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Accurate spectral calibration of airborne and spaceborne imaging spectrometers is essential for proper preprocessing and scientific exploitation of high spectral resolution measurements of the land and atmosphere. A systematic performance assessment of onboard and scene-based methods for in-flight monitoring of instrument spectral calibration is presented for the first time in this paper. Onboard and ground imaging data were collected at several flight altitudes using the Airborne Prism Experiment (APEX) imaging spectrometer. APEX is equipped with an in-flight characterization (IFC) facility allowing the evaluation of radiometric, spectral, and geometric system properties, both in-flight and on-ground for the full field of view. Atmospheric and onboard filter spectral features present in at-sensor radiances are compared with the same features in reference transmittances convolved to varying instrument spectral configurations. A spectrum-matching algorithm, taking advantage of the high sensitivity of measurements around sharp spectral features toward spectrometer spectral performance, is used to retrieve channel center wavelength and bandwidth parameters. Results showed good agreement between spectral parameters estimated using onboard IFC and ground imaging data. The average difference between estimates obtained using the O2 and H2O features and those obtained using the corresponding filter features amounted to about 0:3 nm (0.05 of a spectral pixel). A deviation from the nominal laboratory instrument spectral calibration and an altitude-dependent performance was additionally identified. The relatively good agreement between estimates obtained by the two approaches in similar spectral windows suggests they can be used in a complementary fashion: while the method relying on atmospheric features can be applied without the need for dedicated calibration acquisitions, the IFC allows assessment at user-selectable wavelength positions by custom filters as well as for the

ESA APEX (Airborne Prism EXperiment) is a project for the realisation of an airborne dispersive pushbroom imaging spectrometer, a dedicated data Processing and Archiving Facility (PAF, hosted at VITO) and a Calibration Home Base (CHB, hosted at DLR) for instrument calibration operation. It has been developed by a joint Swiss-Belgian consortium. The APEX instrument is facing its finalisation phase undergoing intense experimental activities in view of its validation and performance assessment. Environmental tests were executed to simulate flight environment conditions. The first APEX airborne campaign has been held in June 2009 covering a variety of water targets over Switzerland and Belgium. Extensive pre- and postflight characterisation and calibration campaigns were accomplished. Instrument data evaluation, performance analysis and optimisation of the data processing schemes adopted have followed. This paper outlines the activities performed and presents the first products achieved.

Sun-induced chlorophyll fluorescence (Fs) is a promising parameter for remote measuring plant photosynthesis. It has been demonstrated that Fs at cell and leaf level is strongly related to photosynthesis. The transfer of the Fs approach to canopy level remains challenging as the canopy Fs signal is not fully understood yet. Several factors influence the Fs signal and need to be quantified. However, the absence of dedicated imaging spectrometers limits the experimental data for such investigations. We propose an experimental setup allowing spatio-temporal investigations of canopy Fs. A non-imaging spectrometer was installed in a low-flying aircraft. An agricultural area was continuously monitored including the extensive coverage of dedicated fields. Fs was retrieved from spectrometer data using the FLD (Fraunhofer Line Depth) method combined with simulated (MODTRAN-4) at-sensor radiances of a reference surface. We present the methodological framework to derive canopy chlorophyll fluorescence from airborne based non-imaging spectrometer measurements and a quality assessment of the data.

Combining bidirectional-reflectance distribution functions of selected materials with airborne-laser and imaging-spectrometer data improves quantitative mapping accuracy.

—The product generation from hyperspectral sensor data has high requirements on the processing infrastructure, both hardware and software. The APEX (Airborne Prism Experiment) processing and archiving facility has been set up to provide for the automated generation of level 1 calibrated data and user configurable on-demand product generation for higher processing levels. The system offers full reproducibility of user orders and processing parameters by employing a relational database. The flexible workflow software allows for the quick integration of novel algorithms or the definition of new processing sequences. Reprocessing of data is supported by the archiving approach. Configuration management based on the database enables the control over different versions of processing modules to be applied. The system is described with a focus on the APEX instrument, however, its generic design allows adaptation to other sensor systems.

The transition from film imaging to digital imaging in photogrammetric data capture is opening interesting possibilities for photogrammetric processes. A great advantage of digital sensors is their radiometric potential. This article presents a state-of-the-art review on the radiometric aspects of digital photogrammetric images. The analysis is based on a literature research and a questionnaire submitted to various interest groups related to the photogrammetric process. An important contribution to this paper is a characterization of the photogrammetric image acquisition and image product generation systems. The questionnaire revealed many weaknesses in current processes, but the future prospects of radiometrically quantitative photogrammetry are promising.

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 correction of BRDF (bidirectional reflectance distribution function) effects in imaging spectrometer data requires object specific spectrodirectional information. Such data may be acquired using goniometer systems such as the dual-view Field Goniometer System (FIGOS). Their use in an operational processing environment requires optimized solutions for their storage, assessment, pre-processing and application in the actual correction procedure. The final goal is the provision of a spectral albedo product to the end user.

The Airborne Prism Experiment (APEX) is a hyperspectral instrument built in a Swiss - Belgian collaboration within the ESA-PRODEX program [1]. 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 [2]. 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) [3] is evaluated together with the ATCOR-4 atmospheric correction program [4],[5]. 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 [6] and a high resolution HYSPEX data set [7]. 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.

The airborne ESA-APEX (Airborne Prism Experiment) hyperspectral mission simulator is described with its distinct specifications to provide high quality remote sensing data. The concept of an automatic calibration, performed in the Calibration Home Base (CHB) by using the Control Test Master (CTM), the In-Flight Calibration facility (IFC), quality flagging (QF) and specific processing in a dedicated Processing and Archiving Facility (PAF), and vicarious calibration experiments are presented. A preview on major applications and the corresponding development efforts to provide scientific data products up to level 2/3 to the user is presented for limnology, vegetation, aerosols, general classification routines and rapid mapping tasks. BRDF (Bidirectional Reflectance Distribution Function) issues are discussed and the spectral database SPECCHIO (Spectral Input/Output) introduced. The optical performance as well as the dedicated software utilities make APEX a state-of-the-art hyperspectral sensor, capable of (a) satisfying the needs of several research communities and (b) helping the understanding of the Earth’s complex mechanisms.

The Bidirectional Reflectance Distribution Function (BRDF) is an inherent property of natural and manmade materials. Its effects depend on the illumination/observation geometry and wavelengths and are apparent in groundbased, airborne and spaceborne imagery. The BRDF is a fundamental quantity from which all other illumination/reflection configurations can be derived. Calibration and validation of hyperspectral images requires knowledge of the BRDF if spectrodirectional effects are to be accounted for. The BRDF can be retrieved from dual-view field goniometer system (FIGOS) data, which is stored in the spectral database SPECCHIO. The retrieval must be precluded by pre-processing steps, which apply transformations on the raw field data and according metadata. SPECCHIO has been updated to support such pre-processing. Intercalibrations of the involved instruments and temporal corrections lead to a network of operations to be applied to the input data. A generalisation of the processing has led to the concept of the Space Processing Chain, allowing the flexible combination of modules to form complex processing flows as required by the goniometer data pre-processing. The newly added support of intercalibration factors in the SPECCHIO data model will be an important asset in future round robin experiments. The Space Chain approach will operationalise the retrieval of BRDF from dual-view FIGOS data and generally increase the usefulness of the SPECCHIO system by the introduction of user configurable processing.

In the scope of hyperspectral airborne imaging spectrometer (APEX) design activities, the acceptable sensitivity of linear polarization of the spectrometer is analyzed by assessing the amount of polarization of reflected light in the atmosphere-surface system. A large number of calculations is performed for a wide variaty of viewing geometries to study the influences of aerosol models, natural surfaces and flight altitudes over the spectral range from the near-UV to the short-wave infrared (SWIR). Thereinafter the design of the imaging spectrometer is outlined accounting for these requirements and a method of partially correcting the instrument polarization sensitivity is briefly introduced. APEX design and post-processing capabilities will enable to reduce the influence of polarization sensitivity of at-sensor radiance and its higher-level products generated for most of the observation conditions.

The automatic correction of atmospheric effects currently requires visible to short-wave spectral bands (400–2500nm) to derive high accuracy surface reflectance data. Common techniques employ spectral correlations of dark targets in the short-wave infrared (SWIR, around 2.2 mm), blue (480 nm) and red (660 nm) regions to derive the aerosol optical depth. A large number of current Earth-observing satellite sensors have only three or four spectral channels in the visible and near-infrared (VNIR) region (400–1000nm), making an automatic image-based atmospheric correction very difficult. This contribution presents a new algorithm and first results with VNIR imagery. The method starts with the assumption of average clear atmospheric conditions (aerosol optical depth AOD50.27, corresponding to a visibility of 23km) and calculates the surface reflectance in the red and near-infrared (NIR) bands. The second step derives a mask of dark vegetation pixels. It is calculated using multiple thresholds of vegetation index combined with red and NIR surface reflectance values. Then the red band surface reflectance for the dark pixels is estimated from the NIR reflectance as rred50.1 rnir, from which the aerosol optical depth (or visibility) can be calculated. The core of the VNIR algorithm consists of two subsequent iteration loops (visibility and rred) to improve the visibility estimate. Results of the VNIR method are presented for Landsat-5 Thematic Mapper (TM) and Landsat-7 Enhanced Thematic Mapper Plus (ETM + ) imagery using only the first four bands. The performance of the method is compared to the established dark pixel technique where the SWIR bands are included. Results show that the deviation between both methods is usually less than 0.005 reflectance units if measured in terms of the scene-average reflectance, indicating a useful potential for this approach.