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Review

Recent Advances of Hyperspectral Imaging Technology and Applications in Agriculture

1
Department of Geography, Geomatics and Environment, University of Toronto Mississauga, 3359 Mississauga Road, Mississauga, ON L5L 1C6, Canada
2
School of the Environment, University of Toronto, 33 Willcocks Street, Toronto, ON M5S 3E8, Canada
3
Agriculture and Agri-Food Canada, 960 Carling Avenue, Ottawa, ON K1A 0C6, Canada
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(16), 2659; https://doi.org/10.3390/rs12162659
Received: 12 July 2020 / Revised: 14 August 2020 / Accepted: 16 August 2020 / Published: 18 August 2020
(This article belongs to the Special Issue Hyperspectral Remote Sensing of Agriculture and Vegetation)
Remote sensing is a useful tool for monitoring spatio-temporal variations of crop morphological and physiological status and supporting practices in precision farming. In comparison with multispectral imaging, hyperspectral imaging is a more advanced technique that is capable of acquiring a detailed spectral response of target features. Due to limited accessibility outside of the scientific community, hyperspectral images have not been widely used in precision agriculture. In recent years, different mini-sized and low-cost airborne hyperspectral sensors (e.g., Headwall Micro-Hyperspec, Cubert UHD 185-Firefly) have been developed, and advanced spaceborne hyperspectral sensors have also been or will be launched (e.g., PRISMA, DESIS, EnMAP, HyspIRI). Hyperspectral imaging is becoming more widely available to agricultural applications. Meanwhile, the acquisition, processing, and analysis of hyperspectral imagery still remain a challenging research topic (e.g., large data volume, high data dimensionality, and complex information analysis). It is hence beneficial to conduct a thorough and in-depth review of the hyperspectral imaging technology (e.g., different platforms and sensors), methods available for processing and analyzing hyperspectral information, and recent advances of hyperspectral imaging in agricultural applications. Publications over the past 30 years in hyperspectral imaging technology and applications in agriculture were thus reviewed. The imaging platforms and sensors, together with analytic methods used in the literature, were discussed. Performances of hyperspectral imaging for different applications (e.g., crop biophysical and biochemical properties’ mapping, soil characteristics, and crop classification) were also evaluated. This review is intended to assist agricultural researchers and practitioners to better understand the strengths and limitations of hyperspectral imaging to agricultural applications and promote the adoption of this valuable technology. Recommendations for future hyperspectral imaging research for precision agriculture are also presented. View Full-Text
Keywords: precision agriculture; remote sensing; hyperspectral imaging; platforms and sensors; analytical methods; crop properties; soil characteristics; classification of agricultural features precision agriculture; remote sensing; hyperspectral imaging; platforms and sensors; analytical methods; crop properties; soil characteristics; classification of agricultural features
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MDPI and ACS Style

Lu, B.; Dao, P.D.; Liu, J.; He, Y.; Shang, J. Recent Advances of Hyperspectral Imaging Technology and Applications in Agriculture. Remote Sens. 2020, 12, 2659. https://doi.org/10.3390/rs12162659

AMA Style

Lu B, Dao PD, Liu J, He Y, Shang J. Recent Advances of Hyperspectral Imaging Technology and Applications in Agriculture. Remote Sensing. 2020; 12(16):2659. https://doi.org/10.3390/rs12162659

Chicago/Turabian Style

Lu, Bing, Phuong D. Dao, Jiangui Liu, Yuhong He, and Jiali Shang. 2020. "Recent Advances of Hyperspectral Imaging Technology and Applications in Agriculture" Remote Sensing 12, no. 16: 2659. https://doi.org/10.3390/rs12162659

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