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Minimizing reflectance anisotropy effects in airborne spectroscopy data using Ross-Li model inversion with continuous field land cover stratification


Weyermann, Jörg; Kneubühler, Mathias; Schläpfer, Daniel; Schaepman, Michael E (2015). Minimizing reflectance anisotropy effects in airborne spectroscopy data using Ross-Li model inversion with continuous field land cover stratification. IEEE Transactions on Geoscience and Remote Sensing, 53(11):5814-5823.

Abstract

The spectral and radiometric quality of airborne imaging spectrometer data is affected by the anisotropic re- flectance behavior of the imaged surface. Illumination and ob- servation angle-dependent patterns of surface reflected radiation propagate into products, hinder quantitative assessment of bio- physical/biochemical parameters, and decrease the comparability of data from multiple flight lines. The Ross–Li model, originally developed for multiangular observations, can be inverted to esti- mate and correct for surface anisotropy effects. This requires land cover be stratified into distinct types of scattering behavior. When the observations subsumed in these classes cover a range of view angles, a pseudo multiangular view on the surface can be employed to invert the Ross–Li model. A discrete land cover classification, however, bears the risk of inappropriate scattering correction resulting in spatial artifacts in the corrected data, predominantly in transition regions of two land cover types (e.g., soil and sparse vegetation with varying fractions). We invert the Ross–Li model on continuous land cover fraction layers. We decompose land cover in dominating structural types using linear spectral unmix- ing. Ross–Li kernel weights and formulations are estimated for each type independently; the correction is then applied pixel-wise according to the fractional distribution. The corrected Airborne Prism EXperiment imaging spectrometer data show significant reduction of anisotropic reflectance effects of up to 90% (average 60% to 75%, p = 0.05), measured in the overlapping regions of adjacent flight lines. No spatial artifacts or spectral irregularities are observed after correction.

Abstract

The spectral and radiometric quality of airborne imaging spectrometer data is affected by the anisotropic re- flectance behavior of the imaged surface. Illumination and ob- servation angle-dependent patterns of surface reflected radiation propagate into products, hinder quantitative assessment of bio- physical/biochemical parameters, and decrease the comparability of data from multiple flight lines. The Ross–Li model, originally developed for multiangular observations, can be inverted to esti- mate and correct for surface anisotropy effects. This requires land cover be stratified into distinct types of scattering behavior. When the observations subsumed in these classes cover a range of view angles, a pseudo multiangular view on the surface can be employed to invert the Ross–Li model. A discrete land cover classification, however, bears the risk of inappropriate scattering correction resulting in spatial artifacts in the corrected data, predominantly in transition regions of two land cover types (e.g., soil and sparse vegetation with varying fractions). We invert the Ross–Li model on continuous land cover fraction layers. We decompose land cover in dominating structural types using linear spectral unmix- ing. Ross–Li kernel weights and formulations are estimated for each type independently; the correction is then applied pixel-wise according to the fractional distribution. The corrected Airborne Prism EXperiment imaging spectrometer data show significant reduction of anisotropic reflectance effects of up to 90% (average 60% to 75%, p = 0.05), measured in the overlapping regions of adjacent flight lines. No spatial artifacts or spectral irregularities are observed after correction.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Language:English
Date:2015
Deposited On:09 Oct 2015 15:22
Last Modified:05 Apr 2016 19:26
Publisher:Institute of Electrical and Electronics Engineers
ISSN:0196-2892
Publisher DOI:https://doi.org/10.1109/TGRS.2015.2415872

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