Land Cover Classification of Remotely Sensed Satellite Data using Bayesian and Hybrid classifier
نویسندگان
چکیده
منابع مشابه
Land Cover Classification of Remotely Sensed Satellite Data using Bayesian and Hybrid classifier
In this paper an attempt has been made to develop classification algorithm for remotely sensed satellite data using Bayesian and hybrid classification approach. Bayesian classification is a probabilistic technique which is capable of classifying every pattern until no pattern remains unclassified. Hybrid classification involves developing training patterns using unsupervised classification foll...
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Land cover is one of basic data layers in geographic information system for physical planning and environmentalmonitoring. Digital image classification is generally performed to produce land cover maps from remote sensing data,particularly for large areas. In the present study the multispectral image from IRS LISS-III image along with ancillary datasuch as vegetation indices, principal componen...
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Remote Sensing Imagery is used by the Government and private agencies for the wide range of applications from military to farm development. Fuzzy c-means clustering is an effective algorithm, but the random selection in center points makes iterative process falling into the local optimal solution easily. In this Paper, a novel clustering method is developed using GA based clustering techniques....
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ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2010
ISSN: 0975-8887
DOI: 10.5120/1295-1783