Hyperspectral imagery applications for precision agriculture - a systemic survey

• Published in: Multimedia tools and applications Vol. 81; no. 2; pp. 3005 - 3038
• Main Authors: Sethy, Prabira Kumar, Pandey, Chanki, Sahu, Yogesh Kumar, Behera, Santi Kumari
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.01.2022; Springer Nature B.V
• Subjects: Agriculture; Computer Communication Networks; Computer Science; Data Structures and Information Theory; Hyperspectral imaging; Image segmentation; Imaging techniques; Machine vision; Multimedia Information Systems; Remote sensing; Special Purpose and Application-Based Systems; Precision Agriculture; Remote sensing; Hyperspectral imaging
• ISSN: 1380-7501; 1573-7721
• DOI: 10.1007/s11042-021-11729-8

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.