globalchange  > 过去全球变化的重建
DOI: 10.1371/journal.pone.0123804
论文题名:
A New Extraction Method of Loess Shoulder-Line Based on Marr-Hildreth Operator and Terrain Mask
作者: Sheng Jiang; Guoan Tang; Kai Liu
刊名: PLOS ONE
ISSN: 1932-6203
出版年: 2015
发表日期: 2015-4-24
卷: 10, 期:4
语种: 英语
英文关键词: Loess ; Terrain ; Image processing ; Landforms ; Plateaus ; Algorithms ; Erosion ; Imaging techniques
英文摘要: Loess shoulder-lines are significant structural lines which divide the complicated loess landform into loess interfluves and gully-slope lands. Existing extraction algorithms for shoulder-lines mainly are based on local maximum of terrain features. These algorithms are sensitive to noise for complicated loess surface and the extraction parameters are difficult to be determined, making the extraction results usually inaccurate. This paper presents a new extraction approach for loess shoulder-lines, in which Marr-Hildreth edge operator is employed to construct initial shoulder-lines. Then the terrain mask for confining the boundary of shoulder-lines is proposed based on slope degree classification and morphology methods, avoiding interference from non-valley area and modify the initial loess shoulder-lines. A case study is conducted in Yijun located in the northern Shanxi Loess Plateau of China. The Digital Elevation Models with a grid size of 5 m is applied as original data. To obtain optimal scale parameters, the Euclidean Distance Offset Percentages between shoulder-lines is calculated by the Marr-Hildreth operator and the manual delineations. The experimental results show that the new method could achieve the highest extraction accuracy when σ = 5 in Gaussian smoothing. According to the accuracy assessment, the average extraction accuracy is about 88.5%, which indicates that the proposed method is applicable for the extraction of loess shoulder-lines in the loess hilly and gully areas.
URL: http://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0123804&type=printable
Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/20300
Appears in Collections:过去全球变化的重建
影响、适应和脆弱性
科学计划与规划
气候变化与战略
全球变化的国际研究计划
气候减缓与适应
气候变化事实与影响

Files in This Item: Download All
File Name/ File Size Content Type Version Access License
journal.pone.0123804.PDF(5145KB)期刊论文作者接受稿开放获取View Download

作者单位: Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, 1 Wenyuan Road, Nanjing, Jiangsu 210023, China;State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province), 1 Wenyuan Road, Nanjing, Jiangsu, 210023, China;Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, 1 Wenyuan Road, Nanjing, Jiangsu 210023, China;Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, 1 Wenyuan Road, Nanjing, Jiangsu 210023, China;State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province), 1 Wenyuan Road, Nanjing, Jiangsu, 210023, China;Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, 1 Wenyuan Road, Nanjing, Jiangsu 210023, China;Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, 1 Wenyuan Road, Nanjing, Jiangsu 210023, China;State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province), 1 Wenyuan Road, Nanjing, Jiangsu, 210023, China;Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, 1 Wenyuan Road, Nanjing, Jiangsu 210023, China

Recommended Citation:
Sheng Jiang,Guoan Tang,Kai Liu. A New Extraction Method of Loess Shoulder-Line Based on Marr-Hildreth Operator and Terrain Mask[J]. PLOS ONE,2015-01-01,10(4)
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[Sheng Jiang]'s Articles
[Guoan Tang]'s Articles
[Kai Liu]'s Articles
百度学术
Similar articles in Baidu Scholar
[Sheng Jiang]'s Articles
[Guoan Tang]'s Articles
[Kai Liu]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[Sheng Jiang]‘s Articles
[Guoan Tang]‘s Articles
[Kai Liu]‘s Articles
Related Copyright Policies
Null
收藏/分享
文件名: journal.pone.0123804.PDF
格式: Adobe PDF
此文件暂不支持浏览
所有评论 (0)
暂无评论
 

Items in IR are protected by copyright, with all rights reserved, unless otherwise indicated.