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      Underwater Hyperspectral Imaging Technology and Its Applications for Detecting and Mapping the Seafloor: A Review

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          Abstract

          Common methods of ocean remote sensing and seafloor surveying are mainly carried out by airborne and spaceborne hyperspectral imagers. However, the water column hinders the propagation of sunlight to deeper areas, thus limiting the scope of observation. As an emerging technology, underwater hyperspectral imaging (UHI) is an extension of hyperspectral imaging technology in air conditions, and is undergoing rapid development for applications in shallow and deep-sea environments. It is a close-range, high-resolution approach for detecting and mapping the seafloor. In this paper, we focus on the concepts of UHI technology, covering imaging systems and the correction methods of eliminating the water column’s influence. The current applications of UHI, such as deep-sea mineral exploration, benthic habitat mapping, and underwater archaeology, are highlighted to show the potential of this technology. This review can provide an introduction and overview for those working in the field and offer a reference for those searching for literature on UHI technology.

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          Most cited references91

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          Imaging spectrometry for Earth remote sensing.

          Imaging spectrometry, a new technique for the remote sensing of the earth, is now technically feasible from aircraft and spacecraft. The initial results show that remote, direct identification of surface materials on a picture-element basis can be accomplished by proper sampling of absorption features in the reflectance spectrum. The airborne and spaceborne sensors are capable of acquiring images simultaneously in 100 to 200 contiguous spectral bands. The ability to acquire laboratory-like spectra remotely is a major advance in remote sensing capability. Concomitant advances in computer technology for the reduction and storage of such potentially massive data sets are at hand, and new analytic techniques are being developed to extract the full information content of the data. The emphasis on the deterministic approach to multispectral data analysis as opposed to the statistical approaches used in the past should stimulate the development of new digital image-processing methodologies.
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            Perspectives for Remote Sensing with Unmanned Aerial Vehicles in Precision Agriculture

            Remote sensing with unmanned aerial vehicles (UAVs) is a game-changer in precision agriculture. It offers unprecedented spectral, spatial, and temporal resolution, but can also provide detailed vegetation height data and multiangular observations. In this article, we review the progress of remote sensing with UAVs in drought stress, in weed and pathogen detection, in nutrient status and growth vigor assessment, and in yield prediction. To transfer this knowledge to everyday practice of precision agriculture, future research should focus on exploiting the complementarity of hyperspectral or multispectral data with thermal data, on integrating observations into robust transfer or growth models rather than linear regression models, and on combining UAV products with other spatially explicit information.
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              On the Use of Unmanned Aerial Systems for Environmental Monitoring

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                Author and article information

                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                02 September 2020
                September 2020
                : 20
                : 17
                : 4962
                Affiliations
                [1 ]Key Laboratory of Laser & Infrared System, Ministry of Education, Shandong University, Qingdao 266237, China; liu_bh@ 123456mail.sdu.edu.cn (B.L.); zhaojunliu@ 123456sdu.edu.cn (Z.L.); yfli@ 123456sdu.edu.cn (Y.L.); zhigang@ 123456sdu.edu.cn (Z.Z.)
                [2 ]School of Information Science & Engineering and Shandong Provincial Key Laboratory of Laser Technology and Application, Shandong University, Qingdao 266237, China; jh_he@ 123456mail.sdu.edu.cn
                [3 ]Center for Optics Research and Engineering, Shandong University, Qingdao 266237, China
                [4 ]National Deep Sea Center, No.6, Xianxialing Road, Qingdao 266061, China; dzj@ 123456ndsc.org.cn
                Author notes
                [* ]Correspondence: shaojiemen@ 123456sdu.edu.cn
                Author information
                https://orcid.org/0000-0002-9845-7900
                https://orcid.org/0000-0003-4654-0857
                https://orcid.org/0000-0002-5164-4055
                Article
                sensors-20-04962
                10.3390/s20174962
                7506868
                32887344
                012c7ba0-14e2-4fb9-96bb-e088f4c2e6bb
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 29 July 2020
                : 31 August 2020
                Categories
                Review

                Biomedical engineering
                underwater hyperspectral imaging,multispectral,marine mineral exploration,benthic habitat mapping,underwater archaeology

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