IEEE GRSS Hyperspectral Cal/Val Workshop
Edinburgh, UK
Oct 7-9, 2015
Resources
Terminology:
bo.eufar.net/wiki/pmwiki/pmwiki.php/N6SP/Glossary
Standards
Standards for hyperspectral imagery and calibration and validation of the data have been under development for many years. The ISO standards are a group of related standards that all work together so that new standards only need define the “new stuff” and can refer to the “existing stuff” that they need. In particular, the standards for hyperspectral cal/val, which this workshop is about, are part of the dozens of standards that the ISO Technical Committee on Geographic Information (ISO TC 211) has produced. ISO 19159-1 is the standard for cal/val of optical sensors, hyperspectral being one subset. However, it refers to ISO 19159 for much of the other information related to cal/val of any remotely-sensed data. ISO 19159 in turn refers to other standards for related information, such as ISO 19101, which is a reference model for geographic information of many kinds, not just remotely-sensed, and not just imagery. What this means is that in order to understand any one standard, you really need to understand dozens, those that are interlinked to the one you care about through these infomration-sharing linkages. Below are links to on-line versions of some of these standards. Because ISO standards must be purchased, these tend to be pre-release versions, but they are still useful for getting the gist of the standards.
- ISO TC 211: Geographic Information
An overview of the entire Technical Committee:
en.wikipedia.org/wiki/ISO/TC_211 - ISO 19115: Geographic information – Metadata
wiki.earthdata.nasa.gov/display/NASAISO/ISO+19115 - ISO 19115-2: Geographic information – Metadata – Part 2: Extensions for imagery and gridded data
wiki.earthdata.nasa.gov/display/NASAISO/ISO+19115-2 - ISO 19101-2: Geographic information — Reference Model – Imagery
www.hpc.msstate.edu/committees/GRSS-DAD/19101-2WD2.pdf - ISO 19121: Geographic information — Imagery and gridded data
cmapspublic3.ihmc.us/rid=1MW1WMFR0-29DL9TN-15HK/ISO TR 19121 Imagery and gridded 2data.doc - ISO 19130: Geographic information – Sensor data model for imagery
csiss.gmu.edu/activity/draftCD19130pt221.doc - ISO 19159: Geographic information – Calibration and validation of remote
sensing imagery sensors and data
www.asprs.org/a/society/divisions/pdad/Spring/Spring 2011/wd1.3_Calibration_and_validation-sf2-110313.pdf - ISO 19159-1: Geographic information – Calibration and validation of remote
sensing imagery sensors and data. Part 1: Optical Sensors
app.sni.gob.ec/sni-link/sni/RESPALDOS/SANTIAGO LUCERO/GLOSARIO DE TERMINOS NACIONAL/ISO-TC211-N33/ISO-TC211_N3389_DTS_19159-1_Calibration_and_validation-_Part_1_Optical_sensors.pdf
References related to ISO 19159-1
CEOS WGISS Interoperability Handbook, Issue 1.1, February 2008.
Close range camera calibration, Duane C. Brown,Photogrammetric Engineering Vol. 37, No. 8, pp. 855–866, 1971.
Digital camera self-calibration Clive S. Fraser, ISPRS Journal of Photogrammetry and Remote Sensing, Volume 52, Issue 4, Pages 149–159, August 1997.
Multi-sensor system self-calibration, C. S. Fraser, M. R. Shortis and G. Ganci, SPIE Conference 2598, Videometrics IV, Philadelphia, USA, October 25-26, 1995
USGS/OSU Progress with Digital Camera in-situ Calibration Methods, Merchant, D.C., Schenk, A., Habib, A., Yoon, T., ISPRS Congress,Istanbul 2004.
Geometric Handling of Large Size Digital Airborne Frame Camera Images, Jacobsen, K., Optical 3D Measurement Techniques VIII, Zürich, pp 164 -171, 2007.
Principal Warps: Thin-Plate Splines and the Decomposition of Deformations, Bookstein, F.L., IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 11, No. 6, pp. 567-585, 1989.
Select CEOS Cal/Val Documents
Best Practice Guidelines for Pre-Launch. Characterization and Calibration of Instruments for Passive Optical Remote Sensing, US National Institute for Standards and Technology, 2009.
Optical Sensors High Resolution Geometry Validation Methodology, Armin Gruen, Sultan Kocaman, ETH Zurich, 2008.
Calibration Requirements Consolidation, R. Santer, Brockman Consult, 2007.
Hyperspectral Cal/Val papers and presentations
The Future Spaceborne Hyperspectral Imager ENMAP: Its Calibration, Validation, and Processing Chain, T. Storch, A. de Miguel, R. Müller, A. Müller, A. Neumann, T. Walzel, M. Bachmann, G. Palubinskas, M. Lehner, R. Richter, E. Borg, B. Fichtelmann, T. Heege, M. Schroeder, and P. Reinartz, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XXXVII, Part B1, Beijing 2008.
Calibration and Validation of Hyperspectral Imagery Using a Permanent Test Field, Lauri Markelin, Eija Honkavaara, Tuure Takala, Petri Pellikka, 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2013, 25-28 June 2013, Gainesville, Florida, USA.
Including Quality Measures in an Automated Processing Chain for Airborne Hyperspectral Data, Martin Bachmann, Martin Habermeyer, Stefanie Holzwarth, Rudolf Richter and Andreas Müller, Proceedings 5th EARSeL Workshop on Imaging Spectroscopy, Bruges, Belgium, April 23-25 2007.
Standards for Airborne Hyperspectral Image Data, S. Holzwarth, M. Bachmann, M. Freer, M. Hofmann, EARSeL 7th SIG-Imaging Spectroscopy Workshop, European Association of Remote Sensing Laboratories, Edinburgh, 11-13 April 2011.
Calibration and Validation for International Satellite Imaging Spectroscopy Missions: Australia’s Contribution, Cindy Ong, Tim Malthus, Ian Lau, Nandika Thapar, Mike Caccetta, Guy Byrne, IGARSS 2014.
Spectral Databases
sdbs.db.aist.go.jp/sdbs/cgi-bin/cre_index.cgi
speclab.cr.usgs.gov/spectral-lib.html
www2.uef.fi/fi/spectral/spectral-database
minerals.gps.caltech.edu/Files/index.html
www-app2.gfz-potsdam.de/spectation/?file=main
References related to spectral databases:
Standards for making measurements