Remote sensing deals with high resolution of geospatial data. It work on the various fields like agriculture, water resource, environment, forests, land use or land cover, ocean applications, soil, geosciences, disaster warning and management. To get required information from satellites images we need to do some image processing on it. Remote sensing image processing consists of various steps in which classification and segmentation of image into its land cover type is very essential part. This paper gives classification technique used to find the land cover classes in satellite images. In this paper three most used classification ion technique is studied that is supervised classification, unsupervised classification and Object oriented classification.


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    Title :

    Survey on Classification Techniques Used in Remote Sensing for Satellite Images


    Contributors:


    Publication date :

    2018-03-01


    Size :

    5403559 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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