Research article

Data-mining Based Detection of Glaciers: Quantifying the Extent of Alpine Valley Glaciation

  • Received: 27 March 2015 Accepted: 13 July 2015 Published: 24 July 2015
  • The extent of glaciation in alpine valleys often gives clues to past climates, plate movement, mountain landforms, bedrock geology and more. However, without field investigation, the degree to which a valley was affected by a glacier has been difficult to assess. We developed a model that uses quantitative parameters derived from digital elevations model (DEM) data to predict whether a glacier was likely present in an alpine valley. The model's inputs are mainly derived from the basin hypsometry, and a new parameter termed the Hypothetical Basin Equilibrium Elevation (HBEE), which is based on the equilibrium elevation altitude (ELA) of a glacier. We used data mining techniques that comb through large data sets to find patterns for classification and prediction as the basis for the model. Four classifiers were utilized, and each was tested with two different training set/test data ratios of nearly 150 basins that were previously delineated as fully- or non-glaciated. The classifiers had a predictive accuracy of up to 90% with none falling below 72%. Two of the classifiers, classification tree and naïve-Bayes, have graphical outputs that visually describe the classification process, predictive results, and in the naïve-Bayes case, the relative effectiveness towards the model of each attribute. In all scenarios, the HBEE was found to be an accurate predictor for the model. The model can be applied to any area where glaciation may have occurred, but is particularly useful in areas where the valley is inaccessible for detailed field investigation.

    Citation: Kory J. Allred, Wei Luo. Data-mining Based Detection of Glaciers: Quantifying the Extent of Alpine Valley Glaciation[J]. AIMS Geosciences, 2015, 1(1): 1-18. doi: 10.3934/geosci.2015.1.1

    Related Papers:

  • The extent of glaciation in alpine valleys often gives clues to past climates, plate movement, mountain landforms, bedrock geology and more. However, without field investigation, the degree to which a valley was affected by a glacier has been difficult to assess. We developed a model that uses quantitative parameters derived from digital elevations model (DEM) data to predict whether a glacier was likely present in an alpine valley. The model's inputs are mainly derived from the basin hypsometry, and a new parameter termed the Hypothetical Basin Equilibrium Elevation (HBEE), which is based on the equilibrium elevation altitude (ELA) of a glacier. We used data mining techniques that comb through large data sets to find patterns for classification and prediction as the basis for the model. Four classifiers were utilized, and each was tested with two different training set/test data ratios of nearly 150 basins that were previously delineated as fully- or non-glaciated. The classifiers had a predictive accuracy of up to 90% with none falling below 72%. Two of the classifiers, classification tree and naïve-Bayes, have graphical outputs that visually describe the classification process, predictive results, and in the naïve-Bayes case, the relative effectiveness towards the model of each attribute. In all scenarios, the HBEE was found to be an accurate predictor for the model. The model can be applied to any area where glaciation may have occurred, but is particularly useful in areas where the valley is inaccessible for detailed field investigation.


    加载中
    [1] Brandon MT, Rodent-Tice MK, Garver JL (1998) Late Cenozoic exhumation of the Cascadia accretionary wedge in the Olympic Mountains, northwest Washington State. GSA Bulletin 110: 985-1009. doi: 10.1130/0016-7606(1998)110<0985:LCEOTC>2.3.CO;2
    [2] Poulos MJ, Pierce JL, Flores AN, et al. (2012) Hillslope asymmetry maps reveal widespread, multi-scale organization. Geophys Res Lett 39: 6.
    [3] Gillespie AR (1982) Quaternary Glaciation and Tectonism in the Southeastern Sierra Nevada. Pasadena. 720 p.
    [4] Delmas M, Gunnell Y, Calvet M (2014) Environmental controls on alpine cirque size. Geomorphology 206: 318-329. doi: 10.1016/j.geomorph.2013.09.037
    [5] Montgomery DR, Balco G, Willett SD (2001) Climate, tectonics and the morphology of the Andes. Geology 29: 579-582. doi: 10.1130/0091-7613(2001)029<0579:CTATMO>2.0.CO;2
    [6] Yanites BJ, Ehlers TA (2012) Global climate and tectonic controls on the denudation of glaciated mountains. Earth Planet Sc Lett 325-326: 63-75. doi: 10.1016/j.epsl.2012.01.030
    [7] Hooyer TS, Cohen D, Iverson NR (2012) Control of glacial quarrying by bedrock joints. Geomorphology 153-154: 91-101. doi: 10.1016/j.geomorph.2012.02.012
    [8] Brocklehurst SH, Whipple KX (2002) Glacial erosion and relief production in the Eastern Sierra Nevada, California. Geomorphology 42: 1-24. doi: 10.1016/S0169-555X(01)00069-1
    [9] Hallet B, Hunter L, Bogen J (1996) Rates of erosion and sediment evacuation by glaciers: a review of field data and their implications. Global Planet Change 12: 213-235. doi: 10.1016/0921-8181(95)00021-6
    [10] Headley R, Hallet B, Roe G, et al. (2012) Spatial distribution of glacial erosion rates in the St. Elias range, Alaska, inferred from a realistic model of glacier dynamics. J Geophys Res 117: 16.
    [11] Koppes MN, Montgomery DR (2009) The relative efficacy of fluvial and glacial erosion over modern to orogenic timescales. Nature Geoscience 2: 644-647. doi: 10.1038/ngeo616
    [12] Oerlemans J (1984) Numerical Experiments on Large-Scale Glacial Erosion. Zeitschrift für Gletscherkunde und Glazialgeologie 20: 107-126.
    [13] Sternai P, Herman F, Fox MR, et al. (2011) Hypsometric analysis to identify spatially variable glacial erosion. J Geophys Res 116: 17.
    [14] Hanson PR, Mason JA, Goble RJ (2006) Fluvial terrace formation along Wyomings Laramie Range as a response to inceased late Pleistocene flood magnitudes. Geomorphology 76: 12-25. doi: 10.1016/j.geomorph.2005.08.010
    [15] Anderson RS, Molnar P, Kessler MA (2006) Features of glacial valley profiles simply explained. J Geophys Res 111: 14.
    [16] Harbor J (1992) Numerical modeling of the development of U-shaped valleys by glacial erosion. Geol Soc Am Bull 104: 1364-1375. doi: 10.1130/0016-7606(1992)104<1364:NMOTDO>2.3.CO;2
    [17] Brocklehurst SH, Whipple KX (2004) Hypsometry of glaciated landscapes. Earth Surf Proc land 29: 907-926. doi: 10.1002/esp.1083
    [18] Swanson CD II (2012) Applying GIS metrics to determine degree of glacial modification in mountainous landscapes. Central Washington University. 104 p.
    [19] Amerson BE, Montgomery DR, Meyer G (2008) Relative size of fluvial and glaciated valleys in central Idaho. Geomorphology 93: 537-547. doi: 10.1016/j.geomorph.2007.04.001
    [20] Bonk R. Scale-dependent (2002) Geomorphometric Analysis of Glacier Mapping of Nanga Parbat: GRASS GIS Approach; 2002; Trento. pp. 21.
    [21] Anders AM, Mitchell SG, Tomkin JH (2010) Cirques, peaks, and precipitation patterns in the Swiss Alps: Connections among climate, glacial erosion, and topography. Geology 38: 239-242. doi: 10.1130/G30691.1
    [22] Brown DG, Lusch DP, Duda KA (1998) Supervised classification of types of glaciated landscapes using digital elevation data. Geomorphology 21: 18.
    [23] Wahbeh AH, Al-Radaideh QA, Al-Kabi MN, et al. (2011) A Comparison Study between Data Mining Tools over some Classification Methods. IJACSA, Special Issue: 18-26.
    [24] Han J, Kamber M (2006) Data Mining: Concepts and Techniques. Burlington, MA: Elsevier Sci Technol.
    [25] Giudici P (2005) Applied Data Mining: Statistical Methods for Business and Industry. Hoboken: Wiley.
    [26] Haghanikhameneh F, Panahy PHS, Khanahmadliravi N, et al. (2012) A Comparison Study between Data Mining Algorithms over Classification Techniques in Squid Dataset. IJAI 9: 59-66.
    [27] Foster D, Brocklehurst SH, Gawthorpe RL (2008) Small valley glaciers and the effectiveness of the glacial buzzsaw in the northern Basin and Range, USA. Geomorphology 102: 624-639. doi: 10.1016/j.geomorph.2008.06.009
    [28] Resources WSDoN. Montgomery DR (2002) Valley formation by fluvial and glacial erosion. Geology 30: 1047-1050. doi: 10.1130/0091-7613(2002)030<1047:VFBFAG>2.0.CO;2
    [29] Strahler AN (1952) Hypsometric (Area-Altitude) Analysis of Erosional Topography. Bull Geol Soc Am 63: 1117-1142. doi: 10.1130/0016-7606(1952)63[1117:HAAOET]2.0.CO;2
    [30] Ramu M, Mahalingam B (2012) Hypsometric Properties of Drainage Basins In Karnataka Using Geographical Information System. NY Sci J 5: 156-158.
    [31] Luo W (2002) Hypsometric analysis of Margaritifer Sinus and origin of valley networks. J Geophys Res 107: 10.
    [32] Perez-Pena JV, Azanon JM, Azor A (2009) CalHypso: An ArcGIS extension to calculate hypsometric curves and their statistical moments. Applications to drainage basin analysis in SE Spain. Compu Geosciences 35: 1214-1223.
    [33] Harlin JM (1978) Statistical Moments of the Hypsometric Curve and Its Density Function. Math Geol 10: 59-72. doi: 10.1007/BF01033300
    [34] Luo W (2000) Quantifying groundwater-sapping landforms with a hypsometric technique. J Geophys Res 105: 10.
    [35] Luo W (1998) Hypsometric analysis with a Geographic Information System. Compu Geosciences 24: 815-821. doi: 10.1016/S0098-3004(98)00076-4
    [36] Thomson SN, Brandon MT, Tomkin JH, et al. (2010) Glaciation as a destructive and constructive control on mountain building. Nature 467: 4. doi: 10.1038/467S4a
    [37] Meier MF, Post AS. Recent variations in mass net budgets of glaciers in Westen North America. In: Ward WH, editor; 1962; Obergurgl. IUGG. pp. 63-77.
    [38] Bahr DB, Dyurgerov M, Meier MF (2009) Sea-level rise from glaciers and ice caps: A lower bound. Geophys Res Lett 36: 4.
    [39] Demsar J, Curk T, Erjavec A (2013) Orange: Data Mining Toolbox in Python. JMLR 14: 2349-2353.
    [40] Bellazi R, Zupan B (2008) Predictive data mining in clinical medicin: current issures and guidelnes. Int Journal Med Inform 77: 81-97. doi: 10.1016/j.ijmedinf.2006.11.006
    [41] Breiman L (2001) Random Forests. Mach Learn 45: 5-32. doi: 10.1023/A:1010933404324
    [42] Ho TK. Random Decision Forests; 1995; Montreal. IEEE. pp. 278-282.
    [43] Catal C, Sevim U, Diri B (2011) Practical development of an Eclipse-based software fault prediction tool using Naive Bayes algorithm. Expert Syst Appl 38: 2347-2353. doi: 10.1016/j.eswa.2010.08.022
    [44] Garcia V, Debreuve E, Nielsen F, et al. K-nearest neighbor search: Fast GPU-based implementations and application to high-dimensional feature matching; 2010 26-29 Sept. 2010. pp. 3757-3760.
    [45] Shao J (1993) Linear model selection by cross-validation. J Am Stat Ass 88: 486--494 . doi: 10.1080/01621459.1993.10476299
    [46] Strobl C, Malley J, Tutz G(2009) An Introduction to Recursive Partitioning: Rationale, Application, and Characteristics of Classification and Regression Trees, Bagging, and Random Forests. Pschol Methods 14(4): 323-348.
    [47] Segal MR (2004) Machine Learning Benchmarks and Random Forest Regression.
    [48] Možina M, Demšar J, Kattan M, et al. (2004) Nomograms for Visualization of Naive Bayesian Classifier. In: Boulicaut J-F, Esposito F, Giannotti F et al., editors. Knowledge Discovery in Databases: PKDD 2004: Springer Berlin Heidelberg. pp. 337-348.
    [49] Horton RE (1945) Erosional development of streams and their drainage basins: hydro-physical approach to quantitative morphology. Geol Soc Am Bull 56: 275-370. doi: 10.1130/0016-7606(1945)56[275:EDOSAT]2.0.CO;2
    [50] Souness C, Hubbard B, Milliken RE, et al. (2012) An inventory and population-scale analysis of martian glacier-like forms. Icarus 217: 13.
    [51] Meier MF, Post AS (1962) Recent variations in mass net budgets of glaciers in western North America. IASHP 58: 63-77.
    [52] Kern Z, László P (2010) Size specific steady-state accumulation-area rato: an improvement for equilibrium-line estimation of small paleoglaciers. QSP 29: 2781-2787
    [53] Naylor S, Gabet EJ (2007) Valley asymmetry and glacial versus nonglacial erosion in the Bitterroot Range, Montana, USA. Geology 35: 375-378. doi: 10.1130/G23283A.1
  • Reader Comments
  • © 2015 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(5352) PDF downloads(1467) Cited by(3)

Article outline

Figures and Tables

Figures(5)  /  Tables(2)

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog