Virtual snow stakes: a new method for snow depth measurement at remote camera stations

Abstract Remote cameras are used to study demographics, ecological processes, and behavior of wildlife populations. Cameras have also been used to measure snow depth with physical snow stakes. However, concerns that physical instruments at camera sites may influence animal behavior limit installatio...

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Main Authors: Kaitlyn M. Strickfaden, Marnie L. Behan, Adrienne M. Marshall, Leona K. Svancara, David E. Ausband, Timothy E. Link
Format: Article
Language:English
Published: Wiley 2023-09-01
Series:Wildlife Society Bulletin
Subjects:
Online Access:https://doi.org/10.1002/wsb.1481
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author Kaitlyn M. Strickfaden
Marnie L. Behan
Adrienne M. Marshall
Leona K. Svancara
David E. Ausband
Timothy E. Link
author_facet Kaitlyn M. Strickfaden
Marnie L. Behan
Adrienne M. Marshall
Leona K. Svancara
David E. Ausband
Timothy E. Link
author_sort Kaitlyn M. Strickfaden
collection DOAJ
description Abstract Remote cameras are used to study demographics, ecological processes, and behavior of wildlife populations. Cameras have also been used to measure snow depth with physical snow stakes. However, concerns that physical instruments at camera sites may influence animal behavior limit installation of instruments to facilitate collecting such data. Given that snow depth data are inherently contained within images, potential insights that could be made using these data are lost. To facilitate camera‐based snow depth observations without additional equipment installation, we developed a method implemented in an R package called edger to superimpose virtual measurement devices onto images. The virtual snow stakes can be used to derive snow depth measurements. We validated the method for snow depth estimation using camera data from Latah County, Idaho, USA in winter 2020–2021. Mean bias error between the virtual snow stake and a physical snow stake was 5.8 cm; the mean absolute bias error was 8.8 cm. The mean Nash Sutcliffe Efficiency score comparing the fit of the 2 sets of measurements within each camera was 0.748, indicating good agreement. The edger package provides researchers with a means to take critical measurements for ecological studies without the use of physical objects that could alter animal behavior, and snow data at finer scales can complement other snow data sources that have coarser spatial and temporal resolution.
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spelling doaj.art-b303affbeba54452bfa0e6a517bf93182023-09-12T04:31:27ZengWileyWildlife Society Bulletin2328-55402023-09-01473n/an/a10.1002/wsb.1481Virtual snow stakes: a new method for snow depth measurement at remote camera stationsKaitlyn M. Strickfaden0Marnie L. Behan1Adrienne M. Marshall2Leona K. Svancara3David E. Ausband4Timothy E. Link5Idaho Cooperative Fish and Wildlife Research Unit, Department of Fish and Wildlife Sciences University of Idaho 875 Perimeter Drive MS 1136 Moscow Idaho 83844 USAIdaho Cooperative Fish and Wildlife Research Unit, Department of Fish and Wildlife Sciences University of Idaho 875 Perimeter Drive MS 1136 Moscow Idaho 83844 USAHydrologic Sciences and Engineering Program Colorado School of Mines 1500 Illinois St. Golden CO 80401 USAIdaho Department of Fish and Game 600 S Walnut St Boise ID 83712 USAU.S. Geological Survey Idaho Cooperative Fish and Wildlife Research Unit 875 Perimeter Drive MS 1141 Moscow Idaho 83844 USADepartment of Forest, Rangeland, and Fire Sciences University of Idaho 875 Perimeter Drive MS 1133 Moscow Idaho 83844 USAAbstract Remote cameras are used to study demographics, ecological processes, and behavior of wildlife populations. Cameras have also been used to measure snow depth with physical snow stakes. However, concerns that physical instruments at camera sites may influence animal behavior limit installation of instruments to facilitate collecting such data. Given that snow depth data are inherently contained within images, potential insights that could be made using these data are lost. To facilitate camera‐based snow depth observations without additional equipment installation, we developed a method implemented in an R package called edger to superimpose virtual measurement devices onto images. The virtual snow stakes can be used to derive snow depth measurements. We validated the method for snow depth estimation using camera data from Latah County, Idaho, USA in winter 2020–2021. Mean bias error between the virtual snow stake and a physical snow stake was 5.8 cm; the mean absolute bias error was 8.8 cm. The mean Nash Sutcliffe Efficiency score comparing the fit of the 2 sets of measurements within each camera was 0.748, indicating good agreement. The edger package provides researchers with a means to take critical measurements for ecological studies without the use of physical objects that could alter animal behavior, and snow data at finer scales can complement other snow data sources that have coarser spatial and temporal resolution.https://doi.org/10.1002/wsb.1481edgerforest‐snowremote camerassnow depthsnowtography
spellingShingle Kaitlyn M. Strickfaden
Marnie L. Behan
Adrienne M. Marshall
Leona K. Svancara
David E. Ausband
Timothy E. Link
Virtual snow stakes: a new method for snow depth measurement at remote camera stations
Wildlife Society Bulletin
edger
forest‐snow
remote cameras
snow depth
snowtography
title Virtual snow stakes: a new method for snow depth measurement at remote camera stations
title_full Virtual snow stakes: a new method for snow depth measurement at remote camera stations
title_fullStr Virtual snow stakes: a new method for snow depth measurement at remote camera stations
title_full_unstemmed Virtual snow stakes: a new method for snow depth measurement at remote camera stations
title_short Virtual snow stakes: a new method for snow depth measurement at remote camera stations
title_sort virtual snow stakes a new method for snow depth measurement at remote camera stations
topic edger
forest‐snow
remote cameras
snow depth
snowtography
url https://doi.org/10.1002/wsb.1481
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AT leonaksvancara virtualsnowstakesanewmethodforsnowdepthmeasurementatremotecamerastations
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