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.
Analysis of Image Preprocessing Effects in a Landsat Image Simulation
KSCE J Civ Eng
KSCE Journal of Civil Engineering ; 24 , 7 ; 2186-2192
2020-07-01
7 pages
Article (Journal)
Electronic Resource
English
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