Andreas Hueni

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.

The use of diffuse reflectance spectroscopy for in situ carbon and nitrogen analysis of pastoral soils

A field method has been developed for rapid in situ assessment of soil carbon (C) and nitrogen (N) content using a portable spectroradiometer (ASD FieldSpecPro). The technique was evaluated at 7 field sites in permanent pasture, and in 1-year, 3-year, and 5-year pine-to-pasture conversions on Pumice, Allophanic, and Tephric Recent Soils in the Taupo and Rotorua region of New Zealand. A total of 210 samples were collected from 2 depths: 37.5 and 112.5 mm. Field measurement of diffuse spectral reflectance was recorded from a flat sectioned horizontal soil surface of a soil core using a purpose-built contact probe attached by fibre optic cable to the spectroradiometer. A 15-mm soil slice was collected from each cut surface for analysis of total C and N using a LECO Analyser. Soils had a wide range of total C and N (0.26–11.21% C, 0.02–1.01% N). Partial least-squares regression analysis was used to develop calibration models between smoothed-first derivative 5-nm-spaced spectral data and LECO-measured total C and N. The models successfully predicted total C and N in the validation sets with the best prediction for C (RPD 2.01, r2 0.75, RMSEP 1.21%) and N (RPD 2.66, r2 0.86, RMSEP 0.07%). Prediction accuracy using different selection methods of calibration and validation set is reported. This study indicates that in situ assessment of soil C and N by field spectroscopy has considerable potential for spatially rapid measurement of soil C and N in the landscape.

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.

APEX - current status, performance and validation concept

The Airborne Prism EXperiment (APEX) is an airborne pushbroom imaging spectrometer for Earth observation. Its products will become available in 2011. APEX is currently prepared for final acceptance configuration completing final hardware upgrades, refined calibration methodologies and test flights. APEX is composed of an airborne dispersive pushbroom imaging spectrometer, a Calibration Home Base (CHB) for instrument calibration and a data Processing and Archiving Facility (PAF) for operational product generation and delivery. A unique In-Flight Characterization (IFC) unit is integrated within the sensor optical head, providing pre- and post- data-acquisition characterization monitoring the instruments spectral and radiometric stability. This paper outlines the activities performed with a special focus on system calibration and validation procedures, as well as preliminary measurement results.

Spectroradiometer data structuring, pre‐processing and analysis – an IT based approach

Hyperspectral data collection results in huge datasets that need pre‐processing prior to analysis. A review of the pre‐processing techniques identified repetitive procedures with consequently a high potential for automation. Data from different hyperspectral field studies were collected and subsequently used as test sets for the described system. A relational database was utilized to store hyperspectral data in a structured way. Software was written to provide a graphical user interface to the database, pre‐processing and analysis functionality. The resulting system provides excellent services in terms of organised data storage, easy data retrieval and efficient pre‐processing. It is suggested that the use of such a system can improve the productivity of researchers significantly.

Airborne Prism Experiment Calibration Information System

The calibration of remote sensing instruments is a crucial step in the generation of products tied to international reference standards. Calibrating imaging spectrometers is particularly demanding due to the high number of spatiospectral pixels and, consequently, the large amount of data acquired during calibration sequences. Storage of these data and associated meta-data in an organized manner, as well as the provision of efficient tools for the data analysis and fast and repeatable calibration coefficient generation with provenance information, is key to the provision of traceable measurements. The airborne prism experiment (APEX) calibration information system is a multilayered information technology solution comprising a database based on the entity-attribute-value (EAV) paradigm and software written in Java and Matlab, providing data access, visualization and processing, and handling the data volumes over the expected lifetime of the system. Although developed in the context of APEX, the system is rather generic and may be adapted to other pushbroom-based imagers with little effort.

Mapping functional diversity from remotely sensed morphological and physiological forest traits

Assessing functional diversity from space can help predict productivity and stability of forest ecosystems at global scale using biodiversity–ecosystem functioning relationships. We present a new spatially continuous method to map regional patterns of tree functional diversity using combined laser scanning and imaging spectroscopy. The method does not require prior taxonomic information and integrates variation in plant functional traits between and within plant species. We compare our method with leaf-level field measurements and species-level plot inventory data and find reasonable agreement. Morphological and physiological diversity show consistent change with topography and soil, with low functional richness at a mountain ridge under specific environmental conditions. Overall, functional richness follows a logarithmic increase with area, whereas divergence and evenness are scale invariant. By mapping diversity at scales of individual trees to whole communities we demonstrate the potential of assessing functional diversity from space, providing a pathway only limited by technological advances and not by methodology.As remote sensing technology improves, it is now possible to map fine-scale variation in plant functional traits. Schneider et al. remotely sense tree functional diversity, validate with field data, and reveal patterns of plant adaptation to the environment previously not retrievable from plot data

Data exchange between distributed spectral databases

Spectral databases constitute one of the components of a complete observing system, storing in situ spectroscopic measurements plus associated metadata and providing data for the validation, calibration, and simulation of imaging spectrometer products. Such databases may be employed by physically or organisationally separate entities. Consequently, methods for data exchange between distributed spectral databases are required, allowing the transfer of defined subsets of spectral data including their full metadata context from a source to a target system. The data exchange comprises generic approaches to the sequential steps of ordered table row export, relational storage in XML files, and nonconflicting import into the target database. The SPECCHIO spectral database system was used as a test bed for the data exchange between databases of identical schemata and according import/export functionality has been added to the SPECCHIO application. Import and export speeds were assessed using test cases of different metadata space densities, a score for the density with which associated metadata are detailed, and the potential utility as a quantitative rating for quality. Future spectral databases should allow the exchange between heterogeneous systems, ideally implementing a common subset of metadata parameters and thus supporting the long-term usability and data sharing between research partners.

Field and Airborne Spectroscopy Cross Validation—Some Considerations

Field spectroscopy is increasingly used in various fields of science: either as a research tool in its own right or in support of airborne- or space-based optical instruments for calibration or validation purposes. Yet, while the use of the instruments appears deceptively simple, the processes of light and surface interactions are complex to be measured in full and are further complicated by the multidimensionality of the measurement process. This study exemplifies the cross validation of in situ point spectroscopy and airborne imaging spectroscopy data across all processing stages within the spectroscopy information hierarchy using data from an experiment focused on vegetation. In support of this endeavor, this study compiles the fundamentals of spectroscopy, the challenges inherent to field and airborne spectroscopy, and the best practices proposed by the field spectroscopy community. This combination of theory and case study shall enable the reader to develop an understanding of 1) some of the commonly involved sources of errors and uncertainties, 2) the techniques to collect high-quality spectra under natural illumination conditions, and 3) the importance of appropriate metadata collection to increase the long-term usability and value of spectral data.