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A Comparison of Crop Parameters Estimation Using Images from UAV-Mounted Snapshot Hyperspectral Sensor and High-Definition Digital Camera
Yue, Jibo1,2; Feng, Haikuan1; Jin, Xiuliang3; Yuan, Huanhuan1,4; Li, Zhenhai1; Zhou, Chengquan1; Yang, Guijun1; Tian, Qingjiu2
2018-07-01
Source PublicationREMOTE SENSING
ISSN2072-4292
Volume10Issue:7Pages:24
Corresponding AuthorFeng, Haikuan(fenghk@nercita.org.cn)
AbstractTimely and accurate estimates of crop parameters are crucial for agriculture management. Unmanned aerial vehicles (UAVs) carrying sophisticated cameras are very pertinent for this work because they can obtain remote-sensing images with higher temporal, spatial, and ground resolution than satellites. In this study, we evaluated (i) the performance of crop parameters estimates using a near-surface spectroscopy (350 similar to 2500 nm, 3 nm at 700 nm, 8.5 nm at 1400 nm, 6.5 nm at 2100 nm), a UAV-mounted snapshot hyperspectral sensor (450 similar to 950 nm, 8 nm at 532 nm) and a high-definition digital camera (Visible, R, G, B); (ii) the crop surface models (CSMs), RGB-based vegetation indices (VIs), hyperspectral-based VIs, and methods combined therefrom to make multi-temporal estimates of crop parameters and to map the parameters. The estimated leaf area index (LAI) and above-ground biomass (AGB) are obtained by using linear and exponential equations, random forest (RF) regression, and partial least squares regression (PLSR) to combine the UAV based spectral VIs and crop heights (from the CSMs). The results show that: (i) spectral VIs correlate strongly with LAI and AGB over single growing stages when crop height correlates positively with AGB over multiple growth stages; (ii) the correlation between the VIs multiplying crop height and AGB is greater than that between a single VI and crop height; (iii) the AGB estimate from the UAV-mounted snapshot hyperspectral sensor and high-definition digital camera is similar to the results from the ground spectrometer when using the combined methods (i.e., using VIs multiplying crop height, RF and PLSR to combine VIs and crop heights); and (iv) the spectral performance of the sensors is crucial in LAI estimates (the wheat LAI cannot be accurately estimated over multiple growing stages when using only crop height). The LAI estimates ranked from best to worst are ground spectrometer, UAV snapshot hyperspectral sensor, and UAV high-definition digital camera.
Keywordcrop surface model crop height aboveground biomass LAI random forest regression partial least squares regression
DOI10.3390/rs10071138
WOS KeywordLEAF-AREA INDEX ; VEGETATION INDEXES ; WINTER-WHEAT ; CHLOROPHYLL CONTENT ; REMOTE ESTIMATION ; REFLECTANCE ; CANOPY ; BIOMASS ; MODEL ; FEATURES
Indexed BySCI
Language英语
Funding ProjectNational Key Research and Development Program[2016YFD0300603] ; Natural Science Foundation of China[41601346] ; Natural Science Foundation of China[41601369] ; Natural Science Foundation of China[41501481] ; Natural Science Foundation of China[61661136003] ; Natural Science Foundation of China[41771370] ; Natural Science Foundation of China[41471285] ; Natural Science Foundation of China[41471351]
Funding OrganizationNational Key Research and Development Program ; Natural Science Foundation of China
WOS Research AreaRemote Sensing
WOS SubjectRemote Sensing
WOS IDWOS:000440332500161
PublisherMDPI
Citation statistics
Cited Times:10[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/54452
Collection中国科学院地理科学与资源研究所
Corresponding AuthorFeng, Haikuan
Affiliation1.Beijing Res Ctr Informat Technol Agr, Key Lab Quantitat Remote Sensing Agr, Minist Agr China, Beijing 100097, Peoples R China
2.Nanjing Univ, Int Inst Earth Syst Sci, Nanjing 210023, Jiangsu, Peoples R China
3.INRA, Environm Mediterraneen & Modelisat Agrohydrosyst, F-84914 Avignon, France
4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
Recommended Citation
GB/T 7714
Yue, Jibo,Feng, Haikuan,Jin, Xiuliang,et al. A Comparison of Crop Parameters Estimation Using Images from UAV-Mounted Snapshot Hyperspectral Sensor and High-Definition Digital Camera[J]. REMOTE SENSING,2018,10(7):24.
APA Yue, Jibo.,Feng, Haikuan.,Jin, Xiuliang.,Yuan, Huanhuan.,Li, Zhenhai.,...&Tian, Qingjiu.(2018).A Comparison of Crop Parameters Estimation Using Images from UAV-Mounted Snapshot Hyperspectral Sensor and High-Definition Digital Camera.REMOTE SENSING,10(7),24.
MLA Yue, Jibo,et al."A Comparison of Crop Parameters Estimation Using Images from UAV-Mounted Snapshot Hyperspectral Sensor and High-Definition Digital Camera".REMOTE SENSING 10.7(2018):24.
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