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.
Hyperspectral imaging (HSI) sensors suffer from spatial misregistration, an artifact that prevents the accurate acquisition
of the spectra. Physical considerations let us assume that the influence of the spatial misregistration on the acquired data
depends both on the wavelength, and on the across-track position. A scene-based edge detection method is therefore
proposed. Such a procedure measures the variation on the spatial location of an edge between its various monochromatic
projections, giving estimation for spatial misregistration, and allowing also misalignments identification. The method has
been applied to several hyperspectral sensors, either prism, or grating-based designs. Results confirm the dependence
assumptions on &lgr; and &thgr;, spectral wavelength and across track pixel respectively. In order to correct for spatial
misregistration suggestions are also given.
In order to achieve quantitative measurements of the Earth's surface radiance and reflectance, it is important to determine the aerosol optical thickness (AOT) to correct for the optical influence of atmospheric particles. An advanced method for aerosol detection and quantification is required, which is not strongly dependant on disturbing effects due to surface reflectance, gas absorption and Rayleigh scattering features. A short review of existing applicable methods to the APEX airborne imaging spectrometer (380nm to 2500nm), leads to the suggested aerosol retrieval method here in this paper. It will measure the distinct radiance change between two near-UV spectral bands (385nm & 412nm) due to aerosol induced scattering and absorption features. Atmospheric radiation transfer model calculations have been used to analyze the AOT retrieval capability and accuracy of APEX. The noise-equivalent differential AOT is presented along with the retrieval sensitivity to various input variables. It is shown, that the suggested method will be able to identify different aerosol model types and measure AOT and columnar size distribution. The proposed accurate AOT determination will lead to a unique opportunity of two-dimensional pixel-wise mapping of aerosol properties at a high spatial resolution. This will be helpful especially for regional climate studies, atmospheric pollution monitoring and for the improvement of aerosol dispersion models and the validation of aerosol algorithms on spaceborne sensors.
APEX is a dispersive pushbroom imaging spectrometer operating in the spectral range between 380 - 2500 nm. The spectral resolution will be better than 10 nm in the SWIR and < 5 nm in the VNIR range of the solar reflected range of the spectrum. The total FOV will be ± 14 deg, recording 1000 pixels across track with about 300 spectral bands simultaneously. A large variety of characterization measurements will be performed in the scope of the APEX project, e.g., on-board characterization, frequent laboratory characterization, and vicarious calibration. The retrieved calibration parameters will allow a data calibration in the APEX Processing and Archiving Facility (PAF). The data calibration includes the calculation of the required, time-dependent calibration coefficients from the calibration parameters and, subsequently, the radiometric, spectral and geometric calibration of the raw data. Because of the heterogeneity of the characterization measurements, the optimal calibration for each data set is achieved using a special assimilation algorithm. In the paper the different facilities allowing characterization measurements, the PAF and the new data assimilation scheme are outlined.
Recently, a joint Swiss/Belgian initiative started a project to build a new generation airborne imaging spectrometer, namely APEX (Airborne Prism Experiment) under the ESA funding scheme named PRODEX. APEX is a dispersive pushbroom imaging spectrometer operating in the spectral range between 380 - 2500 nm. The spectral resolution will be better then 10 nm in the SWIR and < 5 nm in the VNIR range of the solar reflected range of the spectrum. The total FOV will be ± 14 deg, recording 1000 pixels across track with max. 300 spectral bands simultaneously. APEX is subdivided into an industrial team responsible for the optical instrument, the calibration homebase, and the detectors, and a science and operational team, responsible for the processing and archiving of the imaging spectrometer data, as well as for its operation. APEX is in its design phase and the instrument will be operationally available to the user community in the year 2006.
The handling of satellite or airborne earth observation data for scientific applications minimally requires pre-processing to convert
raw digital numbers into scientific units. However depending on sensor characteristics and architecture, additional work may be
needed to achieve spatial and/or spectral uniformity. Standard
higher level processing also typically involves providing orthorectification and atmospheric correction. Fortunately some of the computational tasks required to perform radiometric and geometric calibration can be decomposed into highly independent
subtasks making this processing highly parallelizable. Such
"embarrassingly parallel" problems provide the luxury of being
able to choose between cluster or grid based solutions to perform
these functions. Perhaps the most convenient solutions are grid-based, since most research groups making these kinds of measurements are likely to have access to a LAN whose spare computing resources could be non-obtrusively employed in a grid. However, since many higher level scientific applications of earth observation data might be composed of more highly interdependent subtasks, the parallel
computing resources allocated for these tasks might also be made
available for low level pre-processing as well. We look at two
modules developed for our prototype data calibration processor for
APEX, an airborne imaging spectrometer, which have been implemented
on both a cluster and a grid leading us to be able to make observations and comparisons of the two approaches.
Over the past few years, a joint Swiss/Belgium ESA initiative resulted in a project to build a precursor mission of future spaceborne imaging spectrometers, namely APEX (Airborne Prism Experiment). APEX is designed to be an airborne dispersive pushbroom imaging spectrometer operating in the solar reflected wavelength range between 4000 and 2500 nm. The system is optimized for land applications including limnology, snow, and soil, amongst others. The instrument is optimized with various steps taken to allow for absolute calibrated radiance measurements. This includes the use of a pre- and post-data acquisition internal calibration facility as well as a laboratory calibration and a performance model serving as a stable reference. The instrument is currently in its breadboarding phase, including some new results with respect to detector development and design optimization for imaging spectrometers. In the same APEX framework, a complete processing and archiving facility (PAF) is developed. The PAF not only includes imaging spectrometer data processing up to physical units, but also geometric and atmospheric correction for each scene, as well as calibration data input. The PAF software includes an Internet based web-server and provides interfaces to data users as well as instrument operators and programmers. The software design, the tools and its life cycle are discussed as well.
The launch of ESA’s ENVISAT in March 2002 was followed by a commissioning phase for all ENVISAT instruments to verify the performance of ENVISAT instruments and recommend possible adjustments of the calibration or the product algorithms before the data was widely distributed. The focus of this paper is on the vicarious calibration of the Medium Resolution Imaging Spectrometer (MERIS) radiance product (Level 1b) over land. From August to October 2002, several vicarious calibration (VC) experiments for MERIS were performed by the Optical Sciences Center, University of Arizona, and the Remote Sensing Laboratories, University of Zurich. The purpose of these activities was the acquisition of in-situ measurements of surface and atmospheric conditions over a bright, uniform land target, preferably during the time of MERIS data acquisition. The experiment was performed on a dedicated desert site (Railroad Valley Playa, Nevada, USA), which has previously been used to calibrate most relevant satellite instruments (e.g., MODIS, ETM+, etc.). In-situ data were then used to compute top-of-atmosphere (TOA) radiances which were compared to the MERIS TOA radiances (Level 1b full resolution product) to determine the in-flight radiometric response of the on-orbit sensor. The absolute uncertainties of the vicarious calibration experiment are found between 3.36-7.15%, depending on the accuracies of the available ground truth data. Based on the uncertainties of the vicarious calibration method and the calibration accuracies of MERIS, no recommendation to update the MERIS calibration is given.
The underlying algorithmic architecture of the level 0 to 1 processing
of the APEX spectrometer is presented. This processing step calculates
the observed radiances in physical units from the recorded raw digital
numbers. APEX will operate airborne and record radiance in the solar reflected wavelength range. The system is optimized for land applciations including limnology, snow, soil, amongst others. The instrument will be calibrated with a flexible setup in a laboratory as well as on-board. A concept for the dynamic update of the radiance calibration coefficients for the APEX spectrometer is presented. The time evolution of the coefficients is calculated from the heterogeneous calibration measurements with a data assimilation technique. We propose a Kalman filter for the initial version of the processor. Additionally, the structure of the instrument model suitable for the analysis of APEX data is developed. We show that this model can be used for the processing of observations as well as for the calculation of calibration coefficients. Both processes can be understood as inverse problems with the same forward model, i.e. the instrument model.
The high resolution airborne imaging spectrometer APEX (Airborne Prism Experiment) is currently being built. In parallel, its data processing calibration chain is being designed. The complex design of this high resolution pushbroom instrument bears the risk of optical aberrations in the registered spatio-spectral frames. Such aberrations consist of so-called frown and smile effects, as well as ghost image, smear, and stray light contributions. A concept is presented which shall operationally improve image calibration by inversion of the sensor model.
In the framework of the APEX (Airborne Prism Experiment) pushbroom imaging spectrometer, a complete processing and archiving facility (PAF) is developed. The PAF not only includes imaging spectrometer data processing up to physical units, but also geometric and atmospheric correction for each scene, as well as calibration data input. The PAF software includes an Internet based web-server and provides interfaces to data users as well as instrument operators and programmers. The software design, the tools and its life cycle is discussed as well. Further we will discuss particular instrument requirements (resampling, bad pixel treatment, etc.) in view of the operation of the PAF as well as their consequences on the product quality. Finally we will discuss a combined approach for geometric and atmospheric correction including BRDF (or view angle) related effects.
A method for the determination of aerosol optical properties from imaging spectrometer data on a local scale is investigated, making use of the continuous spectral coverage, high spatial resolution, and the well-calibrated radiometry of such data. The method (correlated spectral unmixing) is based on the decomposition of the sensor signal in the short-wave infrared using spectrum database ground spectra, the reconstruction of image ground spectra in the visible, and forward modelling with a radiative transfer code. The sensitivity of the imaging spectrometer signal to different atmospheric condititions is explored, as well as the correlation of spectral reflectances in the visible and short-wave infrared for a variety of surfaces. The potential of the presented method is demonstrated for a scene from the airborne visible and infrared imaging spectrometer AVIRIS over rugged heterogeneous coastal terrain in California, and comparisons to multispectral methods are made.
A combined geometric and atmospheric correction processing chain for hyperspectral imagery has been developed. The paper first describes the ortho-rectification solution for the geometric part employing a parametric geocoding approach (PARGE model). The model includes all navigation parameters in a forward transformation methodology. Its basic method and implementation principles are depicted. The output of the processor are the geocoded imagery and interface layers to the atmospheric/topographic correction. The radiometric correction of atmospheric and topographic effects is the second part of the preprocessing (model ATCOR 4). The method accounts for the angular and elevation dependence of the path radiance and atmospheric transmittance functions to remove atmospheric and topographic effects. It uses a database of look-up tables of the atmospheric correction function (path radiance, atmospheric transmittance, direct and diffuse solar flux) calculated with the MODTRAN 4 radiative transfer code. The influence of the adjacency effect is included during the calculation of the surface reflectance cube. Additionally, the terrain shape obtained from a digital elevation model is taken into account for the reflectance computation in a rugged area. For sensors with one or more thermal bands the surface temperature can also be calculated. As an option, value adding channels can be derived, such as LAI, FPAR, albedo, absorbed solar radiation flux, and for coregistered reflective and thermal band sensors the net radiation and heat fluxes. Examples of processing of hyperspectral imagery in flat and rugged terrain will be presented.
We present an approach to translate scientific requirements into instrument specifications by using a forward model for generic airborne imaging spectrometers in earth remote sensing. Based on scientific requirements, for each relevant variable detectable using imaging spectroscopy, ground reflectance spectra have been provided by specialists in their field of expertise. Relevant changes to be detected in the observed variable are used to derive critical delta reflectances. Realistic mission scenarios are subsequently combined with theses delta reflectances and a radiative transfer code to determine spectral NedL values at the sensor level. The combination of various fields of application in terms of detectable variables and the use of realistic mission scenarios leads to the determination of various NedL levels that are determined at given at sensor radiances. Using this concept, manufacturable specifications can be derived from scientific requirements.
The consistent simulation of airborne and spaceborne hyperspectral data is an important task and sometimes the only way for the adaptation and optimization of a sensor and its observing conditions, the choice and test of algorithms for data processing, error estimations and the evaluation of the capabilities of the whole sensor system. The integration of three approaches is suggested for the data simulation of APEX (Airborne Prism Experiment): (1) a spectrally consistent approach (e.g. using AVIRIS data), (2) a geometrically consistent approach (e.g. using CASI data), and (3) an end-to- end simulation of the sensor system. In this paper, the last approach is discussed in detail. Such a technique should be used if there is no simple deterministic relation between input and output parameters. The simulation environment SENSOR (Software Environment for the Simulation of Optical Remote Sensing Systems) presented here includes a full model of the sensor system, the observed object and the atmosphere. The simulator consists of three parts. The first part describes the geometrical relations between object, sun, and sensor using a ray tracing algorithm. The second part of the simulation environment considers the radiometry. It calculates the at-sensor-radiance using a pre-calculated multidimensional lookup-table for the atmospheric boundary conditions and bi- directional reflectances. Part three consists of an optical and an electronic sensor model for the generation of digital images. Application-specific algorithms for data processing must be considered additionally. The benefit of using an end- to-end simulation approach is demonstrated, an example of a simulated APEX data cube is given, and preliminary steps of evaluation of SENSOR are carried out.
Nearly all current imaging spectroscopy data are obtained by scanning airborne systems. The stability of such systems is always worse than that of spaceborne platforms. Thus, geometric distortions occur due to variations of the flightpath as well as of the attitude of the plane. These distortions cannot be corrected simply by ground control point based traditional georeferencing procedures since the movements cannot be approximated satisfactorily by polynomial transformations of the image. A pixel by pixel calculation has to be performed instead, to account for the position and attitude of the plane during the scanning process. A georeferencing procedure is described which is based on a parametric approach and theoretically allows sub- pixel accuracy even in steep terrain. The current work resulted in a new algorithm and application for parametric geocoding. A ground control point based procedure has been developed to recalibrate the offsets of the attitude data since they usually are given as relative angles. It exactly reconstructs the scanning geometry for each image pixel using position, attitude, and terrain elevation data. The procedure is tested on AVIRIS and on DAIS data and compared to digital topographic data. The geocoding results are of reliable accuracies of down to 1-2 pixels for both data sets.
In the past various authors pointed out, that the value of imaging spectrometer data is closely related to the accuracy with which the data are calibrated to represent physical parameters. the AVIRIS team at JPL gave good examples on how the calibration can be performed in the laboratory and how its accuracy can be evaluated independently by means of an in-flight calibration/validation experiment. The first part of this paper presents the laboratory instrumentation and measurements that were brought into place at the German Aerospace Research Establishment (DLR) to calibrate the DAIS 7915 sensor. Some estimates of the accuracy of these measurements are given to allow the derivation of an overall precision of the laboratory calibration. It is the purpose of an in-flight calibration and validation campaign to check the validity of the laboratory calibration for data acquired under in-flight conditions. In a joint experiment of DLR and the Remote Sensing Laboratories of the University of Zurich the DAIS instrument flew a standard test site in the center of Switzerland in summer 1996. In parallel to this overflight a number of ground reference measurements are acquired. The influence of the atmosphere is accounted for using the MODTRAN radiative transfer code. Sample spectra for different in-flight calibration targets are displayed.