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http://dx.doi.org/10.5762/KAIS.2018.19.8.329

Reconstruction of Remote Sensing Data based on dynamic Characteristics of Time Series Data  

Jung, Myung-Hee (Division of Software Engineering, Anyang University)
Lee, Sang-Hoon (Division of Industrial Engineering, Gachon University)
Jang, Seok-Woo (Division of Software Engineering, Anyang University)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.19, no.8, 2018 , pp. 329-335 More about this Journal
Abstract
Satellite images, which are widely used in various applications, are very useful for monitoring the surface of the earth. Since satellite data is obtained from a remote sensor, it contains a lot of noise and errors depending on observation weather conditions during data acquisition and sensor malfunction status. Since the accuracy of the data affects the accuracy and reliability of the data analysis results, noise removal and data restoration for high quality data is important. In this study, we propose a reconstruction system that models the time dependent dynamic characteristics of satellite data using a multi-period harmonic model and performs adaptive data restoration considering the spatial correlation of data. The proposed method is a real-time restoration method and thus can be employed as a preprocessing algorithm for real-time reconstruction of satellite data. The proposed method was evaluated with both simulated data and MODIS NDVI data for six years from 2011 to 2016. Experimental results show that the proposed method has the potentiality for reconstructing high quality satellite data.
Keywords
Adaptive Reconstruction; Dynamic Compositing; MODIS NDVI; Multi-period Harmonic Model; Noise Reduction;
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Times Cited By KSCI : 10  (Citation Analysis)
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