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Testing Ikonos and Landsat 7 ETM+ Potential for Stand-Level Forest Type Mapping by Soft Supervised Approaches

  • G. Chirici
  • P. Corona
  • M. Marchetti
  • D. Travaglini
Part of the Forestry Sciences book series (FOSC, volume 76)

Abstract

Forest types can be adopted as a suitable reference for classifying survey units within multipurpose forest resources inventories, at the properly considered level. This kind of hierarchical classification approach integrates an ecologically meaningful per-habitat perspective with practical survey, planning and management requirements. Advanced remote sensing technologies can be valuable tools for a cost-effective implementation of such an approach. In the present paper, data from high (Landsat 7 ETM+) and very high (Ikonos) spatial resolution satellite sensors were tested to understand their potential contribution supporting stand-level forest type mapping under Mediterranean conditions. Ikonos and Landsat images were used to differentiate forest coverages by so called soft classifiers: fuzzy maximum likelihood procedure for Ikonos and subpixel unmixing procedure for Landsat. Fuzzy classified images are then contrasted with forest type map made by photointerpretation of Ikonos imagery. Perfomances are showed and drawbacks discussed.

Keywords

Forest Type Land Cover Class Landsat Data Mixed Pixel Soft Classification 
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 Science+Business Media Dordrecht 2003

Authors and Affiliations

  • G. Chirici
    • 1
  • P. Corona
    • 2
  • M. Marchetti
    • 3
  • D. Travaglini
    • 1
  1. 1.geoLAB — Laboratory of Geomatics, Dipartimento di Scienze e Tecnologie Ambientali ForestaliUniversità di FirenzeFirenzeItaly
  2. 2.sisFOR — Laboratory of Forest Inventory and Information Systems, Dipartimento di Scienze dell’Ambiente Forestale e delle sue RisorseUniversità della TusciaViterboItaly
  3. 3.Dipartimento di Colture ArboreeUniversità di PalermoPalermoItaly

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