Alternative representations of in-stream habitat: Classification using remote sensing, hydraulic modeling, and fuzzy logic

Carl J. Legleiter, Michael Goodchild

Research output: Contribution to journalArticle

39 Citations (Scopus)

Abstract

Improved techniques are needed to characterize complex fluvial systems and monitor ecologically important, yet highly vulnerable riverine environments. This paper explores potential alternatives to traditional mapping of in-stream habitat and presents fuzzy set theory as a means of departing from the rigid, Boolean, object-based framework. We utilize hydrodynamic modeling, remotely sensed data, and fuzzy clustering to obtain classifications that allow for continuous partial membership and gradual transitions among habitat types. Methods of assessing cluster validity are available, but data quality is a crucial consideration. Crisp, vector-based representations can be derived from raster fuzzy classifications by applying a threshold to maximum membership values. This process results in conditional objects separated by ambiguous transition zones, and a compromise must be reached between the proportion of the channel assigned to polygons and the certainty with which this assignment can be made. Spatial patterns of classification uncertainty can also be used to identify areas of confusion, infer boundaries of variable width, and highlight areas of increased habitat diversity. Hydraulic modeling and remote sensing complement one another and, together with field work, could provide a more realistic representation of the fluvial environment.

Original languageEnglish (US)
Pages (from-to)29-50
Number of pages22
JournalInternational Journal of Geographical Information Science
Volume19
Issue number1
DOIs
StatePublished - Jan 1 2005
Externally publishedYes

Fingerprint

fuzzy mathematics
logic
Fuzzy logic
habitat
Remote sensing
Hydraulics
remote sensing
hydraulics
modeling
set theory
Fuzzy set theory
Fuzzy clustering
data quality
raster
polygon
habitat type
transition zone
fieldwork
compromise
Large scale systems

Keywords

  • Fuzzy classification
  • Hydraulic modeling
  • Indeterminate boundaries
  • Remote sensing
  • Rivers
  • Uncertainty

ASJC Scopus subject areas

  • Information Systems
  • Geography, Planning and Development
  • Library and Information Sciences

Cite this

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abstract = "Improved techniques are needed to characterize complex fluvial systems and monitor ecologically important, yet highly vulnerable riverine environments. This paper explores potential alternatives to traditional mapping of in-stream habitat and presents fuzzy set theory as a means of departing from the rigid, Boolean, object-based framework. We utilize hydrodynamic modeling, remotely sensed data, and fuzzy clustering to obtain classifications that allow for continuous partial membership and gradual transitions among habitat types. Methods of assessing cluster validity are available, but data quality is a crucial consideration. Crisp, vector-based representations can be derived from raster fuzzy classifications by applying a threshold to maximum membership values. This process results in conditional objects separated by ambiguous transition zones, and a compromise must be reached between the proportion of the channel assigned to polygons and the certainty with which this assignment can be made. Spatial patterns of classification uncertainty can also be used to identify areas of confusion, infer boundaries of variable width, and highlight areas of increased habitat diversity. Hydraulic modeling and remote sensing complement one another and, together with field work, could provide a more realistic representation of the fluvial environment.",
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