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

위성자료의 시계열 특성에 기반한 실시간 자료 재구축

  • 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)
  • 정명희 (안양대학교 소프트웨어학과) ;
  • 이상훈 (가천대학교 산업경영공학과) ;
  • 장석우 (안양대학교 소프트웨어학과)
  • Received : 2018.07.17
  • Accepted : 2018.08.03
  • Published : 2018.08.31

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

Acknowledgement

Supported by : 한국과학재단(NRF)

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