Spectral Discrimination of Southern Victorian Salt Tolerant Vegetation

  • Chris Matthews
  • Rob Clark
  • Leigh Callinan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4065)


The use of remotely sensed data to map aspects of the landscape is both efficient and cost effective. In geographically large and sparsely populated countries such as Australia these approaches are attracting interest as an aid in the identification of areas affected by environmental problems such as dryland salinity. This paper investigates the feasibility of using visible and near infra-red spectra to distinguish between salt tolerant and salt sensitive vegetation species in order to identify saline areas in Southern Victoria, Australia. A series of classification models were built using a variety of data mining techniques and these together with a discriminant analysis suggested that excellent generalisation results could be achieved on a laboratory collected spectra data base. The results form a basis for continuing work on the development of methods to distinguish between vegetation species based on remotely sensed rather than laboratory based measurements.


Native Grass Minority Class Canonical Variate Analysis Canopy Architecture Derivative Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Chris Matthews
    • 2
  • Rob Clark
    • 1
  • Leigh Callinan
    • 1
  1. 1.Dept of Primary IndustriesPIRVicBendigoAustralia
  2. 2.Faculty of Science, Technology & EngineeringLa Trobe UniversityBendigoAustralia

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