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Atmospheric correction of imaging spectroscopy data using shadow-based quantification of aerosol scattering effects

Schläpfer, Daniel; Richter, Rudolf (2017). Atmospheric correction of imaging spectroscopy data using shadow-based quantification of aerosol scattering effects. EARSeL eProceedings, 16(1):21-28.

Abstract

The atmospheric correction accuracy strongly depends on the correct estimate of the aerosol scattering effects. This paper shows first results of a new aerosol optical thickness inversion method and its use for improved atmospheric correction of high spatial resolution imaging spectroscopy data. The approach uses small scale shadow pixels for the determination of the atmospheric scattering by inverting the shadow correction within the ATCOR® atmospheric compensation method. The detection of shadow pixels is done by a blue to red ratio which is further adjusted by the near infrared band in order to take the vegetation bias into account. On high resolution instruments with resolutions below 5 m, a decent quantity of shaded pixels can be found by this method in a reliable way. Using this shadow mask, the aerosol inversion is done. The aerosol contents are varied in a way that retrieves a correction of shaded areas to a brightness comparable to non-shaded areas, leading to the best fitting aerosol amount. The shadow based aerosol optical thickness (SHAOT) method is tested on APEX and HYSPEX airborne imaging spectroscopy data. It can be shown that the atmospheric compensation using the such derived aerosol contents are significantly improved in comparison to standard correction techniques.

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Scopus Subject Areas:Life Sciences > Forestry
Physical Sciences > Instrumentation
Physical Sciences > Management, Monitoring, Policy and Law
Language:English
Date:2017
Deposited On:12 Dec 2017 16:28
Last Modified:20 Aug 2024 03:40
Publisher:European Association of Remote Sensing Laboratories
ISSN:1729-3782
OA Status:Gold
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.12760/01-2017-1-03
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  • Language: English
  • Licence: Creative Commons: Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)

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