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http://dx.doi.org/10.9720/kseg.2016.1.23

Landslide Susceptibility Analysis : SVM Application of Spatial Databases Considering Clay Mineral Index Values Extracted from an ASTER Satellite Image  

Nam, Koung-Hoon (Dept. of Earth and Environmental Sciences, Andong National University)
Lee, Moung-Jin (Korea Environment Institute)
Jeong, Gyo-Cheol (Dept. of Earth and Environmental Sciences, Andong National University)
Publication Information
The Journal of Engineering Geology / v.26, no.1, 2016 , pp. 23-32 More about this Journal
Abstract
This study evaluates landslide susceptibility using statistical analysis by SVM (support vector machine) and the illite index of clay minerals extracted from ASTER(advanced spaceborne thermal emission and reflection radiometer) imagery which can be use to create mineralogical mapping. Landslide locations in the study area were identified from aerial photographs and field surveys. A GIS spatial database was compiled containing topographic maps (slope, aspect, curvature, distance to stream, and distance to road), maps of soil properties (thickness, material, topography, and drainage), maps of timber properties (diameter, age, and density), and an ASTER satellite imagery (illite index). The landslide susceptibility map was constructed through factor correlation using SVM to analyze the spatial database. Comparison of area under the curve values showed that using the illite index model provided landslide susceptibility maps that were 76.46% accurate, which compared favorably with 74.09% accuracy achieved without them.
Keywords
landslide; clay mineral; GIS; ASTER; AUC;
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Times Cited By KSCI : 7  (Citation Analysis)
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1 Al-Rawas, A. A., 1999, The factors controlling the expansive nature of the soils and rocks of northern Oman, Engineering Geology, 53(3), 327-350.   DOI
2 Bottou, L., Cortes, C., Denker, J. S., Drucker, H., Guyon, I., Jackel, L. D., and Vapnik, V., 1994, Comparison of classifier methods: a case study in handwritten digit recognition, In International Conference on Pattern Recognition, IEEE Computer Society Press, 77-77.
3 Bredensteiner, E. J. and Bennett, K. P., 1999, Multicategory classification by support vector machines, In Computational Optimization, Springer US, 53-19.
4 Cortes, C. and Vapnik, V., 1995, Support-vector networks, Machine learning, 20(3), 273-297.   DOI
5 Cha, A., 2014, A comparison on the identification of landslide hazard using geomorphological characteristics, Journal of the Korean Geo-Environmental Society, 15(6), 67-73 (in Korean).   DOI
6 Chang, C. C. and Lin, C. J., 2011, LIBSVM: A library for support vector machines, ACM Transactions on Intelligent Systems and Technology (TIST), 2(3), 27.
7 Choo, C. O., 2001, Mineralogical Characteristics of illite and its application, The Journal of the Mineralogical Society of Korea (Mineral & Industry), 14(2), 29-37 (in Korean).
8 Coughlan, K. J., Mc Garry, D., Loch, R. J., Bridge, B., and Smith, G. D., 1991, The measurement of soil structure-some practical initiatives, Australian Journal of Soil Research, 29(6), 869-889.   DOI
9 Dudal, R., and Eswaran, H., 1988, Distribution, properties and classification of Vertisols. Vertisols: Their distribution, properties, classification and management, Texas A & M Printing Center, College Station, TX, 1-22.
10 Fujisada, H., 1995, Design and performance of ASTER instrument, Proceedings of SPIE, The International Society for Optical Engineering, 2583, 16-25.
11 Gray, J. and Murphy, B., 2002, Parent material and world soil distribution. In 17th World Congress of Soil Science, Bangkok, Thailand, 2215/1-2215/14.
12 Jayawardane, N. S. and Greacen, E. L., 1987, The nature of swelling in soils, Australian Journal of Soil Research, 25(1), 107-113.   DOI
13 Kang, Y. J., Lee, J. I., Bae, J. H., and Lee, C. H., 2013, Target classification algorithm using complex-valued support vector machine, Journal of the Institute of Electronics Engineers of Korea, 50(4), 942-948 (in Korean).
14 Lee, M. J., Lee, S. R., and Jeon0 S. W., 2012, Landslide Hazard Mappin gnad Verification Using Probability Rainfall and Artificaial Neural Networks, Journal of the Korean Association of Geographic Information Studies, 15(2), 57-70 (in Korean).   DOI
15 Kang, N. Y., Go, S. Y., and Cho, G. S., 2013, A comparative study on suitable SVM kernel function of land cover classification using KOMPSAT-2 imagery, Journal of the Korean Society for Geospatial Information System, 21(2), 19-25 (in Korean).   DOI
16 Lee, H. J., Chi, K. H. and Jang, D. H., 2008, Extraction of pyrophyllite mine using characteristics of spectral reflectance of aster satellite imageries, Journal of the Korean Geomorphological Association, 49-60 (in Korean).
17 Lee, S., Ryu, J. H., Lee, M. J., Lee, M. J., and Won, J. S., 2003a, Landslide Susceptibility Analysis using GIS and Artificial neural network. Earth Surface Processes and Landforms, 27, 1361-1376.   DOI
18 Lee, H. G. and Kim, G. H., 2012, Landslide Risk Assessment in Inje Using Logistic Regression Model, Journal of the Korean Society of Surveing, Geodesy, Photogrammetry, and Cartography, 30(3), 313-321 (in Korean).   DOI
19 Lee, M. J. and Lee, J. H., 2013, The study for development of climate change caused urban geological hazards risk assessment system, KEI working paper, 5p (in Korean).
20 Lee, S. and Min, K. D., 2001, Statistical analysis of landslide susceptibility at Yoing, Korea. Environmental Geology, 40, 1095-111.   DOI
21 Lee, S., Ryu, J. H., Lee, M. J., Lee, M. J., and Won, J. S., 2003b, Landslide susceptibility analysis using artificial neural network at Boun, Korea. Environmental Geology, 44, 820-833.   DOI
22 Lee, H, J., Kim, I. J., Chi, K. H., Kim, E. J., and Jang, D. H., 2009, Extraction model of non-metallic mine using multispectral aster swir data, Journal of the Korean Geomorphological Association, 16(3), 77-86 (in Korean).
23 Oh, H. J., 2010, Landslide susceptibility analysis and validation using Weight-of-Evidence model, Journal of the Geological Society of Korea, 46(2), 157-170 (in Korean).
24 Mc Garry, D. and Malafant, K. W. J., 1987, The analysis of volume change in unconfined units of soil, Soil Science Society of America Journal, 51(2), 290-297.   DOI
25 Nam, K. H., Lee, H. J., and Jeong, G. C., 2014(a), Analysis of Landslide location using Spectral Reflectance of Clay Mineral and ASTER Satellite Image, The Journal of Engineering Geology., 24(3), 411-421.   DOI
26 San, B. T., 2014, An evaluation of SVM using polygon-based random sampling in landslide susceptibility mapping: The Candir catchment area(western Antalya, Turkey), International Journal of Applied Earth Observation and Geoinformation, 26, 399-412.   DOI
27 Nam, K. H., Lee, H. J., and Jeong, G. C., 2014(b), Estimation of landslide triggering factors and application to the risk criterion, Proceedings of KSEG, 2014 Fall Conference, 3-19.
28 Oh, I. S. and Yoon, Y. Y., 1972, 1:50,000 Geological map of the suwon sheet, KIGAM, 7p (in Korean).
29 Rowan, L. C., Hook, S. J., Abrams, J. J., and Mars, C. C., 2003, Mapping hydrothermally altered rocks at Cuprite, Nevada using the Advanced Spaceborne Thermal Emissivity and Reflection Radiometer (ASTER), A new satellite-imageing system, Economic Geology, 98, 1019-1027.   DOI
30 Soil Survey Staff, 1999, Soil Taxonomy, A basic system of soil classification for making and interpreting soil surveys, Second edition, 869.
31 Taboada, M. A. and Lavado, R. S., 2006, Swelling in non-vertisolic soils, Expansive Soils: Recent Advances in Characterization and Treatment, 55p.
32 Van der Meer, F. D., 1999, Can we map swelling clay with remote sensing?., International Journal of Applied Earth Observation and Geoinformation, 1, 27-35.   DOI
33 Yule, D. F. and Ritchie, J. T., 1980, Soil shrinkage relationships of Texas Vertisols: I. Small cores, Soil Science Society of America Journal, 44(6), 1285-1291.   DOI