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Empirical line calibration of WorldView-2 satellite imagery to reflectance data: using quadratic prediction equations


Staben, GW and Pfitzner, K and Bartolo, R and Lucieer, A, Empirical line calibration of WorldView-2 satellite imagery to reflectance data: using quadratic prediction equations, Remote Sensing Letters, 3, (6) pp. 521-530. ISSN 2150-704X (2012) [Refereed Article]

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Copyright Statement

Copyright 2011 Crown Copyright

DOI: doi:10.1080/01431161.2011.609187


Obtaining accurate quantitative spectral information from raw multispectral satellite imagery requires the conversion of raw digital numbers (DNs) to units of radiance or reflectance. In this article, an empirical line method is used to calibrate WorldView-2 satellite imagery to surface reflectance. Prediction equations for the eight multispectral bands were developed using a non-linear relationship between sensor top-of-atmosphere spectral radiance (LTOA) and surface reflectance values obtained from seven field targets. An accuracy assessment was undertaken by comparing image reflectance values against the surface reflectance values of 19 independent field targets. The overall accuracy based on the root mean square error (RMSE) for the eight bands ranged between 0.94% and 2.14% with the greatest variance in the near-infrared (NIR) bands. The results of this study show that empirical line methods can be used to successfully calibrate WorldView-2 satellite imagery to reflectance data.

Item Details

Item Type:Refereed Article
Keywords:multispectral satellite imagery, radiance, reflectance, top-of-atmosphere spectral radiance, surface reflectance, image reflectance value, WorldView-2 satellite imagery
Research Division:Earth Sciences
Research Group:Physical Geography and Environmental Geoscience
Research Field:Physical Geography and Environmental Geoscience not elsewhere classified
Objective Division:Environment
Objective Group:Ecosystem Assessment and Management
Objective Field:Ecosystem Assessment and Management at Regional or Larger Scales
UTAS Author:Staben, GW (Mr Grant Staben)
UTAS Author:Lucieer, A (Professor Arko Lucieer)
ID Code:76527
Year Published:2012
Web of Science® Times Cited:16
Deposited By:Geography and Environmental Studies
Deposited On:2012-03-08
Last Modified:2017-10-24
Downloads:8 View Download Statistics

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