A comparison of measurement methods: terrestrial laser scanning, tachymetry and snow probing for the determination of the spatial snow-depth distribution on slopes

被引:109
|
作者
Prokop, A. [1 ,2 ]
Schirmer, M. [2 ]
Rub, M. [3 ]
Lehning, M. [2 ]
Stocker, M. [3 ]
机构
[1] Univ Nat Resources & Appl Life Sci, Inst Mt Risk Engn, Dept Civil Engn & Nat Hazards, BOKU, Peter Jordan Str 82, A-1180 Vienna, Austria
[2] WSL Swiss Fed Inst Snow & Avalanche Res SLF, CH-7260 Davos, Switzerland
[3] ETH Honggerberg, Inst Geodesy & Photogrammetry, CH-8093 Zurich, Switzerland
来源
基金
瑞士国家科学基金会;
关键词
D O I
10.3189/172756408787814726
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Determination of the spatial snow-depth distribution is important in potential avalanche-starting zones, both for avalanche prediction and for the dimensioning of permanent protection measures. Knowledge of the spatial distribution of snow is needed in order to validate snow depths computed from snowpack and snowdrift models. The inaccessibility of alpine terrain and the acute danger of avalanches complicate snow-depth measurements (e.g. when probes are used), so the possibility of measuring the snowpack using terrestrial laser scanning (TLS) was tested. The results obtained were compared to those of tachymetry and manual snow probing. Laser measurements were taken using the long-range laser profile measuring system Riegl LPM-i800HA. The wavelength used by the laser was 0.9 mu m (near-infrared). The accuracy was typically within 30mm. The highest point resolution was 30mm when measured from a distance of 100m. Tachymetry measurements were carried out using Leica TCRP1201 systems. Snowpack depths measured by the tachymeter were also used. The datasets captured by tachymetry were used as reference models to compare the three different methods (TLS, tachymetry and snow probing). This is the first time that the accuracy of TLS systems in snowy and alpine weather conditions has been quantified. The relative accuracy between the three measurement methods is bounded by a maximum off set of +/- 8 cm. Between TLS and the tachymeter the standard deviation is 1 sigma = 2 cm, and between manual probing and TLS it is up to 1 sigma - 10 cm, for maximum distances for the TLS and tachymeter of 300 m.
引用
收藏
页码:210 / +
页数:2
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    [J]. COLD REGIONS SCIENCE AND TECHNOLOGY, 2008, 54 (03) : 155 - 163
  • [2] Tree canopy and snow depth relationships at fine scales with terrestrial laser scanning
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    Graham, Jake D.
    Spaete, Lucas
    Gelvin, Arthur
    Marshall, Hans-Peter
    McNamara, James P.
    Enterkine, Josh
    [J]. CRYOSPHERE, 2021, 15 (05): : 2187 - 2209
  • [3] MAPPING SNOW DEPTH WITH AUTOMATED TERRESTRIAL LASER SCANNING - INVESTIGATING POTENTIAL APPLICATIONS
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    Gigele, T.
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    [J]. ISPRS INTERNATIONAL JOINT CONFERENCES OF THE 2ND GEOSPATIAL INFORMATION RESEARCH (GI RESEARCH 2017); THE 4TH SENSORS AND MODELS IN PHOTOGRAMMETRY AND REMOTE SENSING (SMPR 2017); THE 6TH EARTH OBSERVATION OF ENVIRONMENTAL CHANGES (EOEC 2017), 2017, 42-4 (W4): : 537 - 540
  • [4] Terrestrial laser scanning for snow depth observations: An update on technical developments and applications
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    [J]. ISSW 09 EUROPE: INTERNATIONAL SNOW SCIENCE WORKSHOP, PROCEEDINGS, 2009, : 192 - 196
  • [5] Terrestrial laser scanner for spatial snow depth and density measurements in mountain environment
    Lavy, Muriel
    Amanzio, Gianpiero
    Crepaldi, Stefano
    Suozzi, Enrico
    De Maio, Marina
    [J]. RENDICONTI ONLINE SOCIETA GEOLOGICA ITALIANA, 2015, 35 : 177 - 179
  • [6] RESOLVING THE INFLUENCE OF FOREST-CANOPY STRUCTURE ON SNOW DEPTH DISTRIBUTIONS WITH TERRESTRIAL LASER SCANNING
    Uhlmann, Zach
    Glenn, Nancy F.
    Spaete, Lucas P.
    Hiemstra, Chris
    Tennant, Chris
    McNamara, Jim
    [J]. IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2018, : 6284 - 6286
  • [7] Canopy influence on snow depth distribution in a pine stand determined from terrestrial laser data
    Revuelto, J.
    Lopez-Moreno, J. I.
    Azorin-Molina, C.
    Vicente-Serrano, S. M.
    [J]. WATER RESOURCES RESEARCH, 2015, 51 (05) : 3476 - 3489
  • [8] Comparison of spatial interpolation methods for estimating snow distribution in the Colorado Rocky Mountains
    Erxleben, J
    Elder, K
    Davis, R
    [J]. HYDROLOGICAL PROCESSES, 2002, 16 (18) : 3627 - 3649
  • [9] Comparison of artificial neural network and combined models in estimating spatial distribution of snow depth and snow water equivalent in Samsami basin of Iran
    Tabari, Hossein
    Marofi, S.
    Abyaneh, H. Zare
    Sharifi, M. R.
    [J]. NEURAL COMPUTING & APPLICATIONS, 2010, 19 (04): : 625 - 635
  • [10] Comparison of artificial neural network and combined models in estimating spatial distribution of snow depth and snow water equivalent in Samsami basin of Iran
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    S. Marofi
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    M. R. Sharifi
    [J]. Neural Computing and Applications, 2010, 19 : 625 - 635