IGSNRR OpenIR
Examining view angle effects on leaf N estimation in wheat using field reflectance spectroscopy
Song, Xiao1,2; Feng, Wei1; He, Li1; Xu, Duanyang3; Zhang, Hai-Yan1; Li, Xiao1; Wang, Zhi-Jie4; Coburn, Craig A.4; Wang, Chen-Yang1; Guo, Tian-Cai1
2016-12-01
Source PublicationISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
ISSN0924-2716
Volume122Pages:57-67
Corresponding AuthorFeng, Wei(fengwei78@126.com) ; Guo, Tian-Cai(tcguo888@sina.com)
AbstractReal-time, nondestructive monitoring of crop nitrogen (N) status is a critical factor for precision N management during wheat production. Over a 3-year period, we analyzed different wheat cultivars grown under different experimental conditions in China and Canada and studied the effects of viewing angle on the relationships between various vegetation indices (VIs) and leaf nitrogen concentration (LNC) using hyperspectral data from 11 field experiments. The objective was to improve the prediction accuracy by minimizing the effects of viewing angle on LNC estimation to construct a novel vegetation index (VI) for use under different experimental conditions. We examined the stability of previously reported optimum VIs obtained from 13 traditional indices for estimating LNC at 13 viewing zenith angles (VZAs) in the solar principal plane (SPP). Backscattering direction showed better index performance than forward scattering direction. Red-edge VIs including modified normalized difference vegetation index (mND705), ratio index within the red edge region (RI-1dB) and normalized difference red edge index (NDRE) were highly correlated with LNC, as confirmed by high R-2 determination coefficients. However, these common VIs tended to saturation, as the relationships strongly depended on experimental conditions. To overcome the influence of VZA on VIs, the chlorophyll-and LNC-sensitive NDRE index was divided by the floating-position water band index (FWBI) to generate the integrated narrow-band vegetation index. The highest correlation between the novel NDRE/FWBI parameter and LNC (R-2 = 0.852) occurred at -10, while the lowest correlation (R-2 = 0.745) occurred at 60 degrees. NDRE/FWBI was more highly correlated with LNC than existing commonly used VIs at an identical viewing zenith angle. Upon further analysis of angle combinations, our novel VI exhibited the best performance, with the best prediction accuracy at 0 to 20 (R-2 = 0.838, RMSE = 0.360) and relatively good accuracy at 0 to 30 (R-2 = 0.835, RMSE = 0.366). As it is possible to monitor plant N status over a wide range of angles using portable spectrometers, viewing angles of as much as 0 to 30 are common. Consequently, we developed a united model across angles of 0 to 30 to reduce the effects of viewing angle on LNC prediction in wheat. The proposed combined NDRE/FWBI parameter, designated the wide-angle-adaptability nitrogen index (WANI), is superior for estimating LNC in wheat on a regional scale in China and Canada. (C) 2016 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.
KeywordWheat Viewing angle Vegetation indices Leaf N concentration Monitoring model
DOI10.1016/j.iprsjprs.2016.10.002
WOS KeywordHYPERSPECTRAL VEGETATION INDEXES ; RED-EDGE ; SPECTRAL REFLECTANCE ; CHLOROPHYLL CONTENT ; WINTER-WHEAT ; PRECISION AGRICULTURE ; CANOPY REFLECTANCE ; NITROGEN STATUS ; HIGHER-PLANTS ; AREA INDEX
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[31671624] ; Program for Science & Technology Innovation Talents in Universities of Henan Province[17HASTIT036] ; Key Scientific and Technological Projects of Henan Province[152102410031] ; Key Scientific Research Project of Colleges and Universities in Henan Province, China[15A210031]
Funding OrganizationNational Natural Science Foundation of China ; Program for Science & Technology Innovation Talents in Universities of Henan Province ; Key Scientific and Technological Projects of Henan Province ; Key Scientific Research Project of Colleges and Universities in Henan Province, China
WOS Research AreaPhysical Geography ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS SubjectGeography, Physical ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000390719600005
PublisherELSEVIER SCIENCE BV
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/65406
Collection中国科学院地理科学与资源研究所
Corresponding AuthorFeng, Wei; Guo, Tian-Cai
Affiliation1.Henan Agr Univ, Collaborat Innovat Ctr Henan Grain Crops, Natl Engn Res Ctr Wheat, 63 Nongye Rd, Zhengzhou 450002, Henan, Peoples R China
2.Henan Acad Agr Sci, Inst Plant Nutrient & Environm Resources, Zhengzhou 450002, Henan, Peoples R China
3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
4.Univ Lethbridge, Dept Phys & Astron, 4401 Univ Dr West, Lethbridge, AB T1K 3M4, Canada
Recommended Citation
GB/T 7714
Song, Xiao,Feng, Wei,He, Li,et al. Examining view angle effects on leaf N estimation in wheat using field reflectance spectroscopy[J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,2016,122:57-67.
APA Song, Xiao.,Feng, Wei.,He, Li.,Xu, Duanyang.,Zhang, Hai-Yan.,...&Guo, Tian-Cai.(2016).Examining view angle effects on leaf N estimation in wheat using field reflectance spectroscopy.ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,122,57-67.
MLA Song, Xiao,et al."Examining view angle effects on leaf N estimation in wheat using field reflectance spectroscopy".ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 122(2016):57-67.
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