Rule-based classification models: flexible integration of satellite imagery and thematic spatial data

Paul V Bolstad, T. M. Lillesand

Research output: Contribution to journalArticlepeer-review

45 Scopus citations

Abstract

A framework for automated land-cover classification based on a concept of a classification model was developed and tested. The framework employs a user-specified rule base to describe a classification model, defined as the series of spatial data operations and decisions used in landcover classification. Both evidential and hierarchical inference are supported utilizing a set of spatial data operators. The concept was tested through the development and application of a set of computer programs which support classification models. A rule base, thematic spatial data, and satellite image data were then used to define a classification model. The classification model approach resulted in statistically significant, 15% improvements in classification accuracy when averaged across different analysts, geographic areas, and years. -from Authors

Original languageEnglish (US)
Pages (from-to)965-971
Number of pages7
JournalPhotogrammetric Engineering & Remote Sensing
Volume58
Issue number7
StatePublished - Jan 1 1992
Externally publishedYes

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