Application of Chebyshev theorem to data preparation in landslide susceptibility mapping studies: an example from Yenice (Karabük, Turkey) region

CORC > 成都山地灾害与环境研究所 > 中国科学院水利部成都山地灾害与环境研究所 > Journal of Mountain Science > Journal of Mountain Science-2016 > Vol13 No.11

	Application of Chebyshev theorem to data preparation in landslide susceptibility mapping studies: an example from Yenice (Karabük, Turkey) region
	Murat ERCANOGLU; Gülseren DAĞDELENLER; Erman ÖZSAYIN; Tolga ALKEVLİ; Harun SÖNMEZ; N. Nur ÖZYURT; Burcu KAHRAMAN; İbrahim UÇAR; Sinem ÇETİNKAYA
刊名	Journal of Mountain Science
	2016-11
卷号	13 期号:11 页码:1923-1940
关键词	Artificial neural network Chebyshev theorem Landslide Landslide database Landslides susceptibility mapping
ISSN号	1672-6316
通讯作者	Murat ERCANOGLU
英文摘要	Landslide database construction is one of the most crucial stages of the landslide susceptibility mapping studies. Although there are many techniques for preparing landslide database in the literature, representative data selection from huge data sets is a challenging, and, to some extent, a subjective task. Thus, in order to produce reliable landslide susceptibility maps, data-driven, objective and representative database construction is a very important stage for these maps. This study mainly focuses on a landslide database construction task. In this study, it was aimed at building a representative landslide database extraction approach by using Chebyshev theorem to evaluate landslide susceptibility in a landslide prone area in the Western Black Sea region of Turkey. The study area was divided into two different parts such as training (Basin 1) and testing areas (Basin 2). A total of nine parameters such as topographical elevation, slope, aspect, planar and profile curvatures, stream power index, distance to drainage, normalized difference vegetation index and topographical wetness index were used in the study. Next, frequency distributions of the considered parameters in both landslide and nonlandslide areas were extracted using different sampling strategies, and a total of nine different landslide databases were obtained. Of these, eight databases were gathered by the methodology proposed by this study based on different standard deviations and algebraic multiplication of raster parameter maps. To evaluate landslide susceptibility, Artificial Neural Network method was used in the study area considering the different landslide and nonlandslide data. Finally, to assess the performances of the so-produced landslide susceptibility maps based on nine data sets, Area Under Curve (AUC) approach was implemented both in Basin 1 and Basin 2. The best performances (the greatest AUC values) were gathered by the landslide susceptibility map produced by two standard deviation database extracted by the Chebyshev theorem, as 0.873 and 0.761, respectively. Results revealed that the methodology proposed by this study is a powerful and objective approach in landslide susceptibility mapping.
收录类别	SCI
语种	英语
内容类型	期刊论文
源URL	[http://ir.imde.ac.cn/handle/131551/17609]
专题	成都山地灾害与环境研究所_Journal of Mountain Science _Journal of Mountain Science-2016_Vol13 No.11
推荐引用方式 GB/T 7714	Murat ERCANOGLU,Gülseren DAĞDELENLER,Erman ÖZSAYIN,et al. Application of Chebyshev theorem to data preparation in landslide susceptibility mapping studies: an example from Yenice (Karabük, Turkey) region[J]. Journal of Mountain Science,2016,13(11):1923-1940.
APA	Murat ERCANOGLU.,Gülseren DAĞDELENLER.,Erman ÖZSAYIN.,Tolga ALKEVLİ.,Harun SÖNMEZ.,...&Sinem ÇETİNKAYA.(2016).Application of Chebyshev theorem to data preparation in landslide susceptibility mapping studies: an example from Yenice (Karabük, Turkey) region.Journal of Mountain Science,13(11),1923-1940.
MLA	Murat ERCANOGLU,et al."Application of Chebyshev theorem to data preparation in landslide susceptibility mapping studies: an example from Yenice (Karabük, Turkey) region".Journal of Mountain Science 13.11(2016):1923-1940.