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Drones
Special Issues
Unmanned Aerial Vehicle Based Hyperspectral Imaging for Earth Observation
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Unmanned Aerial Vehicle Based Hyperspectral Imaging for Earth Observation

A special issue of Drones (ISSN 2504-446X). This special issue belongs to the section "Drones in Ecology".

Deadline for manuscript submissions: 25 July 2024 | Viewed by 3514

Special Issue Editors

Dr. J. Pablo Arroyo-Mora

E-Mail Website
Guest Editor
Flight Research Laboratory, National Research council of Canada, 1920 Research Private, U-61, Ottawa, ON K1V 2B1, Canada
Interests: UAV; airborne; hyperspectral; biodiversity; carbon; tropical; peatlands
Special Issues, Collections and Topics in MDPI journals
Dr. Margaret Kalacska

E-Mail Website
Guest Editor
Department of Geography, Université McGill, Montreal, QC, Canada
Interests: hyperspectral; satellite imagery; land cover change; signal processing; biodiversity; thermal imaging; UAV
Special Issues, Collections and Topics in MDPI journals
Dr. Niall Origo

E-Mail Website1 Website2
Guest Editor
National Physical Laboratory, Teddington, UK
Interests: remote sensing by laser beam; calibration; climatology; forestry; geophysical image processing; image reconstruction; radiometry; remote sensing; vegetation

Special Issue Information

Dear Colleagues,

Small form factor hyperspectral sensors (< 10 kg) (HSI) mounted on unmanned aerial vehicles (UAVs) have rapidly evolved over the last decade and now they have shown potential for next-phase Earth Observation applications—satellite products calibration/validation, forestry, agriculture, biodiversity, geology, inland and costal ecosystems, etc. Currently, UAV-HSI provides up to ~550 contiguous spectral bands, usually encompassing the visible and near infrared (400 nm–900 nm) and short-wave-infrared (900 nm–2500 nm) regions, capturing hyperspectral imagery at ultra-high spatial resolution, e.g., 1 cm–10 cm. For applications such as satellite product validation, UAV-HSI provides spectral and spatial details, which with proper protocol implementation, can replace field spectroscopy measurements in low accessability area and in some cases serve as a substitute for airborne hyperspectral imagery.

The goal of this Special Issue is to publish papers (original research articles and reviews) focused on the use of UAV-HSI for Earth Observation applications, following best practices and protocols to generate reliable hyperspectral imagery, i.e., geometrically and radiometrically corrected imagery. Given the wealth of information in hyperspectral datacubes, we invite articles reflecting novel analytical techniques, such as spectral indices. Moreover, novel aspects related to uncertainty, HSI geometric and radiometric characterisation and up-scaling methodologies are also encouraged.

This Special Issue will welcome manuscripts related to the following themes:

  • EO satellite product cal/val;
  • Vegetation—plant traits;
  • Forestry;
  • Agriculture;
  • Biodiversity;
  • Geology;
  • Inland and costal ecosystems;
  • UAV-HSI beyond spectral indices;
  • UAV-HSI best practice protocols.

We look forward to receiving your original research articles and reviews.

Sincerely

Dr. J. Pablo Arroyo-Mora
Dr. Margaret Kalacska
Dr. Niall Origo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Drones is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • unmanned aerial system (UAS)
  • unmanned aerial vehicle (UAV)
  • remotely piloted aerial system (RPAS)
  • cal/val
  • hyperspectral
  • earth observation applications
  • UAV-HSI uncertainty
  • radiometric assessment
  • geometric assessment
  • earth observation

Published Papers (1 paper)

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Research

24 pages, 7332 KiB  
Article
Development of a Novel Implementation of a Remotely Piloted Aircraft System over 25 kg for Hyperspectral Payloads
by Juan Pablo Arroyo-Mora, Margaret Kalacska, Oliver Lucanus, René Laliberté, Yong Chen, Janine Gorman, Alexandra Marion, Landen Coulas, Hali Barber, Iryna Borshchova, Raymond J. Soffer, George Leblanc, Daniel Lavigne, Ludovic Girard and Martin Bérubé
Drones 2023, 7(11), 652; https://doi.org/10.3390/drones7110652 - 27 Oct 2023
Viewed by 2970
Abstract
A main aspect limiting the operation of low-altitude remotely piloted aircraft systems (RPAS) over 25 kg, integrating pushbroom hyperspectral sensors, comes from the challenges related to aircraft performance (e.g., flight time) and regulatory aspects deterring the users from pushing beyond this weight limit. [...] Read more.
A main aspect limiting the operation of low-altitude remotely piloted aircraft systems (RPAS) over 25 kg, integrating pushbroom hyperspectral sensors, comes from the challenges related to aircraft performance (e.g., flight time) and regulatory aspects deterring the users from pushing beyond this weight limit. In this study, we showcase a novel implementation using the DJI Agras T30 as an aerial system for integrating an advanced hyperspectral imager (HSI, Hyspex VS-620). We present the design and fabrication approach applied to integrate the HSI payload, the key considerations for powering the HSI and its gimbal, and the results from vibration and wind tunnel tests. We also evaluate the system’s flight capacity and the HSI’s geometric and radiometric data qualities. The final weight of the T30 after the integration of the HSI payload and ancillary hardware was 43 kg. Our vibration test showed that the vibration isolator and the gimbal reduced the vibration transmission to above 15 Hz but also introduced a resonant peak at 9.6 Hz that led to vibration amplification in the low-frequency range near 9.6 Hz (on the order of an RMS of ~0.08 g). The wind tunnel test revealed that the system is stable up to nearly twice the wind speed rating of the manufacturer’s specifications (i.e., 8 m/s). Based on the requirements of the Canadian Special Flight Operations Certificate (RPAS > 25 kg) to land at a minimal battery level of ≥30%, the system was able to cover an area of ~2.25 ha at a speed of 3.7 m/s and an altitude of 100 m above ground level (AGL) in 7 min. The results with the HSI payload at different speeds and altitudes from 50 m to 100 m AGL show hyperspectral imagery with minimal roll–pitch–yaw artefacts prior to geocorrection and consistent spectra when compared to nominal reflectance targets. Finally, we discuss the steps followed to deal with the continuously evolving regulatory framework developed by Transport Canada for systems > 25 kg. Our work advances low-altitude HSI applications and encourages remote sensing scientists to take advantage of national regulatory frameworks, which ultimately improve the overall quality of HSI data and safety of operations with RPAS > 25 kg. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Based Hyperspectral Imaging for Earth Observation)
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