The Improved Dual-view Field Goniometer System FIGOS.

In spectrodirectional Remote Sensing (RS) the Earth's surface reflectance characteristics are studied by means of their angular dimensions. Almost all natural surfaces exhibit an individual anisotropic reflectance behaviour due to the contrast between the optical properties of surface elements and background and the geometric surface properties of the observed scene. The underlying concept, which describes the reflectance characteristic of a specific surface area, is called the bidirectional reflectance distribution function (BRDF). BRDF knowledge is essential for both correction of directional effects in RS data and quantitative retrieval of surface parameters. Ground-based spectrodirectional measurements are usually performed with goniometer systems. An accurate retrieval of the bidirectional reflectance factors (BRF) from field goniometer measurements requires hyperspectral knowledge of the angular distribution of the reflected and the incident radiation. However, prior to the study at hand, no operational goniometer system was able to fulfill this requirement. This study presents the first dual-view field goniometer system, which is able to simultaneously collect both the reflected and the incident radiation at high angular and spectral resolution and, thus, providing the necessary spectrodirectional datasets to accurately retrieve the surface specific BRF. Furthermore, the angular distribution of the incoming diffuse radiation is characterized for various atmospheric conditions and the BRF retrieval is performed for an artificial target and compared to laboratory spectrodirectional measurement results obtained with the same goniometer system. Suggestions for further improving goniometer systems are given and the need for intercalibration of various goniometers as well as for standardizing spectrodirectional measurements is expressed.

Sensor Performance Requirements for the Retrieval of Atmospheric Aerosols by Airborne Optical Remote Sensing.

This study explores performance requirements for the retrieval of the atmospheric aerosol optical depth (AOD) by airborne optical remote sensing instruments. Independent of any retrieval techniques, the calculated AOD retrieval requirements are compared with the expected performance parameters of the upcoming hyperspectral sensor APEX at the reference wavelength of 550nm. The AOD accuracy requirements are defined to be capable of resolving transmittance differences of 0.01 to 0.04 according to the demands of atmospheric corrections for remote sensing applications. For the purposes of this analysis, the signal at the sensor level is simulated by radiation transfer equations. The resulting radiances are translated into the AOD retrieval sensitivity (Δτλaer ) and compared to the available measuring sensitivity of the sensor (NE ΔLλsensor). This is done for multiple signal-to-noise ratios (SNR) and surface reflectance values. It is shown that an SNR of 100 is adequate for AOD retrieval at 550nm under typical remote sensing conditions and a surface reflectance of 10% or less. Such dark surfaces require the lowest SNR values and therefore offer the best sensitivity for measuring AOD. Brighter surfaces with up to 30% reflectance require an SNR of around 300. It is shown that AOD retrieval for targets above 50% surface reflectance is more problematic with the current sensor performance as it may require an SNR larger than 1000. In general, feasibility is proven for the analyzed cases under simulated conditions.

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 Earth's complex mechanisms.

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.