Landscape Ecology

, Volume 22, Issue 2, pp 171–177

Mapping Spatial Patterns with Morphological Image Processing

  • Peter Vogt
  • Kurt H. Riitters
  • Christine Estreguil
  • Jacek Kozak
  • Timothy G. Wade
  • James D. Wickham
Report

DOI: 10.1007/s10980-006-9013-2

Cite this article as:
Vogt, P., Riitters, K.H., Estreguil, C. et al. Landscape Ecol (2007) 22: 171. doi:10.1007/s10980-006-9013-2
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Abstract

We use morphological image processing for classifying spatial patterns at the pixel level on binary land-cover maps. Land-cover pattern is classified as ‘perforated,’ ‘edge,’ ‘patch,’ and ‘core’ with higher spatial precision and thematic accuracy compared to a previous approach based on image convolution, while retaining the capability to label these features at the pixel level for any scale of observation. The implementation of morphological image processing is explained and then demonstrated, with comparisons to results from image convolution, for a forest map of the Val Grande National Park in North Italy.

Keywords

Morphological image processingSpatial patternForest fragmentation

Copyright information

© Springer Science+Business Media B.V. 2006

Authors and Affiliations

  • Peter Vogt
    • 1
  • Kurt H. Riitters
    • 2
  • Christine Estreguil
    • 1
  • Jacek Kozak
    • 3
  • Timothy G. Wade
    • 4
  • James D. Wickham
    • 4
  1. 1.Land Management and Natural Hazards Unit (LMNH)European Commission – DG Joint Research Centre, Institute for Environment and Sustainability (IES)IspraItaly
  2. 2.US Forest ServiceSouthern Research StationResearch Triangle ParkUSA
  3. 3.Institute of Geography and Spatial ManagementJagiellonian UniversityKrakówPoland
  4. 4.US Environmental Protection AgencyEnvironmental Sciences DivisionResearch Triangle ParkUSA