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Quantitative remote sensing at ultra-high resolution with UAV spectroscopy: A review of sensor technology, measurement procedures, and data correctionworkflows

Citation

Aasen, H and Honkavaara, E and Lucieer, A and Zarco-Tejada, PJ, Quantitative remote sensing at ultra-high resolution with UAV spectroscopy: A review of sensor technology, measurement procedures, and data correctionworkflows, Remote Sensing, 10, (7) Article 1091. ISSN 2072-4292 (2018) [Refereed Article]


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Copyright 2018 The Authors. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/

DOI: doi:10.3390/rs10071091

Abstract

In the last 10 years, development in robotics, computer vision, and sensor technology has provided new spectral remote sensing tools to capture unprecedented ultra-high spatial and high spectral resolution with unmanned aerial vehicles (UAVs). This development has led to a revolution in geospatial data collection in which not only few specialist data providers collect and deliver remotely sensed data, but a whole diverse community is potentially able to gather geospatial data that fit their needs. However, the diversification of sensing systems and user applications challenges the common application of good practice procedures that ensure the quality of the data. This challenge can only be met by establishing and communicating common procedures that have had demonstrated success in scientific experiments and operational demonstrations. In this review, we evaluate the state-of-the-art methods in UAV spectral remote sensing and discuss sensor technology, measurement procedures, geometric processing, and radiometric calibration based on the literature and more than a decade of experimentation. We follow the 'journey' of the reflected energy from the particle in the environment to its representation as a pixel in a 2D or 2.5D map, or 3D spectral point cloud. Additionally, we reflect on the current revolution in remote sensing, and identify trends, potential opportunities, and limitations.

Item Details

Item Type:Refereed Article
Keywords:imaging spectroscopy, spectral, unmanned aerial vehicles, unmanned aerial systems (UAS), Remotely Piloted Aircraft Systems (RPAS), drone, calibration, hyperspectral, multispectral, low-altitude, remote sensing, sensors, 2D imager, pushbroom, snapshot
Research Division:Engineering
Research Group:Geomatic engineering
Research Field:Photogrammetry and remote sensing
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in the environmental sciences
UTAS Author:Lucieer, A (Professor Arko Lucieer)
ID Code:131175
Year Published:2018
Web of Science® Times Cited:282
Deposited By:Geography and Spatial Science
Deposited On:2019-03-06
Last Modified:2019-04-24
Downloads:39 View Download Statistics

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