Skip to main content

Integrating high resolution remote sensing, GIS and fuzzy set theory for identifying susceptibility areas of forest insect infestations

Buy Article:

$63.00 plus tax (Refund Policy)

The use of fuzzy set theory has become common in remote sensing and geographical information system (GIS) applications to deal with issues surrounding the uncertainty of geospatial datasets. The objective of this study is to develop a model that integrates the concept of fuzzy set theory with remote sensing and GIS in order to produce susceptibility maps of insect infestations in forest landscapes. Fuzzy set theory was applied to information extracted from multiple‐year high resolution remote sensing data and integrated in a raster‐based GIS to create a map indicating the spatial variation of insect susceptibility in a landscape. Variable‐specific fuzzy membership functions were developed based on expert knowledge and existing data, and integrated through a semantic import model. The results from a case study on mountain pine beetle ( Dendroctonus ponderosae Hopkins) illustrate that the model provides a method to successfully estimate areas of varying susceptibility to insect infestation from high resolution remote sensing images. It was concluded that fuzzy sets are an adequate method for dealing with uncertainty in defining susceptibility variables. The susceptibility maps can be utilized for guiding management decisions based on the spatial aspects of insect–host relationships.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Data/Media
No Metrics

Document Type: Research Article

Affiliations: Department of Geography, Simon Fraser University, 8888 University Drive, Burnaby, BC, V5A 1S6, Canada

Publication date: 2005-11-10

More about this publication?
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more