A knowledge based classification for urban mapping using high resolution remote sensing data

Xiao Yi, Xiuping Jia, David Tien

Research output: Book chapter/Published conference paperConference paper

3 Citations (Scopus)

Abstract

This paper addresses the weakness of pixel based or cell-based classification algorithms for urban mapping. They cannot provide a handy object level classification results as often preferred in urban planning and assessment applications. A knowledge based approach is proposed which is integrated with the spectral classification methods and image processing tools. Experiments using a high resolution image were conducted. The results show the proposed method can improve the performances obtained by using the conventional maximum likelihood or ECHO algorithms.

Original languageEnglish
Title of host publicationProceedings - Digital Image Computing Techniques and Applications
Subtitle of host publication9th Biennial Conference of the Australian Pattern Recognition Society, DICTA 2007
Pages586-591
Number of pages6
DOIs
Publication statusPublished - 01 Dec 2007
EventAustralian Pattern Recognition Society (APRS) - Glenelg, SA, Australia
Duration: 03 Dec 200705 Dec 2007

Conference

ConferenceAustralian Pattern Recognition Society (APRS)
CountryAustralia
CityGlenelg, SA
Period03/12/0705/12/07

Fingerprint Dive into the research topics of 'A knowledge based classification for urban mapping using high resolution remote sensing data'. Together they form a unique fingerprint.

  • Cite this

    Yi, X., Jia, X., & Tien, D. (2007). A knowledge based classification for urban mapping using high resolution remote sensing data. In Proceedings - Digital Image Computing Techniques and Applications: 9th Biennial Conference of the Australian Pattern Recognition Society, DICTA 2007 (pp. 586-591). [4426851] https://doi.org/10.1109/DICTA.2007.4426851