An integrated spatio-temporal classification method for urban fringe change detection analysis

Yetao Yang*, Qiming ZHOU, Jianya Gong, Yi Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)

Abstract

The urban fringe is the transition zone between urban land use and rural land use. It represents the most active part of the urban expansion process. Change detection using multi-temporal imagery is proven to be an efficient way to monitor land-use/land-cover change caused by urban expansion. In this study, we propose a new multi-temporal classification method for change detection in the urban fringe area. The proposed method extracts and integrates spatio-temporal contextual information into multi-temporal image classification. The spatial information is extracted by object-oriented image segmentation. The temporal information is modelled with temporal trajectory analysis with a two-step calibration. A probabilistic schema that employs a global membership function is then used to integrate the spectral, spatial and temporal information. A trajectory accuracy measurement is proposed to assist the comparison on the performances of the integrated spatio-temporal method and classical pixel- and 'snapshot'-based classification methods. The experiment shows that the proposed method can significantly improve the accuracies of both single scene classification and temporal trajectory analysis.

Original languageEnglish
Pages (from-to)2516-2531
Number of pages16
JournalInternational Journal of Remote Sensing
Volume33
Issue number8
DOIs
Publication statusPublished - Apr 2012

Scopus Subject Areas

  • Earth and Planetary Sciences(all)

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