Jens Nieke

APEX - the hyperspectral ESA Airborne Prism Experiment

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 Earths complex mechanisms.

The spectral database SPECCHIO for improved long-term usability and data sharing

The organised storage of spectral data described by metadata is important for long-term use and data sharing with other scientists. Metadata describing the sampling environment, geometry and measurement process serves to evaluate the suitability of existing data sets for new applications. There is a need for spectral databases that serve as repositories for spectral field campaign and reference signatures, including appropriate metadata parameters. Such systems must be (a) highly automated in order to encourage users entering their spectral data collections and (b) provide flexible data retrieval mechanisms based on subspace projections in metadata spaces. The recently redesigned SPECCHIO system stores spectral and metadata in a relational database based on a non-redundant data model and offers efficient data import, automated metadata generation, editing and retrieval via a Java application. RSL is disseminating the database and software to the remote sensing community in order to foster the use and further development of spectral databases.

Spatial PSF Nonuniformity Effects in Airborne Pushbroom Imaging Spectrometry Data

Efficient and accurate imaging spectroscopy data processing asks for perfectly consistent (i.e., ideally uniform) data in both the spectral and spatial dimensions. However, real pushbroom-type imaging spectrometers are affected by various point spread function (PSF) nonuniformity artifacts. First, individual pixels or lines may be missing in the raw data due to bad pixels originating from the detector, readout errors, or even electronic failures. Second, so-called smile and keystone optical aberrations are inherent to imaging spectrometers. Appropriate resampling strategies are required for the preprocessing of such data if emphasis is put on spatial PSF uniformity. So far, nearest neighbor interpolations have been often recommended and used for resampling. This paper shall analyze the radiometric effects if linear interpolation is used to optimize the spatial PSF uniformity. For modeling interpolation effects, an extensive library of measured surface reflectance spectra as well as real imaging spectroscopy data over various land cover types are used. The real measurements are systematically replaced by interpolated values, and the deviation between original and resampled spectra is taken as a quality measure. The effects of nearest neighbor resampling and linear interpolation methods are compared. It is found that linear interpolation methods lead to average radiometric errors below 2% for the correction of spatial PSF nonuniformity in the subpixel domain, whereas the replacement of missing pixels leads to average errors in the range of 10%-20%

Structure, Components, and Interfaces of the Airborne Prism Experiment (APEX) Processing and Archiving Facility

The product generation from hyperspectral sensor data has high requirements on the processing infrastructure, both hardware and software. The Airborne Prism Experiment (APEX) 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.

Water Quality Monitoring for Lake Constance with a Physically Based Algorithm for MERIS Data

A physically based algorithm is used for automatic processing of MERIS level 1B full resolution data. The algorithm is originally used with input variables for optimization with different sensors (i.e. channel recalibration and weighting), aquatic regions (i.e. specific inherent optical properties) or atmospheric conditions (i.e. aerosol models). For operational use, however, a lake-specific parameterization is required, representing an approximation of the spatio-temporal variation in atmospheric and hydrooptic conditions, and accounting for sensor properties. The algorithm performs atmospheric correction with a LUT for at-sensor radiance, and a downhill simplex inversion of chl-a, sm and y from subsurface irradiance reflectance. These outputs are enhanced by a selective filter, which makes use of the retrieval residuals. Regular chl-a sampling measurements by the Lakes protection authority coinciding with MERIS acquisitions were used for parameterization, training and validation.

Uniformity of Imaging Spectrometry Data Products

The increasing quantity and sophistication of imaging spectroscopy applications have led to a higher demand on the quality of Earth observation data products. In particular, it is desired that data products be as consistent as possible (i.e., ideally uniform) in both spectral and spatial dimensions. Yet, data acquired from real (e.g., pushbroom) imaging spectrometers are adversely affected by various categories of artifacts and aberrations including as follows: singular and linear (e.g., bad pixels and missing lines), area (e.g., optical aberrations), and stability and degradation defects. Typically, the consumer of such data products is not aware of the magnitude of such inherent data uncertainties even as more uncertainty is introduced during higher level processing for any particular application. In this paper, it is shown that the impact of imaging spectrometry data product imperfections in currently available data products has an inherent uncertainty of 10%, even though worst case scenarios were excluded, state-of-the-art corrections were applied, and radiometric calibration uncertainties were excluded. Thereafter, it is demonstrated how this error can be reduced (<5%) with appropriate available technology (onboard, scene, and laboratory calibration) and assimilation procedures during the preprocessing of the data. As a result, more accurate, i.e., uniform, imaging spectrometry data can be delivered to the user community. Hence, the term uniformity of imaging spectrometry data products is defined for enabling the quantitative means to assess the quality of imaging spectrometry data. It is argued that such rigor is necessary for calculating the error propagation of respective higher level processing results and products.

Improvement of AVNIR-2 Radiometric Calibration by Comparison of Cross-Calibration and Onboard Lamp Calibration

The Advanced Visible and Near Infrared Radiometer type 2 (AVNIR-2) on-orbit radiometric performance has been improved through the comparison of cross-calibration and onboard lamp calibration. We proposed a new cross-calibration scheme which uses top-of-atmosphere reflectance functions of satellite zenith angle at temporally and spatially stable ground sites. Each function is made from Moderate Resolution Imaging Spectroradiometer (MODIS) 500-m resolution data over 16 days, which includes AVNIR-2 observation dates. The results showed that the radiances of AVNIR-2 bands 1 (463 nm), 2 (560 nm), and 3 (652 nm) agreed with the radiances of Aqua and Terra MODIS within 3% accuracy (standard deviation of 2%). AVNIR-2 band 4 (821 nm) had a difference of about 7% (AVNIR-2< MODIS) due to water-vapor absorption which could explain more than half of the 7%. Using many samples from this scheme, we found dependences of radiometric calibration errors within the field of view (FOV) and for different gain modes. The lamp calibration system onboard AVNIR-2 unveiled these dependences over the FOV and time. Furthermore, for the gain mode, consistent results could be retrieved using the cross-calibration scheme. The retrieved radiometric correction factors (over the FOV and gain modes) have been applied to the Japan Aerospace Exploration Agency AVNIR-2 processing scheme. The subsequent validation of the correction showed, for polar snow areas, an improved radiometric performance over the entire FOV.

Scene-based method for spatial misregistration detection in hyperspectral imagery

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 method, based on edge detection, is therefore proposed. Such a procedure measures the variation on the spatial location of an edge between its various monochromatic projections, giving an estimation for spatial misregistration, and also allowing identification of misalignments. The method has been applied to several hyperspectral sensors, either prism, or grating-based designs. The results confirm the dependence assumptions on lambda and theta, spectral wavelength and across-track pixel, respectively. Suggestions are also given to correct for spatial misregistration.

A satellite cross-calibration experiment

Recently, the Advanced Earth Observing Satellite 2 (ADEOS-2) was launched (December 14, 2002) successfully, and the Global Imager (GLI) onboard the ADEOS-2 satellite became operational in April 2003. In a first calibration checkup, the radiometric performance of GLI was compared relatively to that of other sensors on different satellites with different calibration backgrounds. As a calibration site, a large snowfield near Barrow, Alaska, was used, where space sensors in polar orbits view the same ground target on the same day with small differences in the local crossing times. This is why GLI, the Moderate Resolution Imaging Spectroradiometer (Terra, Aqua), the Sea-viewing Wide Field-of-view Sensor, the Advanced Very High Resolution Radiometer (N16, N17), the Medium Resolution Imaging Spectrometer, and the Advanced Along Track Scanning Radiometer datasets were selected for the following clear-sky condition days: April 14 and 26, 2003. At the same time, ground-truth experiments (e.g., measurements of ground reflectance, bidirectional reflectance distribution function, aerosol optical thickness) were carried out. Thereinafter, top-of-atmosphere (TOA) radiance/reflectance was forward calculated by means of radiative transfer code for each sensor, each band, and each day. Finally, the vicariously retrieved TOA signal was compared to TOA sensor Level 1B data. As a result, GLIs performance is encouraging at that time of the mission. GLI and the other seven sensors deliver similar sensor output in the range of about 5% to 7% around the expected vicariously calculated TOA signal.

Calibration Methodology for the Airborne Dispersive Pushbroom Imaging Spectrometer (APEX)

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.