Open AccessSpectral super-resolution reflectance retrieval from remotely sensed imaging spectrometer data
Author(s) -
Guorui Jia,
Andreas Hueni,
Dongxing Tao,
Ruonan Geng,
Michael E. Schaepman,
Haitao Zhao
Publication year - 2016
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.24.019905
Subject(s) - radiance , remote sensing , imaging spectrometer , spectrometer , hyperspectral imaging , spectral resolution , optics , atmospheric correction , imaging spectroscopy , full spectral imaging , environmental science , spectral bands , spectral imaging , near infrared spectroscopy , subpixel rendering , reflectivity , physics , pixel , spectral line , geology , astronomy
Existing atmospheric correction methods retrieve surface reflectance keeping the same nominal spectral response functions (SRFs) as that of the airborne/spaceborne imaging spectrometer radiance data. Since the SRFs vary dependent on sensor type and configuration, the retrieved reflectance of the same ground object varies from sensor to sensor as well. This imposes evident limitations on data validation efforts between sensors at surface reflectance level. We propose a method to retrieve super-resolution reflectance at the surface, by combining the first-principles atmospheric correction method FLAASH (fast line-of-sight atmospheric analysis of spectral hypercubes) with spectral super-resolution of imaging spectrometer radiance data. This approach is validated by comparing airborne AVIRIS (airborne visible/infrared imaging spectrometer) and spaceborne Hyperion data. The results demonstrate that the super-resolution reflectance in spectral bands with sufficiently high signal-to-noise ratio (SNR) serves as intermediate quantity to cross validate data originating from different imaging spectrometers.