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.

[1]  Jens Nieke,et al.  Metadata of spectral data collections , 2007 .

[2]  Liping Di The development of remote-sensing related standards at FGDC, OGC, and ISO TC 211 , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

[3]  Jindi Wang,et al.  Studies on methods for quality assessment of crop spectral data , 2004, IGARSS 2004. 2004 IEEE International Geoscience and Remote Sensing Symposium.

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

[5]  Martin Brändli,et al.  A large-scale, long-term view on collecting and sharing landscape data , 2007 .

[6]  D. Landgrebe On Information Extraction Principles for Hyperspectral Data , 1997 .

[7]  K. Pfitzner,et al.  A standard design for collecting vegetation reference spectra: Implementation and implications for data sharing , 2006 .

[8]  Paul J. Curran,et al.  Imaging spectrometry , 1994 .

[9]  J. Schopfer,et al.  GENERATION OF RSL ’ S SPECTRUM DATABASE “ SPECCHIO ” , 2007 .

[10]  Sucharita Ghosh,et al.  A changing world: Challenges for landscape research , 2007 .

[11]  Daniel Schläpfer,et al.  SPECCHIO: a spectrum database for remote sensing applications , 2003 .

[12]  John A. Richards,et al.  Remote Sensing Digital Image Analysis , 1986 .

[13]  John A. Richards,et al.  Interpretation of Hyperspectral Image Data , 1999 .

[14]  William K. Michener,et al.  Ecological Data: Design, Management and Processing , 2000 .

[15]  E. LeDrew,et al.  Remote sensing of aquatic coastal ecosystem processes , 2006 .

[16]  J. G. Ferwerda,et al.  A free online reference library for hyperspectral reflectance signatures , 2006 .

[17]  Andreas Hueni,et al.  Spectroradiometer data structuring, pre‐processing and analysis – an IT based approach , 2006 .

[18]  J. C. Price How unique are spectral signatures , 1994 .

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