Title: Snow and Avalanche Science - Highlights of applied avalanche research and forecasting
Remote Sensing Tools Advance Avalanche Research
Active
By Northern Rocky Mountain Science Center
August 17, 2021
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.
Sources/Usage: Public Domain. View Media Details
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:
Sources/Usage: Public Domain. View Media Details
- 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.
Sources/Usage: Some content may have restrictions. View Media Details
- 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.
Sources/Usage: Some content may have restrictions. View Media Details
- 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
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, yet ecologically important species such as bighorn sheep and black bear. The mountain ecosystems of GNP that support these species are dynamic...
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...
Below are multimedia items associated with this project.
PubTalk 3/2018 - Snow & Avalanche Science
Title: Snow and Avalanche Science - Highlights of applied avalanche research and forecasting
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.
Sources/Usage: Public Domain. View Media Details
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:
Sources/Usage: Public Domain. View Media Details
- 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.
Sources/Usage: Some content may have restrictions. View Media Details
- 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.
Sources/Usage: Some content may have restrictions. View Media Details
- 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
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, yet ecologically important species such as bighorn sheep and black bear. The mountain ecosystems of GNP that support these species are dynamic...
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...
Below are multimedia items associated with this project.
PubTalk 3/2018 - Snow & Avalanche Science
Title: Snow and Avalanche Science - Highlights of applied avalanche research and forecasting
Title: Snow and Avalanche Science - Highlights of applied avalanche research and forecasting