Article ID Journal Published Year Pages File Type
4460697 Remote Sensing of Environment 2007 12 Pages PDF
Abstract

Imaging spectrometers operating in the solar spectrum measure the upwelling reflected solar radiation, and are an important tool in the bio/geochemical characterization of the Earth system. Surface reflectance is usually the starting point for the retrieval of biophysical parameters from remote measurements. Reliable radiometric and spectral calibrations and accurate atmospheric correction are mandatory in the interpretation of the surface reflectance. A complete surface reflectance retrieval scheme specifically designed for ultra-fine spectral resolution (bandwidth from 10 to 2 nm) and spatial resolution (pixel size less than 10 m) imaging spectrometers is presented in this work. The assessment of the spectral calibration is coupled to the removal of the atmospheric distortion so that maps of surface reflectance are derived, as well as columnar water vapor (CWV) maps, estimations of aerosol optical thickness (AOT) and updated sensor gain coefficients and spectral calibration. Radiative transfer calculations are performed by an optimized version of the MODTRAN4 code, which is run before processing each image. The method is tested against Compact Airborne Spectrographic Imager (CASI) 1500 images acquired during the ESA SENtinel-2 and FLuorescence EXperiment (SEN2FLEX) campaigns held in the Barrax (La Mancha, Spain) study site during June and July 2005. A peak-to-peak spectral shift variation of up to 2.3 nm is detected in CASI. Concerning atmospheric products and surface reflectance retrievals, an extensive validation is performed using ground-based measurements. A good correlation between ground measurements and CASI-derived AOT and CWV is found, with a Pearson correlation coefficient r2 up to 0.71 and 0.74, respectively. The subsequent surface reflectance retrievals also hold a good correspondence with ground-based measurements.

Related Topics
Physical Sciences and Engineering Earth and Planetary Sciences Computers in Earth Sciences
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