Objective class definitions using correlation of similarities between remotely sensed and environmental data

S. Andréfouët, M. Claereboudt

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

This letter presents a natural approach for selecting a subset of environmental variables to define classes prior to mapping them efficiently using remotely sensed data. The procedure is based on correlation calculations between a set of 'environmental' similarity matrices and an 'image' similarity matrix. The correlation is a modified Spearman rank correlation. Using a SPOT-HRV image and seven environmental variables, an application in a coral reef environment showed that only three environmental variables are relevant to defining classes prior to mapping.

Original languageEnglish
Pages (from-to)1925-1930
Number of pages6
JournalInternational Journal of Remote Sensing
Volume21
Issue number9
Publication statusPublished - 2000

ASJC Scopus subject areas

  • Computers in Earth Sciences

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