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.

[1]  Malcolm Lidierth,et al.  sigTOOL: A MATLAB-based environment for sharing laboratory-developed software to analyze biological signals , 2009, Journal of Neuroscience Methods.

[2]  Timo Stuffler,et al.  EnMAP A Hyperspectral Sensor for Environmental Mapping and Analysis , 2006, 2006 IEEE International Symposium on Geoscience and Remote Sensing.

[3]  H. Kaufmann,et al.  Hyperspectral imaging—An advanced instrument concept for the EnMAP mission (Environmental Mapping and Analysis Programme) , 2009 .

[4]  L. Floridi On defining library and information science as applied philosophy of information , 2002 .

[5]  Perry L. Miller,et al.  Application of Information Technology: Organization of Heterogeneous Scientific Data Using the EAV/CR Representation , 1999, J. Am. Medical Informatics Assoc..

[6]  David B. Stephenson,et al.  A Changing Climate for Prediction , 2007, Science.

[7]  R. Ackoff From Data to Wisdom , 2014 .

[8]  Frederic Teston,et al.  The PROBA/CHRIS mission: a low-cost smallsat for hyperspectral multiangle observations of the Earth surface and atmosphere , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[9]  Gareth R.T. White,et al.  Business Information Management: Improving Performance Using Information Systems , 2004 .

[10]  Jens Nieke,et al.  The spectral database SPECCHIO for improved long-term usability and data sharing , 2009, Comput. Geosci..

[11]  R. Jenssen,et al.  1 THE HYMAP TM AIRBORNE HYPERSPECTRAL SENSOR : THE SYSTEM , CALIBRATION AND PERFORMANCE , 1998 .

[12]  Matthias Ecker Automatisierung einer optoelektronischen Kalibriereinrichtung , 2007 .

[13]  Jennifer E. Rowley,et al.  The wisdom hierarchy: representations of the DIKW hierarchy , 2007, J. Inf. Sci..

[14]  Thomas D. Wason,et al.  Structured Metadata Spaces , 2000 .

[15]  Nigel P. Fox,et al.  Progress in Field Spectroscopy , 2006, 2006 IEEE International Symposium on Geoscience and Remote Sensing.

[16]  Peter Strobl,et al.  Preprocessing for the digital airborne imaging spectrometer DAIS 7915 , 1996, Defense + Commercial Sensing.

[17]  Markus Bundschus,et al.  Towards a Next-Generation Matrix Library for Java , 2009, 2009 33rd Annual IEEE International Computer Software and Applications Conference.

[18]  Demetrio Labate,et al.  The PRISMA payload optomechanical design, a high performance instrument for a new hyperspectral mission , 2009 .

[19]  Stefan Adriaensen,et al.  Structure, Components, and Interfaces of the Airborne Prism Experiment (APEX) Processing and Archiving Facility , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[20]  Shunlin Liang,et al.  Earth system science related imaging spectroscopy — an assessment , 2009 .

[21]  John J. Barnett,et al.  Traceable Radiometry Underpinning Terrestrial- and Helio-Studies (TRUTHS): An Element of a Space-Based Climate and Calibration Observatory , 2003, Remote. Sens..

[22]  Richard J. Varey The Knowing Organization: : How Organizations Use Information to Construct Meaning, Create Knowledge, and Make Decisions , 2013 .

[23]  Jessica A. Faust,et al.  Imaging Spectroscopy and the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) , 1998 .

[24]  L. Floridi Understanding Epistemic Relevance , 2008 .

[25]  John Shepanski,et al.  Hyperion, a space-based imaging spectrometer , 2003, IEEE Trans. Geosci. Remote. Sens..

[26]  Prakash M. Nadkarni,et al.  Guidelines for the effective use of entity-attribute-value modeling for biomedical databases , 2007, Int. J. Medical Informatics.

[27]  Steven Kempler,et al.  Evolution of Information Management at the GSFC Earth Sciences (GES) Data and Information Services Center (DISC): 2006–2007 , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[28]  Peter Gege,et al.  Calibration facility for airborne imaging spectrometers , 2005 .

[29]  Arie Shoshani,et al.  The Earth System Grid: Supporting the Next Generation of Climate Modeling Research , 2005, Proceedings of the IEEE.