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http://dx.doi.org/10.11108/kagis.2012.15.3.066

A Study on Object Based Image Analysis Methods for Land Use and Land Cover Classification in Agricultural Areas  

Yeon, Jong-Min (Satellite Information Research Center, Korea Aerospace Research Institute)
Kim, Hyun-Ok (Satellite Information Research Center, Korea Aerospace Research Institute)
Yoon, Bo-Yeol (Satellite Information Research Center, Korea Aerospace Research Institute)
Publication Information
Journal of the Korean Association of Geographic Information Studies / v.15, no.3, 2012 , pp. 66-80 More about this Journal
Abstract
It is necessary to normalize spectral image values derived from multi-temporal satellite data to a common scale in order to apply remote sensing methods for change detection, disaster mapping, crop monitoring and etc. There are two main approaches: absolute radiometric normalization and relative radiometric normalization. This study focuses on the multi-temporal satellite image processing by the use of relative radiometric normalization. Three scenes of KOMPSAT-2 imagery were processed using the Multivariate Alteration Detection(MAD) method, which has a particular advantage of selecting PIFs(Pseudo Invariant Features) automatically by canonical correlation analysis. The scenes were then applied to detect disaster areas over Sendai, Japan, which was hit by a tsunami on 11 March 2011. The case study showed that the automatic extraction of changed areas after the tsunami using relatively normalized satellite data via the MAD method was done within a high accuracy level. In addition, the relative normalization of multi-temporal satellite imagery produced better results to rapidly map disaster-affected areas with an increased confidence level.
Keywords
Multivariate Alteration Detection(MAD); Relative Radiometric Normalization; KOMPSAT-2; Change Detection; Disaster Areas;
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Times Cited By KSCI : 1  (Citation Analysis)
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