Hyperspectral imagery applications for precision agriculture-a systemic survey

被引:49
作者
Sethy, Prabira Kumar [1 ]
Pandey, Chanki [2 ]
Sahu, Yogesh Kumar [2 ]
Behera, Santi Kumari [3 ]
机构
[1] Sambalpur Univ, Dept Elect, Sambalpur, Odisha, India
[2] Govt Engn Coll, Dept ET&T Engn, Jagdalpur, CG, India
[3] VSSUT, Dept Comp Sci & Engn, Burla, Odisha, India
基金
英国科研创新办公室;
关键词
Hyperspectral imaging; Precision Agriculture; Remote sensing; PRINCIPAL COMPONENT ANALYSIS; NEAR-INFRARED SPECTROSCOPY; SINGLE MAIZE SEED; VARIABLE SELECTION; VEGETATION INDEXES; MOISTURE-CONTENT; NITROGEN-CONTENT; RAPID ASSESSMENT; PROTEIN-CONTENT; PREDICTION;
D O I
10.1007/s11042-021-11729-8
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Hyperspectral imaging has been extensively investigated as an emerging, promising technique for measuring the quality and protection of horticultural and agricultural products over the past 20 years. This technology evolved from remote sensing and joins the machine vision and point spectroscopy realms to provide superior image segmentation for defect and contamination detection. In this paper, we have incorporated spatial and spectral information into hyperspectral imaging techniques. It can efficiently and non-destructively provide helpful information on both external physical and internal chemical characteristics of agricultural and food products. This paper has reviewed the sum of crucial aspect applications of hyperspectral imaging in precision agriculture. This paper reviews hyperspectral imaging's current and past development in the agriculture industry, such as classification, chromatic, climatic, convergence, etc. This analysis aims to refer to potential work on key issues and promote deployed end-user solutions to fulfill the existing global sustainability objectives.
引用
收藏
页码:3005 / 3038
页数:34
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