Functional classification of spatially heterogeneous environments: the Land Cover Mosaic approach in remote sensing

M.H. Obbink

Research output: Thesisinternal PhD, WU

Abstract

Tropical rainforest areas are difficult to classify in the digital analysis of remote sensing data because of spatial heterogeneity. Often many technical solutions are adopted to reduce the ‘problem’ of spatial heterogeneity. This thesis describes theory and methods that now use this heterogeneity during the digital image classification. With spatial heterogeneity, spatial aggregation levels such as patches,patch-mosaics and landscapes can be distinguished. Consequently, vegetation patterns can be related to functional management units at different decision-levels. The developed theory and methods thus save two birds with one stone: (a) the classification is completely digitally, and (b) the classification provides information on deforestation that meets the needs of decision-makers. This thesis further recommends approaching all land cover classifications from a heterogeneous perspective for understanding and controlling environmental processes on a global level. This can enhance a sustainable development of tropical rainforest areas for the benefit of future generations.

  

Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Wageningen University
Supervisors/Advisors
  • Molenaar, M., Promotor
  • Clevers, Jan, Co-promotor
Award date6 Sep 2011
Place of Publication[S.l.]
Print ISBNs9789085859956
Publication statusPublished - 2011

Keywords

  • remote sensing
  • heterogeneity
  • tropical rain forests
  • spatial variation
  • classification
  • landscape ecology
  • decision making

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