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

doi:10.1080/2150704X.2019.1610981

	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
	Guo, Bing 1,2,3,4; Yang, Fei 5; Han, Baomin 1; Fan, Yewen 3; Chen, Shuting 1; Yang, Wenna 1; Jiang, Lin 1
刊名	REMOTE SENSING LETTERS
	2019-08-03
卷号	10 期号:8 页码:796-805
ISSN号	2150-704X
DOI	10.1080/2150704X.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.
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关键词	SALINITY ; INDEX
WOS研究方向	Remote Sensing ; Imaging Science & Photographic Technology
语种	英语
出版者	TAYLOR & FRANCIS LTD
WOS记录号	WOS:000466114500001
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
内容类型	期刊论文
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.Shandong Univ Technol, Sch Civil Architectural Engn, Zibo, Shandong, Peoples R China 2.East China Normal Univ, Key Lab Geog Informat Sci, Minist Educ, Shanghai, Peoples R China 3.Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan, Hubei, Peoples R China 4.Hubei Univ, Hubei Key Lab Reg Dev & Environm Response, Wuhan, Hubei, Peoples R China 5.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, 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.