Jürg Schopfer

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 Improved Dual-view Field Goniometer System FIGOS

In spectrodirectional Remote Sensing (RS) the Earths 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.

Scaling dimensions in spectroscopy of soil and vegetation

Abstract The paper revises and clarifies definitions of the term scale and scaling conversions for imaging spectroscopy of soil and vegetation. We demonstrate a new four-dimensional scale concept that includes not only spatial but also the spectral, directional and temporal components. Three scaling remote sensing techniques are reviewed: (1) radiative transfer, (2) spectral (un)mixing, and (3) data fusion. Relevant case studies are given in the context of their up- and/or down-scaling abilities over the soil/vegetation surfaces and a multi-source approach is proposed for their integration. Radiative transfer (RT) models are described to show their capacity for spatial, spectral up-scaling, and directional down-scaling within a heterogeneous environment. Spectral information and spectral derivatives, like vegetation indices (e.g. TCARI/OSAVI), can be scaled and even tested by their means. Radiative transfer of an experimental Norway spruce (Picea abies (L.) Karst.) research plot in the Czech Republic was simulated by the Discrete Anisotropic Radiative Transfer (DART) model to prove relevance of the correct object optical properties scaled up to image data at two different spatial resolutions. Interconnection of the successive modelling levels in vegetation is shown. A future development in measurement and simulation of the leaf directional spectral properties is discussed. We describe linear and/or non-linear spectral mixing techniques and unmixing methods that demonstrate spatial down-scaling. Relevance of proper selection or acquisition of the spectral endmembers using spectral libraries, field measurements, and pure pixels of the hyperspectral image is highlighted. An extensive list of advanced unmixing techniques, a particular example of unmixing a reflective optics system imaging spectrometer (ROSIS) image from Spain, and examples of other mixture applications give insight into the present status of scaling capabilities. Simultaneous spatial and temporal down-scaling by means of a data fusion technique is described. A demonstrative example is given for the moderate resolution imaging spectroradiometer (MODIS) and LANDSAT Thematic Mapper (TM) data from Brazil. Corresponding spectral bands of both sensors were fused via a pyramidal wavelet transform in Fourier space. New spectral and temporal information of the resultant image can be used for thematic classification or qualitative mapping. All three described scaling techniques can be integrated as the relevant methodological steps within a complex multi-source approach. We present this concept of combining numerous optical remote sensing data and methods to generate inputs for ecosystem process models.

Toward a direct comparison of field and laboratory goniometer measurements

Field and laboratory goniometers are widely used in the remote sensing community to assess spectrodirectional reflection properties of selected targets. Even when the same target and goniometer system are used, field and laboratory results cannot directly be compared due to inherent differences, mainly in the illumination conditions since actual goniometers measure a hemispherical-conical reflectance in the field and a biconical reflectance in the lab. Yet, the ability to compare and combine measurements from different instrumental designs is critical to ensure sensor cross-calibration and for all applications that rely on measurements obtained with both types of instruments. One approach to this problem consists in retrieving the bidirectional reflectance distribution function (BRDF) of the targets of interest for each experimental setup and to compare these, since theoretically they are independent of the particular conditions of illumination and observation. This involves a correction for diffuse incoming radiation in the case of field measurements, and a correction for conicity and inhomogeneity of illumination in the case of laboratory measurements. In this paper, we present a novel BRDF retrieval scheme for typical laboratory goniometers and compare it with the usual correction method assuming Lambertian behavior. We then discuss the first results of measurements and BRDF retrievals using the field and laboratory goniometer systems of the Remote Sensing Laboratories of the University of Zurich, which share the exact observation geometry, on the same inert, highly anisotropic target.

Combined field and laboratory goniometer system - FIGOS and LAGOS

Ground level measurements of surface directional reflectance properties can be performed either in the field or within a laboratory setup. The latter has the advantage of independence on weather conditions, constant illumination and neglectable atmospheric disturbances. On the other hand, the artificial laboratory light sources usually are less parallel and less homogeneous than the clear sky solar illumination. In order to compare these two types of measurements (or replace one by the other) a careful correction of the data (BRDF retrieval) with respect to the mentioned sources of error is necessary. For the field case, this can be done following the well known procedures proposed by Martonchick and others. The purpose of this paper is to present our laboratory goniometer system and a corresponding BRDF retrieval solution. The RSL laboratory goniometer system (LAGOS) is based on the field goniometer (FIGOS) with the addition of a 1000 W brightness-stabilized quartz tungsten halogen lamp and lens system, placed in a dark room for minimization of stray light. The inhomogeneity of the illuminated area has been directly measured and found to be within 10% mean deviation for the zenith position. A simulation of the complete geometry of LAGOS, including the angular distributions and inhomogeneity of the light source as well as the changing position of the radiometer footprint allows us to estimate the measurement error for any target with known BRDF. The same algorithm can be used as core for the BRDF retrieval.

Monitoring Vegetation Growth using Multitemporal CHRIS/PROBA Data

The spaceborne ESA-mission CHRIS/PROBA (Compact High Resolution Imaging Spectrometer-Project for On-board Autonomy) provides hyperspectral and multi- directional data of selected targets spread over the world. This coupled system represents a new source of information for Earth observation purposes. While the spectral information content of CHRIS data is able to assess the biochemistry of a vegetation canopy, the directional information can describe the structure of an observed canopy. Both biochemical content and canopy structure change with phenological development. During May to September 2005, numerous spectro-directional CHRIS data sets for six different phenological stages were acquired over a testsite in Switzerland. The area covered is dominated by agricultural fields and forests. A selection of CHRIS data sets that span the observed growing phase were geometrically and atmospherically corrected using a parametric geocoding approach and the physically based atmospheric correction software ATCOR. The analysis of the CHRIS data focuses on the interpretation of HDRF (Hemispherical Directional Reflectance Factor) changes contained in the various data sets over time. The spectrodirectional behaviour of agricultural crops varies over time as a function of vegetation stages (phenology). Understanding of this effect, which is studied on selected crops, may improve agricultural monitoring and crop classification. Accurate spatial mapping of crop status serves as an important input to precision agriculture.

Comparison of field and laboratory spectro-directional measurements using a standard artificial target

Spectro-directional surface measurements can either be performed in the field or within a laboratory setup. Laboratory measurements have the advantage of constant illumination and neglectable atmospheric disturbances. On the other hand, artificial light sources are usually less parallel and less homogeneous than the clear sky solar illumination. To account for these differences and for determining for which targets a replacement of field by laboratory experiments is indeed feasible, a quantitative comparison is a prerequisite. Currently, there exists no systematic comparison of field and laboratory measurements using the same targets. In this study we concentrate on the difference in spectro-directional field and laboratory data of the same target due to diffuse illumination. The field data were corrected for diffuse illumination following the proposed procedure by Martonchik . Spectro-directional data were obtained with a GER3700 spectroradiometer. In the field, a MFR sun photometer directly observed the total incoming diffuse irradiance. In the laboratory, a 1000W brightness-stabilized quartz tungsten halogen lamp was used. For the first direct comparison of field and laboratory measurements, we used an artificial and inert target with high angular anisotropy. Analysis shows that the diffuse illumination in the field is leading to a higher total reflectance and less pronounced angular anisotropy.

Visualisation, processing and storage of spectrodirectional data based on the spectral database SPECCHIO

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.