EARSeL eProceedings Vol. 3, No. 2, 143-153, 2004

The use of hyperspectral data in coastal zone vegetation monitoring
Remko de Lange, Mark van Til and Stephen Dury

Vegetation monitoring is an important tool in the evaluation of nature management in the coastal zone of The Netherlands. Remote sensing images are valuable in order to investigate spatio-temporal changes in the vegetation. A classification method has been developed based on airborne hyperspectral data, which were acquired using the GER EPS-A scanner. A supervised classification method has been used applying the Spectral Angle Mapper, in combination with an expert system. The SAM algorithm determines the similarity between spectra of different vegetation types. The expert system adds extra information about environmental conditions to the classification in order to improve the discrimination of vegetation types, which are otherwise spectrally difficult to identify. In our case, this method gives the opportunity for rapid classification with an overall accuracy of 60-70%.

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Submitted: 07 June 2003
Revised: 31 January 2004
Accepted: 23 February 2004

de Lange R, M van Til & S Dury, 2004. The use of hyperspectral data in coastal zone vegetation monitoring. EARSeL eProceedings 3(2), 143-153


EARSeL European Association of Remote Sensing Laboratories, Paris, France


BIS Library and Information System, Carl von Ossietzky University of Oldenburg


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