Recent Advances of Hyperspectral Imaging Technology and Applications in Agriculture

Abstract

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.

A Review of Remote Sensing Challenges for Food Security with Respect to Salinity and Drought Threats

“…In the forward mode, RTMs simulate the vegetation spectrum based on known spectral signatures of vegetation biochemical and biophysical properties. Likewise, RTMs can retrieve vegetation properties from reflectance data in the inverse mode [72][73][74]. Indeed, RTM inversion has been successfully applied to monitor the changes in plant traits and reflectance upon drought [70].…”

Forecasting Plant and Crop Disease: An Explorative Study on Current Algorithms

“…To the best of our knowledge, this is the first study that focuses exclusively on predicting the symptoms of plant and crop diseases before they appear in the field or in an early stage with mild and minor lesions. A brief review of 10 scientific works related to pest detection and prediction is provided in [26], while other review works were conducted for different domains [22] and sub-domains [27][28][29][30] belonging to the agriculture sector.…”

Raman-Based Diagnostics of Biotic and Abiotic Stresses in Plants. A Review

“…There are several imaging techniques, such as hyperspectral imaging and thermography, that potentially can be used for an indirect detection of abiotic stresses in plants (Bauer et al, 2019;Caballero et al, 2020). These techniques allow for fast imaging of broad field areas and identification of "problematic areas" (Baena et al, 2017;Lu et al, 2020). However, these methods do not always possess required specificity.…”