Optical remote sensing has limitations in obtaining images due to weather and environmental effects, so these limitations must be overcome to produce time-series image data. As an alternative to this, research are being conducted to simulate images at a specific time for which a specific image is needed. The purpose of this study is to improve the results of this process by preprocessing the input images of a multiple linear regression model alongside other remote sensing image simulation methods. Specifically, the input images, which are applied to a multi-linear regression equation, are preprocessed for phenological and radiometric normalization by a random forest regression model. The experimental results show that the proposed method is superior to the conventional methods both visually and quantitatively.


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    Title :

    Analysis of Image Preprocessing Effects in a Landsat Image Simulation


    Additional title:

    KSCE J Civ Eng


    Contributors:

    Published in:

    Publication date :

    2020-07-01


    Size :

    7 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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