Hyperspectral Imaging: A Review on UAV-Based Sensors, Data Processing and Applications for Agriculture and Forestry

Traditional imagery—provided, for example, by RGB and/or NIR sensors—has proven to be useful in many agroforestry applications. However, it lacks the spectral range and precision to profile materials and organisms that only hyperspectral sensors can provide. This kind of high-resolution spectroscopy...

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Main Authors: Telmo Adão, Jonáš Hruška, Luís Pádua, José Bessa, Emanuel Peres, Raul Morais, Joaquim João Sousa
Format: Article
Language:English
Published: MDPI AG 2017-10-01
Series:Remote Sensing
Subjects:
UAS
UAV
Online Access:https://www.mdpi.com/2072-4292/9/11/1110
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spelling doaj-fe6d2815f65c4499b3897bdff9b2515b2020-11-24T23:55:15ZengMDPI AGRemote Sensing2072-42922017-10-01911111010.3390/rs9111110rs9111110Hyperspectral Imaging: A Review on UAV-Based Sensors, Data Processing and Applications for Agriculture and ForestryTelmo Adão0Jonáš Hruška1Luís Pádua2José Bessa3Emanuel Peres4Raul Morais5Joaquim João Sousa6Institute for Systems and Computer Engineering, Technology and Science (INESC-TEC—Formerly INESC Porto), 4200-465 Porto, PortugalDepartment of Engineering, School of Sciences and Technology, University of Trás-os-Montes e Alto Douro, 5000-801 Vila Real, PortugalDepartment of Engineering, School of Sciences and Technology, University of Trás-os-Montes e Alto Douro, 5000-801 Vila Real, PortugalDepartment of Engineering, School of Sciences and Technology, University of Trás-os-Montes e Alto Douro, 5000-801 Vila Real, PortugalInstitute for Systems and Computer Engineering, Technology and Science (INESC-TEC—Formerly INESC Porto), 4200-465 Porto, PortugalInstitute for Systems and Computer Engineering, Technology and Science (INESC-TEC—Formerly INESC Porto), 4200-465 Porto, PortugalInstitute for Systems and Computer Engineering, Technology and Science (INESC-TEC—Formerly INESC Porto), 4200-465 Porto, PortugalTraditional imagery—provided, for example, by RGB and/or NIR sensors—has proven to be useful in many agroforestry applications. However, it lacks the spectral range and precision to profile materials and organisms that only hyperspectral sensors can provide. This kind of high-resolution spectroscopy was firstly used in satellites and later in manned aircraft, which are significantly expensive platforms and extremely restrictive due to availability limitations and/or complex logistics. More recently, UAS have emerged as a very popular and cost-effective remote sensing technology, composed of aerial platforms capable of carrying small-sized and lightweight sensors. Meanwhile, hyperspectral technology developments have been consistently resulting in smaller and lighter sensors that can currently be integrated in UAS for either scientific or commercial purposes. The hyperspectral sensors’ ability for measuring hundreds of bands raises complexity when considering the sheer quantity of acquired data, whose usefulness depends on both calibration and corrective tasks occurring in pre- and post-flight stages. Further steps regarding hyperspectral data processing must be performed towards the retrieval of relevant information, which provides the true benefits for assertive interventions in agricultural crops and forested areas. Considering the aforementioned topics and the goal of providing a global view focused on hyperspectral-based remote sensing supported by UAV platforms, a survey including hyperspectral sensors, inherent data processing and applications focusing both on agriculture and forestry—wherein the combination of UAV and hyperspectral sensors plays a center role—is presented in this paper. Firstly, the advantages of hyperspectral data over RGB imagery and multispectral data are highlighted. Then, hyperspectral acquisition devices are addressed, including sensor types, acquisition modes and UAV-compatible sensors that can be used for both research and commercial purposes. Pre-flight operations and post-flight pre-processing are pointed out as necessary to ensure the usefulness of hyperspectral data for further processing towards the retrieval of conclusive information. With the goal of simplifying hyperspectral data processing—by isolating the common user from the processes’ mathematical complexity—several available toolboxes that allow a direct access to level-one hyperspectral data are presented. Moreover, research works focusing the symbiosis between UAV-hyperspectral for agriculture and forestry applications are reviewed, just before the paper’s conclusions.https://www.mdpi.com/2072-4292/9/11/1110hyperspectralUASUAVhyperspectral sensorshyperspectral data processingagricultureforestryagroforestry
collection DOAJ
language English
format Article
sources DOAJ
author Telmo Adão
Jonáš Hruška
Luís Pádua
José Bessa
Emanuel Peres
Raul Morais
Joaquim João Sousa
spellingShingle Telmo Adão
Jonáš Hruška
Luís Pádua
José Bessa
Emanuel Peres
Raul Morais
Joaquim João Sousa
Hyperspectral Imaging: A Review on UAV-Based Sensors, Data Processing and Applications for Agriculture and Forestry
Remote Sensing
hyperspectral
UAS
UAV
hyperspectral sensors
hyperspectral data processing
agriculture
forestry
agroforestry
author_facet Telmo Adão
Jonáš Hruška
Luís Pádua
José Bessa
Emanuel Peres
Raul Morais
Joaquim João Sousa
author_sort Telmo Adão
title Hyperspectral Imaging: A Review on UAV-Based Sensors, Data Processing and Applications for Agriculture and Forestry
title_short Hyperspectral Imaging: A Review on UAV-Based Sensors, Data Processing and Applications for Agriculture and Forestry
title_full Hyperspectral Imaging: A Review on UAV-Based Sensors, Data Processing and Applications for Agriculture and Forestry
title_fullStr Hyperspectral Imaging: A Review on UAV-Based Sensors, Data Processing and Applications for Agriculture and Forestry
title_full_unstemmed Hyperspectral Imaging: A Review on UAV-Based Sensors, Data Processing and Applications for Agriculture and Forestry
title_sort hyperspectral imaging: a review on uav-based sensors, data processing and applications for agriculture and forestry
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2017-10-01
description Traditional imagery—provided, for example, by RGB and/or NIR sensors—has proven to be useful in many agroforestry applications. However, it lacks the spectral range and precision to profile materials and organisms that only hyperspectral sensors can provide. This kind of high-resolution spectroscopy was firstly used in satellites and later in manned aircraft, which are significantly expensive platforms and extremely restrictive due to availability limitations and/or complex logistics. More recently, UAS have emerged as a very popular and cost-effective remote sensing technology, composed of aerial platforms capable of carrying small-sized and lightweight sensors. Meanwhile, hyperspectral technology developments have been consistently resulting in smaller and lighter sensors that can currently be integrated in UAS for either scientific or commercial purposes. The hyperspectral sensors’ ability for measuring hundreds of bands raises complexity when considering the sheer quantity of acquired data, whose usefulness depends on both calibration and corrective tasks occurring in pre- and post-flight stages. Further steps regarding hyperspectral data processing must be performed towards the retrieval of relevant information, which provides the true benefits for assertive interventions in agricultural crops and forested areas. Considering the aforementioned topics and the goal of providing a global view focused on hyperspectral-based remote sensing supported by UAV platforms, a survey including hyperspectral sensors, inherent data processing and applications focusing both on agriculture and forestry—wherein the combination of UAV and hyperspectral sensors plays a center role—is presented in this paper. Firstly, the advantages of hyperspectral data over RGB imagery and multispectral data are highlighted. Then, hyperspectral acquisition devices are addressed, including sensor types, acquisition modes and UAV-compatible sensors that can be used for both research and commercial purposes. Pre-flight operations and post-flight pre-processing are pointed out as necessary to ensure the usefulness of hyperspectral data for further processing towards the retrieval of conclusive information. With the goal of simplifying hyperspectral data processing—by isolating the common user from the processes’ mathematical complexity—several available toolboxes that allow a direct access to level-one hyperspectral data are presented. Moreover, research works focusing the symbiosis between UAV-hyperspectral for agriculture and forestry applications are reviewed, just before the paper’s conclusions.
topic hyperspectral
UAS
UAV
hyperspectral sensors
hyperspectral data processing
agriculture
forestry
agroforestry
url https://www.mdpi.com/2072-4292/9/11/1110
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