Estimation of winter wheat above-ground biomass using unmanned aerial vehicle-based snapshot hyperspectral sensor and crop height improved models

Remote Sensing

Volumn 9, Issue 7, 2017, Pages

  Yue, Jibo ^a,b,c   Yang, Guijun ^a,d,e   Li, Changchun ^c   Li, Zhenhai ^a,d,e   Wang, Yanjie ^a,c,d   Feng, Haikuan ^a,d   Xu, Bo ^a,d,e  

^a Ministry of Agriculture Key Laboratory of Resource Remote Sensing and Digital Agriculture   (China)

^b NANJING UNIVERSITY   (China)

^c HENAN POLYTECHNIC UNIVERSITY   (China)

^d NATIONAL ENGINEERING RESEARCH CENTER FOR INFORMATION TECHNOLOGY IN AGRICULTURE   (China)

^e Beijing Engineering Research Center of Agricultural Internet of Things   (China)

Author keywords

Crop height; Hyperspectral image; Partial least squares regression; Unmanned aerial vehicle platforms; Winter wheat biomass

Indexed keywords

BIOMASS; CROPS; HYPERSPECTRAL IMAGING; LEAST SQUARES APPROXIMATIONS; REGRESSION ANALYSIS; SPECTROSCOPY; UNMANNED AERIAL VEHICLES (UAV); VEHICLES;

AGRICULTURAL MANAGEMENT; CROP HEIGHT; HYPERSPECTRAL REFLECTANCE; HYPERSPECTRAL SENSORS; PARTIAL LEAST SQUARES REGRESSION; PARTIAL LEAST SQUARES REGRESSION MODELS; RATIO VEGETATION INDICES; WINTER WHEAT;

PARAMETER ESTIMATION;

EID: 85022320211     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs9070708     Document Type: Article

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