NDLI: Object-Oriented Classification for Change Detection with Different Spatial Resolution Images

Content Provider	IEEE Xplore Digital Library
Author	Yongdae Gweon Yun Zhang
Copyright Year	2008
Description	Author affiliation: Dept. of Geodesy & Geomatics Eng., Univ. of New Brunswick, Fredericton, NB (Yongdae Gweon; Yun Zhang)
Abstract	Aerial photos have been increasingly and commonly used in various spatially related applications. Many municipalities and government agencies have constructed aerial photo databases all over the world. Keeping these databases up to date is the most important part of making them effective so that aerial photo databases are expected to be updated as frequently as possible. However, in practice, some of them are barely updated because of high cost. In this study, medium spatial resolution imagery is proposed to detect changes. Instead of using aerial photos, free accessible Landsat ETM+ from GeoBase and orthophotomaps from SODB are used for change detection. In order to compare with different spatial resolution images orthophotomaps are decomposed, segmented, and classified through wavelet transform and object-oriented classification. Although the detected changes are rough, the result shows that the method is quite cost-effective and practical. Moreover, it could support decision making for updating aerial photo databases.
File Size	632209
File Format	PDF
ISBN	9781424428076
DOI	10.1109/IGARSS.2008.4779519
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-07-07
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Spatial resolution Image databases Spatial databases Object oriented databases Local government Costs Satellites Remote sensing Image segmentation Wavelet transforms object-oriented classification Change detection wavelet transform
Content Type	Text
Resource Type	Article

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