Monitoring cotton (Gossypium hirsutum L.) leaf ion content and leaf water content in saline soil with hyperspectral reflectance

被引：19

作者：

Zhang, Lei ^{[1
,2
]}

Zhou, Zhiguo ^{[1
]}

Zhang, Guowei ^{[1
]}

Meng, Yali ^{[1
]}

Chen, Binglin ^{[1
]}

Wang, Youhua ^{[1
]}

机构：

[1] Nanjing Agr Univ, Key Lab Crop Growth Regulat, Minist Agr, Nanjing 210095, Jiangsu, Peoples R China

[2] Chinese Acad Agr Sci, Inst Cotton Res, State Key Lab Cotton Biol, Anyang 455100, Henan, Peoples R China

来源：

EUROPEAN JOURNAL OF REMOTE SENSING | 2014年 / 47卷

基金：

国家高技术研究发展计划(863计划); 中国国家自然科学基金;

关键词：

cotton; saline soil; hyperspectral reflectance; ion content; leaf water content; monitoring model; NEAR-INFRARED SPECTROSCOPY; SPECTRAL ABSORPTION FEATURES; SALT TOLERANCE; WINTER-WHEAT; VEGETATION; INDEXES; STRESS; LEAVES; NM; BIOMASS;

D O I：

10.5721/EuJRS20144733

中图分类号：

TP7 [遥感技术];

学科分类号：

081102 ; 0816 ; 081602 ; 083002 ; 1404 ;

摘要：

The objectives of this study were to establish quantitative models for monitoring the leaf ion and water content under saline conditions. The best spectral indices for estimating leaf ion content and leaf water content were found to be normalized difference spectral indices (NDSI (R-1340, R-2306)), ratio spectral indices (RSI (R-2306, R-1347)) for K+, NDSI (R-1346, R-2276), RSI (R-2276, R-1343) for Na+, NDSI (R-1380, R-2307), RSI (R-2306, R-1350) for Ca2+; NDSI (R-1200, R-2211), RSI (R-2202, R-1361) for Mg2+; NDSI (R-1300, R-2250), RSI (R-2264, R-1335) for Cl-; NDSI (R-1154, R-2317), RSI (R-2317, R-1154) for SO42- and NDSI (R-1222, R-2264), RSI (R-2264, R-1321) for RWC, respectively. The regression models based on the above spectral indices were formulated with R-2 greater than 0.46. The high fit between the measured and estimated values indicate that the present models based on RSI could be used to estimate leaf ion and water content feasibly under saline conditions.

引用

页码：593 / 610

页数：18

共 52 条

[41] MEASUREMENT OF THE MAGNESIUM CONCENTRATION IN PERENNIAL RYEGRASS (LOLIUM-PERENNE) USING NEAR-INFRARED REFLECTANCE SPECTROSCOPY [J].

SMITH, KF ;

WILLIS, SE ;

FLINN, PC .

AUSTRALIAN JOURNAL OF AGRICULTURAL RESEARCH, 1991, 42 (08) :1399-1404

[42]

The MathWorks Inc., 2000, MATLAB 6 0

[43]

Tian Q, 2001, INT J REMOTE SENS, V22, P2329, DOI 10.1080/014311601300229845

[44] REMOTE-SENSING OF LEAF WATER-CONTENT IN THE NEAR-INFRARED [J].

TUCKER, CJ .

REMOTE SENSING OF ENVIRONMENT, 1980, 10 (01) :23-32

[45]

Wang GQ, 2004, SPECTROSC SPECT ANAL, V24, P1540

[46] Predicting vegetation water content in wheat using normalized difference water indices derived from ground measurements [J].

Wu, Chaoyang ;

Niu, Zheng ;

Tang, Quan ;

Huang, Wenjiang .

JOURNAL OF PLANT RESEARCH, 2009, 122 (03) :317-326

[47] Exploring hyperspectral bands and estimation indices for leaf nitrogen accumulation in wheat [J].

Yao, Xia ;

Zhu, Yan ;

Tian, YongChao ;

Feng, Wei ;

Cao, WeiXing .

INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2010, 12 (02) :89-100

[48] Remote sensing of vegetation water content from equivalent water thickness using satellite imagery [J].

Yilmaz, M. Tugrul ;

Hunt, E. Raymond, Jr. ;

Jackson, Thomas J. .

REMOTE SENSING OF ENVIRONMENT, 2008, 112 (05) :2514-2522

[49]

Zhang Guo-wei, 2011, Yingyong Shengtai Xuebao, V22, P2045

[50] Monitoring the leaf water content and specific leaf weight of cotton (Gossypium hirsutum L.) in saline soil using leaf spectral reflectance [J].

Zhang, Lei ;

Zhou, Zhiguo ;

Zhang, Guowei ;

Meng, Yali ;

Chen, Binglin ;

Wang, Youhua .

EUROPEAN JOURNAL OF AGRONOMY, 2012, 41 :103-117

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