The experimental results prove that only few landscapes are remaining on the earth due to anthropogenic activities and the human activities, which has a great impact on the globe. As the population is getting increased day by day, there are many changes occurring in the land use and land cover which results in mitigating the agriculture land that leads to drought and other natural calamities. To reduce such impact on the globe, change detection techniques are very helpful for finding the areas where the change is occurring. Deep learning methods are being used efficiently in remote sensing projects these days. In this paper, Land cover classification and change detection is made using high resolution satellite images of Guntur region taken over the years 2013 and 2016 with Landsat-7. The change detection process is performed by using VGG 19 technique in Convolution neural network algorithm.


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    Titel :

    Land Cover Change Detection Using Convolution Neural Network


    Beteiligte:
    M, Tejaswini (Autor:in) / P, Pranuthi (Autor:in) / S, Ravichand (Autor:in) / T, Anuradha (Autor:in)


    Erscheinungsdatum :

    01.06.2019


    Format / Umfang :

    1267668 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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