The management and storage of spectroradiometer data are important issues, especially in regards of long-term use, data
quality and shareability. The SPECCHIO spectral database system developed at the Remote Sensing Laboratories (RSL)
provides a solution for the organized storage of spectral data and associated metadata and for the spectral processing
based on interactive, customizable and generic processing chains. Optimized data structures and graphical user interfaces
combined with intelligent file parsing routines enable the efficient entry of spectral data and metadata. The system can be
operated in a heterogeneous computing environment, offering multiuser access to a centralized database and enabling
easy data sharing within and even across research groups.
An empirical (target-) BRDF normalization method has been implemented for Imaging Spectrometry data processing,
following the approach of Kennedy, published in 1997. It is a simple, empirical method with the purpose of a rapid
technique, based on a least-squares quadratic curve fitting process. The algorithm is calculating correction factors in
either multiplicative or additive manner for each of the identified land cover classes, per spectral band and view angle
unit. Image pre-classification is essential for successful anisotropy normalization. This anisotropy normalization method
is a candidate to be used as baseline correction for future data products of APEX, a new airborne Imaging Spectrometer
suitable for simulation and inter-calibration of data from various other sensors.
A classification algorithm, being able to provide anisotropy class indexing that is optimized for the purpose of BRDF
normalization has to be used. In this study, the performance of the standard Spectral Angle Mapper (SAM) approach
with RSL's spectral database SPECCHIO attached is investigated. Due to its robustness regarding directional effects,
SAM classification is estimated to be the most efficient. Results of both the classification and the normalization process
are validated using two airborne image datasets from the HyMAP sensor, taken in 2004 over the "Vordemwald" test site
in northern Switzerland.
The Airborne Prism Experiment (APEX) is a hyperspectral instrument built in a Swiss - Belgian collaboration within the
ESA-PRODEX program. It aims at highest possible accuracy of its delivered surface reflectance image data products.
The atmospheric correction of hyperspectral imagery is a critical element of a complete processing chain towards
unbiased reflectance and for the creation of higher level products. As the first data of APEX is expected to become
available in 2009, an appropriate processing chain for higher level processing needs to be defined and evaluated.
Standard products have been identified in all application fields of hyperspectral imaging, i.e., geology, vegetation,
cryosphere, limnology and atmosphere. They are being implemented at the APEX science center. The according
processing procedures rely on data of well-defined processing states which range from calibrated at-sensor radiance to
(bihemispherical) spectral albedo.
In this paper, the atmospheric processing which is implemented as part of the automated data processing chain for level 2
in the APEX processing and archiving facility (PAF) at VITO (Mol, Belgium) is evaluated together with the
ATCOR-4 atmospheric correction program. The evaluation is done regarding flexibility, reflectance output
accuracy and processing efficiency. Two test data sets are taken for this purpose: a well-documented set of HYMAP data and a high resolution HYSPEX data set. Both data sets exhibit areas of overlap, which are taken for self-contained
analysis of the atmospheric correction procedure. The accuracy tests include plausibility checks on selected
regions of interest including a variety of known surfaces in the imagery. As some of the observed effects are related to
BRDF differences, the results also give an indication for the inaccuracy related to these reflectance anisotropies. Speed
measurements of the processing are then compared to the demand for operational processing of series of data acquisition.
Further comparison information is drawn from the by-products of atmospheric correction such as water vapor
The study shows performance and limitations of atmospheric correction using the state-of-the-art technology, which are
mainly found in the field of BRDF effects. This points towards improvements to be implemented in course of the further
development of the higher level processing chain for the APEX sensor.