ACCEPTABLE RISK FOR BACKCOUNTRY SKIERS AND RIDERS FROM AVALANCHE HAZARDS: DIFFERENCES IN UPHILL AND DOWNHILL TERRAIN SELECTION

Similar documents
3/8/2016 Oregon Wallowa Mountains Published by Michael Hatch (Wallowa Avalanche Center) and Scott Savage (on behalf of USFS National Avalanche Center)

Avalanche Problem Essentials Wind Slabs. Development

Near Miss Avalanche Incident Jan 3 rd, 2014

TRAVEL BEHAVIOR OF LIFT ACCESS BACKCOUNTRY SKIERS ADJACENT TO BRIDGER BOWL SKI AREA, MONTANA, USA

THE EFFECTIVENESS OF BOOT PACKING FOR SNOWPACK STABILIZATION

NEAR-SURFACE FACETED CRYSTALS ON A SLOPE COVERED WITH STONE PINE TREES. Peter Höller*

Loose Dry Avalanches

Creek Trash Assessment (CTA) Methodology (Demonstration: Mill Run Creek, Cheltenham, Pa.)

Safety Assessment of Installing Traffic Signals at High-Speed Expressway Intersections

12/14/2015 Idaho Bald Mountain Sidecountry Published by Scott Savage, SAC

Alternative Impedances for Shortest Path Network Analysis for Cycling

A New Approach in the GIS Bikeshed Analysis Considering of Topography, Street Connectivity, and Energy Consumption

Using smartphones for cycle planning Authors: Norman, G. and Kesha, N January 2015

Evaluating the Influence of Development on Mule Deer Migrations

Advanced Terrain. Powder / Snow Alpine Terrain Tree Skiing Strong. Intermediate. Terrain

Compression Study: City, State. City Convention & Visitors Bureau. Prepared for

Snow Avalanches. Basic Principles for Avoiding and Surviving Snow Avalanches. By Lance Young

Colorado Mountain Club Youth Education Program

Planning Daily Work Trip under Congested Abuja Keffi Road Corridor

Morse Creek Drainage Avalanche Accident March 7, 2004

4. Identify and employ rope rescue systems.

2016/04/03 Alaska Hoodoo Mountains, Eastern Alaska Range Published by Conrad Chapman Eastern Alaska Range Avalanche Center

PEER AMBASSADORS AT WORK: MODELING GOOD DECISION-MAKING IN AGGRO FREERIDE FILMS INTERNATIONAL SNOW SCIENCE WORKSHOP 2018

GRANITE MOUNTAIN (5629 ) AVALANCHE INCIDENT March 10, Narrative provided by John Stimberis WSDOT Avalanche Technician, Snoqualmie Pass

Analysis of Run-Off-Road Crashes in Relation to Roadway Features and Driver Behavior

Walking up Scenic Hills: Towards a GIS Based Typology of Crowd Sourced Walking Routes

The Stuffblock Snow Stability Test. Contents. Publication Number: MTDC. Introduction. Snow Stability Tests and Their Limitations

from the PSIA Nordic Team February, 2014

Proceedings, International Snow Science Workshop, Innsbruck, Austria, 2018

*** FULL REPORT FROM THE WCMAC *** View report and photos online at:

KICKING HORSE MOUNTAIN RESORT APPLICATION TO AMEND THE EXISTING CONTROLLED RECREATION AREA

Investigating Commute Mode and Route Choice Variability in Jakarta using multi-day GPS Data

Active Travel and Exposure to Air Pollution: Implications for Transportation and Land Use Planning

Agriculture Zone Winter Replicate Count 2007/08

Whither the Hybrid Swarm? Stream environments segregate cutthroat and rainbow trout to control hybrid zone locations

Cross-Country Madness: Run for Your Life

Combined impacts of configurational and compositional properties of street network on vehicular flow

CROSS COURSE INSTRUCTION DOCUMENT

Over or Around? Kinetic Energy vs. Potential Energy. Critical Factors

GIS for Public Opinion / Survey Research. Timothy Michalowski Senior Statistical GIS Analyst Abt SRBI - New York, NY

Using sensory feedback to improve locomotion performance of the salamander robot in different environments

Who s at risk in the backcountry?

ALPINE LEVEL 1 CERTIFICATION PROCESS Updated August 2018

Windcube FCR measurements

Union Creek Avalanche Accident

20 -Day Alaska Mountaineering Leadership & Guide Training Course Information

TROUT CREEK WATERSHED (Second Year of Snowline Data)

AVALANCHE ACCIDENT - GLADIATOR RIDGE

Proceedings, International Snow Science Workshop, Breckenridge, Colorado, 2016 POLAR CIRCUS AVALANCHE RESPONSE, FEBRUARY 5-11, 2015

Henry s Avalanche Talk

Mt Hood Meadows Avalanche Accident

Determining the Limit Performance of a GP2 Race Car: from Reality to Multibody and Analytical Simulation - Part II.

PSY201: Chapter 5: The Normal Curve and Standard Scores

March 6, 2013 Tony Giarrusso, Rama Sivakumar Center for GIS, Georgia Institute of Technology

IPC Nordic Skiing Homologation Guide Version 2015

#19 MONITORING AND PREDICTING PEDESTRIAN BEHAVIOR USING TRAFFIC CAMERAS

Estimating Valley Confinement using DEM Data to Support Cutthroat Trout Research

World Para Nordic Skiing Homologation Guide Version 2017

Team 7416 HiMCM 2017 Page 1 of 24. Olympic ski slopes are difficult to plan, and a ranch in Utah is being evaluated to

Predicting Snow Layer Hardness with Meteorological Factors

WMS 8.4 Tutorial Hydraulics and Floodplain Modeling HY-8 Modeling Wizard Learn how to model a culvert using HY-8 and WMS

A SURVEY OF 1997 COLORADO ANGLERS AND THEIR WILLINGNESS TO PAY INCREASED LICENSE FEES

Visitor Guidelines for WPC-owned Properties. Last revised 5/20/2010

2010 International Snow Science Workshop

Appendix 22 Sea angling from a private or chartered boat

We present you golf in a way never seen before.

Proceedings, 2012 International Snow Science Workshop, Anchorage, Alaska

Centre for Transport Studies

Appendix 21 Sea angling from the shore

Dude Mountain Avalanche Accident Report Ketchikan, Southeast Alaska

Sontek RiverSurveyor Test Plan Prepared by David S. Mueller, OSW February 20, 2004

Guided Uphill Arc Blue Groomed. Carved Uphill Arc Blue Groomed. Skate on Flat Terrain Green Groomed. Vertical Side Slip Blue Groomed

USING THE MILITARY LENSATIC COMPASS

IPC Nordic Skiing Homologation Guide Version 2016

A Framework For Integrating Pedestrians into Travel Demand Models

Back to TOC. Title: Encouraging adoption of precision irrigation technology through on-course application and demonstration of water savings

The Affect of Climate Change on Winter Recreation. Presentation by Sydnie LeMieux

Sport Fishing Expenditures and Economic Impacts on Public Lands in Washington

Table 1: Original and adjusted slope gradients for each difficulty rating Traditional Ranges Adjusted Ranges

GEA FOR ADVANCED STRUCTURAL DYNAMIC ANALYSIS

USING THE MILITARY LENSATIC COMPASS

Giant Traveling Map Lesson

Sussex County, DE Preliminary Study Overview

METROPOLITAN TRANSPORTATION PLAN OUTREACH: INTERACTIVE MAP SUMMARY REPORT- 10/03/14

Butch Mountain avalanche January 29 th Synopsis

Introduction to Sugar Access. Sugar Access - Measuring Accessibility (Robert Kohler, Citilabs) Slide 1 of 21

Winter Sports (Snow)

Cyclists gaze behavior in urban space: an eye-tracking experiment on bicycle facilities.

Wind Flow Validation Summary

What s the latest research on mountain biking in protected areas?

Citizen Advisory Committee Meeting. November 15, 2011 MPRB Headquarters- 6:30-8:30 p.m.

Sublette Moose Project! 2014 Capture Report

STUDY REPORT W&AR-03 RESERVOIR TEMPERATURE MODEL ATTACHMENT B DON PEDRO RESERVOIR BATHYMETRIC STUDY REPORT

Title: Modeling Crossing Behavior of Drivers and Pedestrians at Uncontrolled Intersections and Mid-block Crossings

unsignalized signalized isolated coordinated Intersections roundabouts Highway Capacity Manual level of service control delay

International Snow Science Workshop

Forecasting High Speed Rail Ridership Using Aggregate Data:

OPERATIONAL AMV PRODUCTS DERIVED WITH METEOSAT-6 RAPID SCAN DATA. Arthur de Smet. EUMETSAT, Am Kavalleriesand 31, D Darmstadt, Germany ABSTRACT

Aspects Regarding Priority Settings in Unsignalized Intersections and the Influence on the Level of Service

Lowland Leader Award. Lowland Leader Award

Transcription:

ACCEPTABLE RISK FOR BACKCOUNTRY SKIERS AND RIDERS FROM AVALANCHE HAZARDS: DIFFERENCES IN UPHILL AND DOWNHILL TERRAIN SELECTION Aubrey D. Miller 1 *, John R. Squires 2, Lucretia E. Olson 2, and Elizabeth K. Roberts 3 1 National School of Surveying, University of Otago, Dunedin, New Zealand 2 Rocky Mountain Research Station, US Forest Service, Missoula, MT, USA 3 White River National Forest, US Forest Service, Glenwood Springs, CO, USA ABSTRACT: Backcountry skiers and riders move through terrain differently depending on whether they are traveling uphill, downhill or along rolling or flat terrain. For example, skiers often follow ridgelines or travel through denser tree cover when ascending but select more open and often steeper terrain when descending. The movement characteristics of a recreationist affects exposure to avalanche terrain hazard. Using a GPS point dataset (n=433,555 points from 687 individual tracks) of winter recreationist movement patterns from Colorado, USA, collected between 2011 and 2013, this analysis tested if it is possible to measure whether backcountry skiers and riders increased their exposure to terrainrelated avalanche risk when traveling downhill, compared with traveling uphill. In other words, was backcountry skier/rider terrain selection more conservative when ascending? GPS points were segmented into uphill/downhill using an adapted Douglas-Peucker-Ramer generalization algorithm. Physical terrain variables including elevation, slope angle, slope curvature, slope position, aspect, terrain roughness, heat loading, and percent tree canopy cover for each point were used to characterize differences between the uphill and downhill portions of the trip. As a proxy for avalanche risk from snowpack conditions, differences in the forecasted avalanche danger (from North American scale of Low to Extreme) were tested as well. Results provide practitioners and researchers with insights into terrain selection and risk exposure for non motorized-assisted backcountry skiers/riders. KEYWORDS: Terrain selection, GPS tracking, Recreation, GIS, Danger scale 1. INTRODUCTION The use of a GPS receiver to quantify winter recreationist movement patterns offers an objective record of terrain selection. It is becoming increasingly common in winter recreation studies (e.g., Bielański et al. 2018; Miller et al., 2017; Olson et al., 2017; D Antonio et al., 2010), including in studies specifically recording guided and unguided recreation in avalanche terrain (e.g., Hendrikx and Johnson, 2016; Hendrikx et al., 2015; Thumlert and Haegeli, 2018). Recreationist terrain selection is only one part of complex set of interactions between snow, weather, terrain and human factors that all together characterize avalanche hazard. However, objectively measuring how recreationists move through avalanche terrain sheds light on underlying drivers of terrain selection and help to improve our understanding of exposure to terrain-related hazards. Previous research suggests recreationists move through a landscape differently depending on * Corresponding author address: Aubrey D. Miller, University of Otago, Dunedin, New Zealand; tel: +64 03-479-7606; email: aubrey.miller@otago.ac.nz their mode of travel (Olson et al., 2017). For example snowmobilers and hybrid motorized-assisted skiers/riders penetrate much deeper into the backcountry and away from maintained roads compared with backcountry skiers/riders. And overall skiers select steeper slopes than snowmobilers (Olson et al., 2017). Research is lacking on differences in recreation movement patterns within one mode of travel. Field observation suggests backcountry skiers/riders move through a landscape differently depending on whether they are traveling uphill or downhill. For instance, in steep mountainous terrain, skiers/riders will often lay in a skin track up ridge features and ski down open slopes or slide paths (see Figure 1, for example). But these observations remain largely untested. Here we use common terrain variables such as elevation, slope angle, slope curvature, tree cover and aspect fundamentals to the Avalanche Terrain Exposure Scale (Statham et al., 2006; Thumlert and Haegeli, 2018) in addition to terrain variables more common in ecological research, including slope position, heat load index and terrain roughness to quantify differences in uphill vs. downhill terrain selection among skiers/riders. Since exposure is related to time spent in avalanche terrain, we also approximate the differences in time spent moving uphill vs. moving 1664

downhill in the steepest terrain used by backcountry skiers/riders sampled in the study. Figure 1: Example of skier/rider GPS locations segmented by downhill (blue) and uphill (orange) portions of trip. 2. METHODS For this analysis, we used recreation data that were captured between 2011 and 2013 as part of a larger recreation and wildlife study in Colorado. Technicians approached recreationists at backcountry access portals in the San Juan range of southwest Colorado, USA (Figure 2) and asked them if they would voluntarily carry a small passive GPS device (Qstarz, model BT-Q1300, position accuracy <10m, logging frequency of 5-sec) for the trip duration. GPS units were collected from drop-boxes at the end of each day and data downloaded as point locations. Only one GPS unit was carried per group, but group size was documented for each track. For a full account of sampling methodology, see Olson et al. (2017). 2.1 Data pre-processing Data were analyzed using a combination of ArcGIS Desktop and Python scripts. For this analysis, a total of 433,555 points (from 687 individual skier/rider tracks) were segmented into uphill and downhill portions of the backcountry tour. Points were then assigned physical terrain variables based on their location, from a 10m DEM (USGS NED), which included elevation, slope angle, down-slope and across-slope curvature, slope position (from Evans et al. (2014) terrain position index at a local 30m and a medium 125m scale), terrain roughness, aspect (linearized for analysis into measures of eastness and northness), heat loading (a folded aspect by McCune (2007) where high values are steeper southwesterly sunny aspects, and low values are darker northeasterly aspects) and percent tree canopy cover from the 30m national land cover database (Homer et al., 2015). Points were also assigned the forecasted danger rating (North American Scale: Low (1) to Extreme (5)) for the day the point was recorded and for the combination of aspect and elevation for the location of the point from the avalanche forecast released by the Colorado Avalanche Information Center (CAIC). 2.2 Segmentation algorithm We used an adapted Douglas-Peucker-Ramer algorithm to segment the points into their uphill and downhill portions. The original algorithm introduced independently by Ramer (1972) and Douglas and Peucker (1973) was used for 2D line generalization on the x and y coordinates of vertices along the line. Here, we adapt it for 3D usage by applying the accumulated xy inter-point distance of all points along a track to the algorithm s x coordinate and the elevation of the point to the algorithm s y coordinate. The iterative algorithm identifies transition points where elevation change along the track reverses (from uphill to downhill and vice versa) if a user-input threshold elevation is exceeded, allowing segmentation of all points along a track as either uphill or downhill. This adapted algorithm is effective at uphill and downhill segmentation even when terrain is undulating since it looks for significant elevation changes over the track. Skiers/riders often lap terrain several times during their trip, which the algorithm also effectively captures. Figure 2 provides an overview map of the data used in analysis and examples of the segmented points. 2.3 Data analysis Once points were processed, we compared variable distributions between the uphill points and the downhill points with a one-way ANOVA (at p < 0.05). We also compared distributions on steep slopes in the 95 th percentile of slope angle distribution (Hendrikx and Johnson, 2016) and measured differences in the time spent on the uphill vs. downhill portions of the recreationist s trip. 3. RESULTS All variables had statically significant differing means, however the effect sizes were small (largest were aspect (northness) with adjusted r 2 of.013 and heat load index with adjusted r 2 of.012). Since points were recorded every five seconds when moving and skiers/riders move more slowly uphill than downhill, 67% of the points were uphill points and 32% were downhill points. In other words, skiers/riders spent on average two thirds of their moving time traveling uphill compared with one third of the time moving downhill. The mean moving speed of uphill points was 2.7kph, compared with 7.16kph for downhill points. 1665

Figure 2: Backcountry skier/rider data from San Juan range in southwest Colorado, USA segmented by downhill (blue points) and uphill (orange points) portions of trip. Top scene shows example data, bottom map shows all data used in analysis. Basemaps: Esri. Note: Scale bar in scene is linear distance at center of the scene. While there are differences in the terrain features (e.g., ridge vs. gulley) that characterize uphill vs. downhill travel, these differences are small and hard to detect since skiers/riders move through a range of terrain features throughout their trip. But when we look specifically at the points located on the steepest slopes (95th percentile of steep slope angles recorded in dataset, or slopes greater than 33.5deg), some clearer differences emerge. First, both measures of aspect and the heat load index suggest skiers/riders more often select southwesterly aspects while moving uphill vs. easterly aspects while moving downhill (Figure 3). Figure 3: Example boxplot distributions (median, 25th and 75th quartiles, range) for data from the steepest slopes (95th percentile) to highlight differences in downhill (left, blue) and uphill (right, orange) points. Clockwise from top left: Aspect, heat load index, slope angle, local and mediumscale terrain position index and percent tree canopy cover. The head load index measures a slope s angle towards the sun (high values, correspond with sunnier, southwesterly steep slopes and low values correspond with darker, north easterly steep slopes. Downhill points have a wider distribution of aspects. Also, skiers/riders moving uphill select slightly more concave features (medium-scale TPI such as ridges) but skiers/riders moving 1666

downhill cover a wider range of slope convexity/concavity. In both cases, the distributions are skewed towards more concave features at a local and medium scale-measure. Finally, there was minimal difference in the forecasted avalanche danger between uphill and downhill points when looking at all points (downhill mean of 2.4 and uphill mean of 2.42), but on the steepest slopes that spread increases. The mean forecasted danger rating was 2.35 for downhill points and 2.46 for uphill points. There were 243 individual tracks (35% of all tracks) that included points in the steepest 5% of terrain when the forecasted danger was considerable or high. 4. DISCUSSION AND FUTURE RE- SEARCH The results of this analysis highlight important differences in the ways in which skiers/riders select terrain when moving uphill compared with downhill. The differences in terrain selection are for the most part small. However, clearer differences emerge for the portions of the trip on the steepest slopes. And, the results have implications for skier/rider exposure to terrain-related avalanche hazards in the backcountry. On the steepest slopes, backcountry skiers/riders traveling downhill will select steeper, more northeasterly, and more convex slopes compared with their uphill portions of the trip. These results fit with field observations. The question of whether skiers/riders are willing to accept a higher level of risk when traveling downhill are harder to see from these results. It is important to note that 70% of the individual tracks in this analysis included points in the steepest 95% of slopes in the dataset, suggesting most skiers/riders move through a wide range of terrain. Terrain selection is more complex than can be measured by the terrain variables presented here. The availability and location of access portals to the backcountry and the presence of established skin tracks, the seasonal snowpack and the recreationist demographics and familiarity with the terrain are all important drivers to the real-time decision making of exactly where a recreationist goes in the backcountry. However this analysis provides an important, objective documentation of how skiers/riders use a landscape. Researchers and practitioners interested in improving public messaging about decision making in avalanche terrain may find these results interesting for two reasons. First, a small proportion of skiers/riders move through steep terrain even when forecasted danger is considerable or high. Accepting the limitations of the resolution of the DEM available for analysis and the accuracy of the GPS units, our data show an average moving time of more than two minutes on the steepest 5% of slopes for data from the 243 individual tracks. In other words, more than a third of skiers/riders sampled spent some time on steep slopes with considerable or high forecasted danger. More investigation is necessary to determine if there is a pattern to where these points are located. Second, while terrain variables measured here suggest that skiers/riders may select slightly more hazardous terrain when traveling downhill, this is balanced by the fact that they spend less time traveling downhill. It highlights the importance of encouraging conservative terrain selection for both downhill and uphill travel. More research is needed on exactly where recreationists are willing to accept the highest terrain-related risk. ACKNOWLEDGEMENT Thank you to the research staff who collected data and study participants who volunteered to carry a GPS unit and to Tony Moore and Greg Leonard for help adapting the Douglas-Peucker- Ramer algorithm to track segmentation. REFERENCES Bielański, M., Taczanowska, K., Muhar, A., Adamski, P., González, L.-M. and Z. Witkowski, 2018. Application of GPS tracking for monitoring spatially unconstrained outdoor recreational activities in protected areas A case study of ski touring in the Tatra National Park, Poland. Applied Geography 96, 51 65. D Antonio, A. D., Monz, C., Lawson, S., Newman, P., Pettebone, D. and A. Courtemanch, 2010. GPS-Based Measurements of Backcountry Visitors in Parks and Protected Areas: Examples of Methods and Applications from Three Case Studies. Journal of Park and Recreation Administration 28(3), 42 60. Douglas, D. H. and Peucker, T. K., 1973. Algorithms for the reduction of the number of points required to represent a digitized line or its caricature. Cartographica 10(2), 112-122. Evans J. S., Oakleaf J., Cushman S. A. and D. Theobald, 2014. An ArcGIS Toolbox for Surface Gradient and Geomorphometric Modeling, version 2.0-0. Available from: http://evansmurphy.wixsite.com/evansspatial/arcgis-gradient-metrics-toolbox. Hendrikx, J. and J. Johnson, 2016. Understanding Global Crowd Sourcing Data to Examine Travel Behavior in Avalanche Terrain, in: Proceedings of the International Snow Science Workshop, Breckenridge, Colorado, 737 743. Hendrikx, J., Johnson, J. and C. Shelly, 2015. Using GPS tracking to explore terrain preferences of heli-ski guides. Journal of Outdoor Recreation and Tourism 13, 34 43. McCune, B. 2007. Improved estimates of incident radiation and heat load using non-parametric regression against topographic variables. Journal of Vegetation Science 18:751-754. 1667

Miller, A. D., Vaske, J. J., Squires, J. R., Olson, L. E. and E. K. Roberts, 2017. Does Zoning Winter Recreationists Reduce Recreation Conflict? Environmental Management 59, 50 67. Olson, L. E., Squires, J. R., Roberts, E. K., Miller, A. D., Ivan, J. S., and M. Hebblewhite, 2017. Modeling large-scale winter recreation terrain selection with implications for recreation management and wildlife. Applied Geography 86, 66 91. Ramer, U. 1972. An iterative procedure for the polygonal approximation of plane curves. Computer Graphics and Image Processing. 1, 224-256. Statham G., McMahon B. and I. Tomm, 2006. The avalanche terrain exposure scale. In the Proceedings of the International Snow Science Workshop, Telluride, Colorado, 491 499. Thumlert, S. and P. Haegeli, 2018. Describing the severity of avalanche terrain numerically using the observed terrain selection practices of professional guides. Natural Hazards 91, 89 115. 1668