017
This dataset includes processed tree ring data from avalanche paths in Glacier National Park and the Flathead National Forest in northwest Montana. The data were processed in three distinct phases that resulted in this dataset: collection, processing, and avalanche signal analysis. This dataset consists of samples from 647 trees with 2304 growth disturbances identified from 12 avalanche paths. - Multimedia
Below are multimedia items associated with this project.
PubTalk 3/2018 - Snow & Avalanche ScienceTitle: Snow and Avalanche Science - Highlights of applied avalanche research and forecasting
Title: Snow and Avalanche Science - Highlights of applied avalanche research and forecasting
- Publications
Below are publications associated with this project.
Filter Total Items: 13Climate drivers of large magnitude snow avalanche years in the U.S. northern Rocky Mountains
Large magnitude snow avalanches pose a hazard to humans and infrastructure worldwide. Analyzing the spatiotemporal behavior of avalanches and the contributory climate factors is important for understanding historical variability in climate-avalanche relationships as well as improving avalanche forecasting. We used established dendrochronological methods to develop a long-term (1867–2019) regionalAuthorsErich Peitzsch, Gregory T. Pederson, Karl W. Birkeland, Jordy Hendrikx, Daniel B. FagreA regional spatio-temporal analysis of large magnitude snow avalanches using tree rings
Snow avalanches affect transportation corridors and settlements worldwide. In many mountainous regions, robust records of avalanche frequency and magnitude are sparse or non-existent. However, dendrochronological methods can be used to fill this gap and infer historical avalanche patterns. In this study, we developed a tree-ring-based avalanche chronology for large magnitude avalanche events (sizeAuthorsErich Peitzsch, Jordy Hendrikx, Daniel Kent Stahle, Gregory T. Pederson, Karl W. Birkeland, Daniel B. FagreResearch Note: How old are the people who die in avalanches? A look into the ages of avalanche victims in the United States (1950-2018)
Since the winter of 1950-1951, 1084 individuals perished in snow avalanches in the United States. In this study, we analyze the ages of those killed (n=900) by applying non-parametric methods to annual median ages and for age groups and primary activity groups. Change point detection results suggest a significant change in 1990 in the median age of avalanche fatalities. Significant positive trendsAuthorsErich Peitzsch, Sara Boilen, Karl W. Birkeland, Spencer LoganDetecting snow depth change in avalanche path starting zones using uninhabited aerial systems and structure from motion photogrammetry
Understanding snow depth distribution and change is useful for avalanche forecasting and mitigation, runoff forecasting, and infrastructure planning. Advances in remote sensing are improving the ability to collect snow depth measurements. The development of structure from motion (SfM), a photogrammetry technique, combined with the use of uninhabited aerial systems (UASs) allows for high resolutionAuthorsErich H. Peitzsch, Daniel B. Fagre, Jordy Hendrikx, Karl W. BirkelandIdentifying major avalanche years from a regional tree-ring based avalanche chronology for the U.S. Northern Rocky Mountains
Avalanches not only pose a major hazard to people and infrastructure, but also act as an important ecological disturbance. In many mountainous regions in North America, including areas with existing transportation corridors, reliable and consistent avalanche records are sparse or non-existent. Thus, inferring long-term avalanche patterns and associated contributory climate and weather factors reAuthorsErich H. Peitzsch, Daniel B. Fagre, Gregory T. Pederson, Jordy Hendrikx, Karl W. Birkeland, Daniel StahleOn the exchange of sensible and latent heat between the atmosphere and melting snow
The snow energy balance is difficult to measure during the snowmelt period, yet critical for predictions of water yield in regions characterized by snow cover. Robust simplifications of the snowmelt energy balance can aid our understanding of water resources in a changing climate. Research to date has demonstrated that the net turbulent flux (FT) between a melting snowpack and the atmosphere is neAuthorsPaul C. Stoy, Erich H. Peitzsch, David J. A. Wood, Daniel Rottinghaus, Georg Wohlfahrt, Michael Goulden, Helen WardCase study: 2016 Natural glide and wet slab avalanche cycle, Going-to-the-Sun Road, Glacier National Park, Montana, USA
The Going-to-the-Sun Road (GTSR) is the premier tourist attraction in Glacier National Park, Montana. The GTSR also traverses through and under 40 avalanche paths which pose a hazard to National Park Service (NPS) road crews during the annual spring snow plowing operation. Through a joint collaboration between the NPS and the U.S. Geological Survey (USGS), a forecasting program primarily dealing wAuthorsJacob Hutchinson, Erich H. Peitzsch, Adam ClarkUsing structure from motion photogrammetry to examine glide snow avalanches
Structure from Motion (SfM), a photogrammetric technique, has been used extensively and successfully in many fields including geosciences over the past few years to create 3D models and high resolution digital elevation models (DEMs) from aerial or oblique photographs. SfM has recently been used in a limited capacity in snow avalanche research and shows promise as a tool for broader applications.AuthorsErich H. Peitzsch, Jordy Hendrikx, Daniel B. FagreExamining spring wet slab and glide avalanche occurrence along the Going-to-the-Sun Road corridor, Glacier National Park, Montana, USA
Wet slab and glide snow avalanches are dangerous and yet can be particularly difficult to predict. Wet slab and glide avalanches are presumably triggered by free water moving through the snowpack and the subsequent interaction with layer or ground interfaces, and typically occur in the spring during warming and subsequent melt periods. In Glacier National Park (GNP), Montana, both types of avalancAuthorsErich H. Peitzsch, Jordy Hendrikx, Daniel B. Fagre, Blase ReardonTime lapse photography as an approach to understanding glide avalanche activity
Avalanches resulting from glide cracks are notoriously difficult to forecast, but are a recurring problem for numerous avalanche forecasting programs. In some cases glide cracks are observed to open and then melt away in situ. In other cases, they open and then fail catastrophically as large, full-depth avalanches. Our understanding and management of these phenomena are currently limited. It is thAuthorsJordy Hendrikx, Erich H. Peitzsch, Daniel B. FagreTiming of wet snow avalanche activity: An analysis from Glacier National Park, Montana, USA.
Wet snow avalanches pose a problem for annual spring road opening operations along the Going-to-the-Sun Road (GTSR) in Glacier National Park, Montana, USA. A suite of meteorological metrics and snow observations has been used to forecast for wet slab and glide avalanche activity. However, the timing of spring wet slab and glide avalanches is a difficult process to forecast and requires new capabilAuthorsErich H. Peitzsch, Jordy Hendrikx, Daniel B. FagreAvalanche ecology and large magnitude avalanche events: Glacier National Park, Montana, USA
Large magnitude snow avalanches play an important role ecologically in terms of wildlife habitat, vegetation diversity, and sediment transport within a watershed. Ecological effects from these infrequent avalanches can last for decades. Understanding the frequency of such large magnitude avalanches is also critical to avalanche forecasting for the Going-to-the-Sun Road (GTSR). In January 2009, a lAuthorsDaniel B. Fagre, Erich H. Peitzsch - News
Below are news stories associated with this project.