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Simplified radiometric calibration for UAS-mounted multispectral sensor


Iqbal, F and Lucieer, A and Barry, K, Simplified radiometric calibration for UAS-mounted multispectral sensor, European Journal of Remote Sensing, 51, (1) pp. 301-313. ISSN 2279-7254 (2018) [Refereed Article]


Copyright Statement

Copyright 2018 The Authors. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0)

DOI: doi:10.1080/22797254.2018.1432293


Unmanned aircraft system (UAS) in combination with multispectral sensors stimulate the utilisation of site-specific technologies to manage crop production according to intrafield variability. Crop monitoring requires accurate calibration. However, radiometric calibration methods in practice are difficult to implement for UAS remote sensing as every single image requires correction due to smaller field of view and changes in light. Therefore, this paper proposes an easy radiometric calibration process for UAS-based miniature multiple camera array multispectral sensor. Results showed linear relationship between spectral reflectance and raw DN values with y-intercept value compatible with zero. It is the minimal possible surface reflectance recorded by sensor and can be used as a first point for equation development. The spectral quantification of white pseudo target was used as a second point of equation. Quantitative spectral information was generated by developing equation for every single image. An accuracy assessment was undertaken by comparing image-driven reflectance values against reflectance values measured in the field from soil and crop. The overall accuracy based on the root mean square error for the six bands ranged from 0.025% to 0.064%. The results of this study showed that the proposed method can be used for the calibration of UAS-based multispectral image.

Item Details

Item Type:Refereed Article
Keywords:radiometric calibration, empirical line, UAS, remote sensing
Research Division:Engineering
Research Group:Geomatic engineering
Research Field:Photogrammetry and remote sensing
Objective Division:Environmental Management
Objective Group:Terrestrial systems and management
Objective Field:Assessment and management of terrestrial ecosystems
UTAS Author:Iqbal, F (Mr Faheem Iqbal)
UTAS Author:Lucieer, A (Professor Arko Lucieer)
UTAS Author:Barry, K (Associate Professor Kara Barry)
ID Code:124564
Year Published:2018
Web of Science® Times Cited:55
Deposited By:Geography and Spatial Science
Deposited On:2018-02-27
Last Modified:2019-03-14
Downloads:131 View Download Statistics

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