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http://dx.doi.org/10.7780/kjrs.2002.18.2.71

Particulate Distribution Map of Tidal Flat using Unsupervised Classification of Multi-Temporary Satellite Data  

정종철 (남서울대학교 지리정보공학과)
Publication Information
Korean Journal of Remote Sensing / v.18, no.2, 2002 , pp. 71-79 More about this Journal
Abstract
This research presents particulate distribution map of tidal flats of Hampyung bay using reflectance which extracted from satellite data and field survey data during same periods. The spectrum of particulate composition obtained from Landsat TM data was analysed and 7 scenes of satellite image were classified with ISODATA and K-MEANS methods. The results of unsupervised classification were estimated with in-situ data. The classification accuracy of ISODATA and K-MAMS methods were 84.3% and 85.7%. For validation of classified results of multi-temporal satellite images, TM image of May 1999(reference data), which was classified with field survey data was compared with classified results of multi-temporary satellite data.
Keywords
Unsupervised Classification; Multi-temporary Satellite Data; Tidal Flats; Particulate Distribution Map.;
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Times Cited By KSCI : 2  (Citation Analysis)
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