A VNIR/SWIR atmospheric correction algorithm for hyperspectral imagery with adjacency effect

Radiometrically calibrated hyperspectral imagery contains information relat ing to the material properties of a surface target and the atmospheric laye rs between the surface target and the sensor. All atmospheric layers contai n well-mixed molecular gases, aerosol particles, and water vapor, and infor mation about these constituents may be extracted from hyperspectral imagery by using specialty designed algorithms. This research describes a total se nsor radiance-to-ground reflectance inversion program. An equivalent surfac e-pressure depth can be extracted using the Non-Linear Least-Squares Spectr al Fit (NLLSSF) technique on the 760-nm oxygen band. Two different methods, the Atmospheric Pre-Corrected Differential Absorption (APDA) and NLLSSF, c an be used to derive total columnar water vapor using the radiative transfe r model MODTRAN 4.0. Atmospheric visibility can be derived via the NLLSSF t echnique from the 400 - 700-nm, bands or using an approach that uses the up welled radiance fit from the Regression Intersection Method from 550 to 700 nm. A new numerical approximation technique is also introduced to calculat e the effect of the target surround on the sensor-received radiance. The re covered spectral reflectances for each technique are compared to reflectanc e panels with well-characterized ground truth. (C), 2001 Elsevier Science I nc. All rights reserved.