Assessing effects of input uncertainty in structural landscape classification

Frank Canters, William De Genst, Hans Dufourmont

Research output: Contribution to journalArticle

35 Citations (Scopus)

Abstract

This paper presents the result of a study aimed at assessing the effects of input uncertainty on the outcome of a raster-based model for structural landscape classification. The model uses a DEM and a land-cover map as input, and calculates four structural indices from these data. The first two indices determine the openness of the landscape, the other two determine the degree of landscape homogeneity. By combining both aspects, nine different landscape types are defined. Applying Monte Carlo simulation, the effect of DEM error, uncertainty in land-cover classification, and the combined effect of both sources on uncertainty on the outcome of the landscape model are assessed. Special attention is paid to the spatial structure of uncertainty in both data sources.
Original languageEnglish
Pages (from-to)129-149
Number of pages21
JournalInternational Journal of Geographical Information Science
Volume16
Issue number2
Publication statusPublished - 2002

Bibliographical note

International Journal of Geographical Information Science, 16(2), 129-149.

Keywords

  • spatial data uncertainty
  • Monte Carlo simulation
  • digital elevation modeling
  • land-cover classification
  • landscape analysis

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