A Fast Smoothing Algorithm for Post-Processing of Surface Reflectance Spectra Retrieved from Airborne Imaging Spectrometer Data

Sensors

Bo-Cai Gao¹ 

[1]Remote Sensing Division, Code 7232, Naval Research Laboratory, Washington, DC 20375, USA

关键词: remote sensing;    sensors;    spectroscopy;    smoothing;    surface reflectance;   

DOI  :  10.3390/s131013879

来源: mdpi

【 摘 要 】

Surface reflectance spectra retrieved from remotely sensed hyperspectral imaging data using radiative transfer models often contain residual atmospheric absorption and scattering effects. The reflectance spectra may also contain minor artifacts due to errors in radiometric and spectral calibrations. We have developed a fast smoothing technique for post-processing of retrieved surface reflectance spectra. In the present spectral smoothing technique, model-derived reflectance spectra are first fit using moving filters derived with a cubic spline smoothing algorithm. A common gain curve, which contains minor artifacts in the model-derived reflectance spectra, is then derived. This gain curve is finally applied to all of the reflectance spectra in a scene to obtain the spectrally smoothed surface reflectance spectra. Results from analysis of hyperspectral imaging data collected with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data are given. Comparisons between the smoothed spectra and those derived with the empirical line method are also presented.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.