Automatic approach to deriving fuzzy slope positions

doi:10.1016/j.geomorph.2017.12.024

	Automatic approach to deriving fuzzy slope positions
	Zhu, Liang-Jun 1,2; Zhu, A-Xing 1,3,4,5,6; Qin, Cheng-Zhi 1,2,6; Liu, Jun-Zhi 3,4,6
刊名	GEOMORPHOLOGY
	2018-03-01
卷号	304 页码:173-183
关键词	Slope position Fuzzy membership Automation Parallel computing
ISSN号	0169-555X
DOI	10.1016/j.geomorph.2017.12.024
通讯作者	Qin, Cheng-Zhi(qincz@lreis.ac.cn)
英文摘要	Fuzzy characterization of slope positions is important for geographic modeling. Most of the existing fuzzy classification-based methods for fuzzy characterization require extensive user intervention in data preparation and parameter setting, which is tedious and time-consuming. This paper presents an automatic approach to overcoming these limitations in the prototype-based inference method for deriving fuzzy membership value (or similarity) to slope positions. The key contribution is a procedure for finding the typical locations and setting the fuzzy inference parameters for each slope position type. Instead of being determined totally by users in the prototype-based inference method, in the proposed approach the typical locations and fuzzy inference parameters for each slope position type are automatically determined by a rule set based on prior domain knowledge and the frequency distributions of topographic attributes. Furthermore, the preparation of topographic attributes (e.g., slope gradient, curvature, and relative position index) is automated, so the proposed automatic approach has only one necessary input, i.e., the gridded digital elevation model of the study area. All compute-intensive algorithms in the proposed approach were speeded up by parallel computing. Two study cases were provided to demonstrate that this approach can properly, conveniently and quickly derive the fuzzy slope positions. (C) 2018 Elsevier B.V. All rights reserved.
资助项目	Natural Science Foundation of China[41422109] ; Natural Science Foundation of China[41431177] ; Innovation Project of LREIS[O88RA20CYA] ; Natural Science Foundation of Jiangsu Province of China[BK20150975]
WOS关键词	LANDFORM ELEMENTS ; TERRAIN ANALYSIS ; CLASSIFICATION ; SEGMENTATION ; GEOMETRY ; LOGIC ; DEMS
WOS研究方向	Physical Geography ; Geology
语种	英语
出版者	ELSEVIER SCIENCE BV
WOS记录号	WOS:000426023400014
资助机构	Natural Science Foundation of China ; Innovation Project of LREIS ; Natural Science Foundation of Jiangsu Province of China
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/56994]
专题	中国科学院地理科学与资源研究所
通讯作者	Qin, Cheng-Zhi
作者单位	1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Nanjing Normal Univ, Minist Educ, Key Lab Virtual Geog Environm, Nanjing 210023, Jiangsu, Peoples R China 4.State Key Lab Cultivat Base Geog Environm Evolut, Nanjing 210023, Jiangsu, Peoples R China 5.Univ Wisconsin Madison, Dept Geog, Madison, WI 53706 USA 6.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Jiangsu, Peoples R China
推荐引用方式 GB/T 7714	Zhu, Liang-Jun,Zhu, A-Xing,Qin, Cheng-Zhi,et al. Automatic approach to deriving fuzzy slope positions[J]. GEOMORPHOLOGY,2018,304:173-183.
APA	Zhu, Liang-Jun,Zhu, A-Xing,Qin, Cheng-Zhi,&Liu, Jun-Zhi.(2018).Automatic approach to deriving fuzzy slope positions.GEOMORPHOLOGY,304,173-183.
MLA	Zhu, Liang-Jun,et al."Automatic approach to deriving fuzzy slope positions".GEOMORPHOLOGY 304(2018):173-183.