Research of object-oriented classification method for high-spatial resolution remote sensing image used in land use/cover

  • Min Zhang*
  • , Yunxuan Zhou
  • , Jin Huang
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Based on characteristics of clear geometry features in high-spatial resolution remote sensing image, the paper presents a study method of land use/cover by object-oriented classification. The object-oriented classification method overcomes salt and pepper phenomena of conventional classification method by using feature object as basic processing units, which are generated from image segmentation. In this process, we consider spectral and shape as two basic factors and also emphasize texture information of surface features. Object-oriented remote sensing image classification method is based on the cognitive model of remote sensing information extraction, which can achieve multi-scale analysis of spatial, meet different scales requirement of surface feature extraction of information, and integrate multi-source data of classification, so as to make classification results more convinced.

Original languageEnglish
Title of host publication2010 International Conference on Multimedia Technology, ICMT 2010
DOIs
StatePublished - 2010
Externally publishedYes
Event2010 International Conference on Multimedia Technology, ICMT 2010 - Ningbo, China
Duration: 29 Oct 201031 Oct 2010

Publication series

Name2010 International Conference on Multimedia Technology, ICMT 2010

Conference

Conference2010 International Conference on Multimedia Technology, ICMT 2010
Country/TerritoryChina
CityNingbo
Period29/10/1031/10/10

Keywords

  • Information extraction
  • Land use and land cover
  • Object-orientation classification
  • SPOT5 image
  • eCognition

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