干旱区生态环境知识资源中心(Arid): Modelling gully-erosion susceptibility in a semi-arid region, Iran: Investigation of applicability of certainty factor and maximum entropy models

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DOI	10.1016/j.scitotenv.2018.11.235
	Modelling gully-erosion susceptibility in a semi-arid region, Iran: Investigation of applicability of certainty factor and maximum entropy models
	Azareh, Ali 1; Rahmati, Omid 2; Rafiei-Sardooi, Elham 3; Sankey, Joel B.4; Lee, Saro 5; Shahabi, Himan 6; Bin Ahmad, Baharin 7
通讯作者	Lee, Saro
来源期刊	SCIENCE OF THE TOTAL ENVIRONMENT
ISSN	0048-9697
EISSN	1879-1026
出版年	2019
卷号	655 页码:684-696
英文摘要	Gully erosion susceptibility mapping is a fundamental tool for land-use planning aimed at mitigating land degradation. However, the capabilities of some state-of-the-art data-mining models for developing accurate maps of gully erosion susceptibility have not yet been fully investigated. This study assessed and compared the performance of two different types of data-mining models for accurately mapping gully erosion susceptibility at a regional scale in Chavar, Ilam, Iran. The two methods evaluated were: Certainty Factor (CF), a bivariate statistical model; and Maximum Entropy (ME), an advanced machine learning model. Several geographic and environmental factors that can contribute to gully erosion were considered as predictor variables of gully erosion susceptibility. Based on an existing differential GPS survey inventory of gully erosion, a total of 63 eroded gullies were spatially randomly split in a 70:30 ratio for use in model calibration and validation, respectively. Accuracy assessments completed with the receiver operating characteristic curve method showed that the ME-based regional gully susceptibility map has an area under the curve (AUC) value of 88.6% whereas the CF-based map has an AUC of 81.8%. According to jackknife tests that were used to investigate the relative importance of predictor variables, aspect, distance to river, lithology and land use are the most influential factors for the spatial distribution of gully erosion susceptibility in this region of Iran. The gully erosion susceptibility maps produced in this study could be useful tools for land managers and engineers tasked with road development, urbanization and other future development. (C) 2018 Elsevier B.V. All rights reserved.
英文关键词	Gully Erosion GESM Certainty factor Maximum entropy Machine learning
类型	Article
语种	英语
国家	Iran ; USA ; South Korea ; Malaysia
收录类别	SCI-E
WOS记录号	WOS:000455034600069
WOS关键词	TOPOGRAPHIC WETNESS INDEX ; SAMPLE SELECTION BIAS ; LANDSLIDE SUSCEPTIBILITY ; LOGISTIC-REGRESSION ; SOIL-EROSION ; SLOPE ASPECT ; FREQUENCY RATIO ; WATER EROSION ; DECISION TREE ; K-FACTOR
WOS类目	Environmental Sciences
WOS研究方向	Environmental Sciences & Ecology
来源机构	United States Geological Survey
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/218640
作者单位	1.Univ Jiroft, Dept Geog, Kerman, Iran; 2.Islamic Azad Univ, Khorramabad Branch, Young Researchers & Elites Club, Khorramabad, Iran; 3.Univ Jiroft, Fac Nat Resources, Kerman, Iran; 4.US Geol Survey, Southwest Biol Sci Ctr, Grand Canyon Monitoring & Res Ctr, 2255 N Gemini Dr, Flagstaff, AZ 86001 USA; 5.Korea Inst Geosci & Mineral Resources KIGAM, Geosci Platform Res Div, Daejeon 305350, South Korea; 6.Univ Kurdistan, Fac Nat Resources, Dept Geomorphol, Sanandaj, Iran; 7.Univ Teknol Malaysia, Fac Built Environm & Surveying, Johor Baharu 81310, Malaysia
推荐引用方式 GB/T 7714	Azareh, Ali,Rahmati, Omid,Rafiei-Sardooi, Elham,et al. Modelling gully-erosion susceptibility in a semi-arid region, Iran: Investigation of applicability of certainty factor and maximum entropy models[J]. United States Geological Survey,2019,655:684-696.
APA	Azareh, Ali.,Rahmati, Omid.,Rafiei-Sardooi, Elham.,Sankey, Joel B..,Lee, Saro.,...&Bin Ahmad, Baharin.(2019).Modelling gully-erosion susceptibility in a semi-arid region, Iran: Investigation of applicability of certainty factor and maximum entropy models.SCIENCE OF THE TOTAL ENVIRONMENT,655,684-696.
MLA	Azareh, Ali,et al."Modelling gully-erosion susceptibility in a semi-arid region, Iran: Investigation of applicability of certainty factor and maximum entropy models".SCIENCE OF THE TOTAL ENVIRONMENT 655(2019):684-696.