Retrieving winter wheat leaf area index based on unmanned aerial vehicle hyperspectral remote sensing

Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering

Volumn 32, Issue 22, 2016, Pages 113-120

  Gao, Lin ^a,b,c,d,e   Yang, Guijun ^a,b,c,d   Yu, Haiyang ^a,b,c,d   Xu, Bo ^a,b,c,d   Zhao, Xiaoqing ^a,b,c,d   Dong, Jinhui ^a,b,c,d,f   Ma, Yabin ^a,b,c,d  

^a BEIJING RESEARCH CENTER FOR INFORMATION TECHNOLOGY IN AGRICULTURE   (China)

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

^c AGRO ENVIRONMENTAL PROTECTION INSTITUTE   (China)

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

^e NANJING UNIVERSITY   (China)

^f HENAN POLYTECHNIC UNIVERSITY   (China)

Author keywords

Leaf area index; Red edge parameters; Remote sensing; Sensors; Spectral indices; Unmanned aerial vehicle

Indexed keywords

AGRICULTURE; CROPS; LINEAR REGRESSION; NONDESTRUCTIVE EXAMINATION; OPTICAL WAVEGUIDES; REGRESSION ANALYSIS; SENSORS; SPECTROMETERS; UNMANNED AERIAL VEHICLES (UAV); VEGETATION; VEHICLES;

HYPERSPECTRAL REMOTE SENSING; HYPERSPECTRAL REMOTE SENSING DATA; HYPERSPECTRAL REMOTE SENSING TECHNOLOGY; LEAF AREA INDEX; NORMALIZED DIFFERENCE VEGETATION INDEX; RED EDGE PARAMETERS; REMOTE SENSING TECHNIQUES; SPECTRAL INDICES;

REMOTE SENSING;

EID: 84999277863     PISSN: 10026819     EISSN: None     Source Type: Journal    
DOI: 10.11975/j.issn.1002-6819.2016.22.016     Document Type: Article

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