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A model for the rapid monitoring of soil salinization in the Yellow River Delta using Landsat 8 OLI imagery based on VI-SI feature space

文献类型：期刊论文

作者Guo, Bing2,3,4,5; Yang, Fei1; Han, Baomin3; Fan, Yewen4; Chen, Shuting3; Yang, Wenna3; Jiang, Lin3
刊名REMOTE SENSING LETTERS
出版日期2019-08-03
卷号10期号:8页码:796-805
ISSN号2150-704X
DOI10.1080/2150704X.2019.1610981
通讯作者Yang, Fei(1468007871@qq.com)
英文摘要Traditional monitoring methods often ignore the vegetation information, which has significantly indirect influence on the process of soil salinization. In this study, the vegetation indices-salinity indices (VI-SI) feature space was utilized to improve the inversion accuracy of soil salinity, while considering the bare soil and vegetation information. By fully considering the surface vegetation landscape in the Yellow River Delta, twelve VI-SI feature spaces were constructed, and two categories of soil salinization monitoring index were established. The experiment results showed that remote sensing monitoring index based on MSAVI-SI1 had the highest inversion accuracy (coefficient of determination (R-2) = 0.912), while that based on the ENDVI-SI4 feature space had the lowest (R-2 = 0.664). Therefore, the remote sensing monitoring index derived from MSAVI-SI can greatly improve the dynamic and periodical monitoring of soil salinity in the Yellow River Delta.
WOS关键词SALINITY ; INDEX
资助项目National Key R&D Program of China[2017YFA0604804] ; Natural Science Foundation of Shandong Province[ZR2018BD001] ; Open Fund of Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University[KLGIS2017A02] ; Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University[17I04] ; Project of Shandong Province Higher Educational Science and Technology Program[J18KA181]
WOS研究方向Remote Sensing ; Imaging Science & Photographic Technology
语种英语
WOS记录号WOS:000466114500001
出版者TAYLOR & FRANCIS LTD
资助机构National Key R&D Program of China ; Natural Science Foundation of Shandong Province ; Open Fund of Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University ; Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University ; Project of Shandong Province Higher Educational Science and Technology Program
源URL[http://ir.igsnrr.ac.cn/handle/311030/68616]  
专题中国科学院地理科学与资源研究所
通讯作者Yang, Fei
作者单位1.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
2.East China Normal Univ, Key Lab Geog Informat Sci, Minist Educ, Shanghai, Peoples R China
3.Shandong Univ Technol, Sch Civil Architectural Engn, Zibo, Shandong, Peoples R China
4.Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan, Hubei, Peoples R China
5.Hubei Univ, Hubei Key Lab Reg Dev & Environm Response, Wuhan, Hubei, Peoples R China
推荐引用方式
GB/T 7714		 Guo, Bing,Yang, Fei,Han, Baomin,et al. A model for the rapid monitoring of soil salinization in the Yellow River Delta using Landsat 8 OLI imagery based on VI-SI feature space[J]. REMOTE SENSING LETTERS,2019,10(8):796-805.
APA Guo, Bing.,Yang, Fei.,Han, Baomin.,Fan, Yewen.,Chen, Shuting.,...&Jiang, Lin.(2019).A model for the rapid monitoring of soil salinization in the Yellow River Delta using Landsat 8 OLI imagery based on VI-SI feature space.REMOTE SENSING LETTERS,10(8),796-805.
MLA Guo, Bing,et al."A model for the rapid monitoring of soil salinization in the Yellow River Delta using Landsat 8 OLI imagery based on VI-SI feature space".REMOTE SENSING LETTERS 10.8(2019):796-805.

入库方式： OAI收割

来源：地理科学与资源研究所

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