IGSNRR OpenIR
Relating Hyperspectral Vegetation Indices with Soil Salinity at Different Depths for the Diagnosis of Winter Wheat Salt Stress
Zhu, Kangying1,2; Sun, Zhigang1,2,3,4; Zhao, Fenghua1; Yang, Ting3,4; Tian, Zhenrong1; Lai, Jianbin1; Zhu, Wanxue1,2; Long, Buju5
2021
Source PublicationREMOTE SENSING
Volume13Issue:2Pages:21
Corresponding AuthorSun, Zhigang(sun.zhigang@igsnrr.ac.cn)
AbstractAbundant shallow underground brackish water resources could help in alleviating the shortage of fresh water resources and the crisis concerning agricultural water resources in the North China Plain. Improper brackish water irrigation will increase soil salinity and decrease the final yield due to salt stress affecting the crops. Therefore, it is urgent to develop a practical and low-cost method to monitor the soil salinity of brackish irrigation systems. Remotely sensed spectral vegetation indices (SVIs) of crops are promising proxies for indicating the salinity of the surface soil layer. However, there is still a challenge concerning quantitatively correlating SVIs with the salinity of deeper soil layers, in which crop roots are mainly distributed. In this study, a field experiment was conducted to investigate the relationship between SVIs and salinity measurements at four soil depths within six winter wheat plots irrigated using three salinity levels at the Yucheng Comprehensive Experimental Station of the Chinese Academy of Sciences during 2017-2019. The hyperspectral reflectance was measured during the grain-filling stage of winter wheat, since it is more sensitive to soil salinity during this period. The SVIs derived from the observed hyperspectral data of winter wheat were compared with the salinity at four soil depths. The results showed that the optimized SVIs, involving soil salt-sensitive blue, red-edge, and near-infrared wavebands, performed better when retrieving the soil salinity (R-2 >= 0.58, root mean square error (RMSE) <= 0.62 g/L), especially at the 30-cm depth (R-2 = 0.81, RMSE = 0.36 g/L). For practical applications, linear or quadratic models based on the screened SVIs in the form of normalized differential vegetation indices (NDVIs) could be used to retrieve soil salinity (R-2 >= 0.63, RMSE <= 0.62 g/L) at all soil depths and then diagnose salt stress in winter wheat. This could provide a practical technique for evaluating regional brackish water irrigation systems.
Keywordhyperspectral remote sensing soil salinity brackish water irrigation spectral vegetation index winter wheat
DOI10.3390/rs13020250
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[31570472] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA23050102] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA19040303] ; National Key Research and Development Program of China[2017YFC0503805] ; Key Projects of the Chinese Academy of Sciences[KJZD-SW-113]
Funding OrganizationNational Natural Science Foundation of China ; Strategic Priority Research Program of the Chinese Academy of Sciences ; National Key Research and Development Program of China ; Key Projects of the Chinese Academy of Sciences
WOS Research AreaEnvironmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS SubjectEnvironmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000611556400001
PublisherMDPI
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/136166
Collection中国科学院地理科学与资源研究所
Corresponding AuthorSun, Zhigang
Affiliation1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R China
2.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China
3.Chinese Acad Sci, Shandong Dongying Inst Geog Sci, Inst Geog Sci & Nat Resources Res, Dongying 257000, Peoples R China
4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, CAS Engn Lab Yellow River Delta Modern Agr, Beijing 100101, Peoples R China
5.China Agr Univ, Coll Resources & Environm Sci, Beijing 100193, Peoples R China
Recommended Citation
GB/T 7714
Zhu, Kangying,Sun, Zhigang,Zhao, Fenghua,et al. Relating Hyperspectral Vegetation Indices with Soil Salinity at Different Depths for the Diagnosis of Winter Wheat Salt Stress[J]. REMOTE SENSING,2021,13(2):21.
APA Zhu, Kangying.,Sun, Zhigang.,Zhao, Fenghua.,Yang, Ting.,Tian, Zhenrong.,...&Long, Buju.(2021).Relating Hyperspectral Vegetation Indices with Soil Salinity at Different Depths for the Diagnosis of Winter Wheat Salt Stress.REMOTE SENSING,13(2),21.
MLA Zhu, Kangying,et al."Relating Hyperspectral Vegetation Indices with Soil Salinity at Different Depths for the Diagnosis of Winter Wheat Salt Stress".REMOTE SENSING 13.2(2021):21.
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