中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Identifying terraces in the hilly and gully regions of the Loess Plateau in China

文献类型:期刊论文

作者Sun, Wenyi1,2; Zhang, Yongqiang2,4; Mu, Xingmin1; Li, Jiuyi4; Gao, Peng1; Zhao, Guangju1; Dang, Tianmin3; Chiew, Francis2
刊名LAND DEGRADATION & DEVELOPMENT
出版日期2019-08-07
页码13
关键词identification KNN the Loess Plateau SAM terraces
ISSN号1085-3278
DOI10.1002/ldr.3405
通讯作者Mu, Xingmin(muxm2014@gmail.com) ; Li, Jiuyi(lijiuyi@igsnrr.ac.cn)
英文摘要Terrace identification is the basis for understanding quantity, quality, and land covers of terraces and their effects on agriculture production and various surface processes, for example, hydrological and ecological processes. However, there are some drawbacks and limitations in the automatic extraction of terraces, such as difficulty of outlining the overall boundary for individual terrace and the limitation of applying methods and parameters. In this study, we used machine learning methods on the basis of Geographic Object-Based Image Analysis using K-nearest neighbours and spectral angle mapper algorithms to extract terraces in the hilly and gully regions on the Loess Plateau, China. This study relied on medium-resolution image Landsat-8 combined with Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model to extract the overall boundary of terraces and relies on high-resolution images GaoFen-1 to extract the terraced edges of terraces. It used the methods of principal component analysis and Laplacian convolution filter to enhance and extract terraced edges inside of the boundary of terraces. Our estimates are with overall accuracy of 62.2% in K-nearest neighbours and 74.8% in spectral angle mapper methods, indicating the advantages of the proposed method despite the use of much lower resolution data than previous studies that used both high-resolution terrain and remote sensing imageries data. This study highlights the importance of using appropriate methods plus reasonable spatial resolution of remote sensing data for outlining the overall boundary of terraces in the hilly and gully regions.
WOS关键词CLASSIFICATION ; IDENTIFICATION ; BENEFITS ; EROSION
资助项目National Natural Science Foundation of China[41430861] ; National Natural Science Foundation of China[41501293] ; National Key Research and Development Program of China[2014FY210100] ; National Key Research and Development Program of China[2016YFC0402401]
WOS研究方向Environmental Sciences & Ecology ; Agriculture
语种英语
WOS记录号WOS:000481148500001
出版者WILEY
资助机构National Natural Science Foundation of China ; National Key Research and Development Program of China
源URL[http://ir.igsnrr.ac.cn/handle/311030/69057]  
专题中国科学院地理科学与资源研究所
通讯作者Mu, Xingmin; Li, Jiuyi
作者单位1.Northwest A&F Univ, Inst Soil & Water Conservat, State Key Lab Soil Eros & Dryland Farming Loess P, Yangling 712100, Shaanxi, Peoples R China
2.CSIRO, Land & Water, Canberra, ACT 2601, Australia
3.Yellow River Conservancy Commiss, Upper & Middle Yellow River Bur, Xian 710021, Shaanxi, Peoples R China
4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China
推荐引用方式
GB/T 7714
Sun, Wenyi,Zhang, Yongqiang,Mu, Xingmin,et al. Identifying terraces in the hilly and gully regions of the Loess Plateau in China[J]. LAND DEGRADATION & DEVELOPMENT,2019:13.
APA Sun, Wenyi.,Zhang, Yongqiang.,Mu, Xingmin.,Li, Jiuyi.,Gao, Peng.,...&Chiew, Francis.(2019).Identifying terraces in the hilly and gully regions of the Loess Plateau in China.LAND DEGRADATION & DEVELOPMENT,13.
MLA Sun, Wenyi,et al."Identifying terraces in the hilly and gully regions of the Loess Plateau in China".LAND DEGRADATION & DEVELOPMENT (2019):13.

入库方式: OAI收割

来源:地理科学与资源研究所

浏览0
下载0
收藏0
其他版本

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。