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)
• Accepted : 2018.08.03
• Published : 2018.08.31
• 33 2

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)

References

1. Y. Lee, K. Lee, I. Seo, S. S. Ko, "Efficient Satellite Mission Scheduling Problem Using Particle Swarm Optimization", Journal of the Society of Korea Industrial and Systems Engineering, Vol.39, No.1, pp.56-63, 2016. DOI: https://dx.doi.org/10.11627/jkise.2016.39.1.056 https://doi.org/10.11627/jkise.2016.39.1.056
2. H. B. Kim, H. S. Kim, "Optimal Satellite Constellation Design for Korean Navigation Satellite System", Journal of the Society of Korea Industrial and Systems Engineering, Vol.39, No.3, pp.1-9, 2016. DOI: https://dx.doi.org/10.11627/jkise.2016.39.3.001 https://doi.org/10.11627/jkise.2016.39.3.001
3. L. M. Hwang, B. J. Lee, B. G. Yeo, J. P. Cho, K. S. Kim, "Link Relay H-ARQ mode for Throughput improvement in a Satellite Communication network", The Journal of the Institute of Internet, Broadcasting and Communication, Vol.16, No.1, pp.121-127, 2016. DOI: https://dx.doi.org/10.7236/JIIBC.2016.16.1.121 https://doi.org/10.7236/JIIBC.2016.16.1.121
4. J. Lee, J. Lim, D. Ga, "A Study on Coaxial-Structure Waveguide High-Order Mode Coupler of Ku-Band satellite tracking system for UAV", The Journal of the Institute of Internet, Broadcasting and Communication, Vol.16, No.2, pp.93-99, 2016. DOI: https://dx.doi.org/10.7236/JIIBC.2016.16.2.93 https://doi.org/10.7236/JIIBC.2016.16.2.93
5. S. Kim, S. Park, "Design and fabrication of SSPA module in Ku band for satellite terminals", The Journal of the Institute of Internet, Broadcasting and Communication, Vol.16, No.4, pp.59-64, 2016. DOI: https://dx.doi.org/10.7236/JIIBC.2016.16.4.59 https://doi.org/10.7236/JIIBC.2016.16.4.59
6. J. Y. Jeong, J. H. Park, J. M. Woo, "Design of active beam steering antenna mounted on LEO small satellite", The Journal of the Institute of Internet, Broadcasting and Communication, Vol.16, No.5, pp.197-203, 2016. DOI: https://dx.doi.org/10.7236/JIIBC.2016.16.5.197 https://doi.org/10.7236/JIIBC.2016.16.5.197
7. C. U. Baek, J. W. Jung, "A Study on Optical High-Throughput Efficiency Methods for Digital Satellite Broadcasting System", The Journal of the Institute of Internet, Broadcasting and Communication, Vol.17, No.3, pp.63-69, 2017. DOI: https://dx.doi.org/10.7236/JIIBC.2017.17.3.63 https://doi.org/10.7236/JIIBC.2017.17.3.63
8. Y. M. Lee, J. S. Shin, "Design of VHF Band Meander Sleeve Monopole Antenna for Satellite Communications", The Journal of the Institute of Internet, Broadcasting and Communication, Vol.17, No.5, pp.91-96, 2017. DOI: https://dx.doi.org/10.7236/JIIBC.2017.17.5.91 https://doi.org/10.7236/JIIBC.2017.17.5.91
9. NASA, MODIS, Key instrument aboard the Terra (originally known as EOS AM-1) and Aqua (originally known as EOS PM-1) satellites, Available From: https://modis.gsfc.nasa.gov/ (accessed Jul., 20, 2018)
10. P.S. Beck, C. Atzberger and K.A. Hogda, "Improved monitoring of vegetation dynamics at very high latitudes: A new method using MODIS NDVI," Remote Sensing of Environment, Vol. 100, pp.321-334 2006. DOI: https://doi.org/10.1016/j.rse.2005.10.021 https://doi.org/10.1016/j.rse.2005.10.021
11. P.J. Sellers, C.J. Tucker, G.J. Collatz, S.O. Los, C.O. Justice, and D.A. Dazlich, "A global $1^{\circ}$ by $1^{\circ}$ NDVI data set for climate studies. Part 2: The generation of global fields of terrestrial biophysical parameters from the NDVI ," International Journal of Remote Sensing, Vol. 151, pp. 3519-3545, 1994. DOI: https://doi.org/10.1080/01431169408954343 https://doi.org/10.1080/01431169408954343
12. A.R. Huete, K. Didan and T. Miura, "Overview of the radiometric and biophysical performance of the MODIS vegetation indices.," Remote Sensing of Environment, Vol. 83, pp. 195-213, 2002. DOI: https://doi.org/10.1016/s0034-4257(02)00096-2 https://doi.org/10.1016/s0034-4257(02)00096-2
13. J. D. Wim, L. Van, A. R. Huete and T. W. Laing, "MODIS Vegetation Index Compositing Approach: A Prototype with AVHRR Data," Remote Sensing of Environment, Vol. 69, pp. 264-280, 1999. DOI: https://doi.org/10.1016/s0034-4257(99)00022-x https://doi.org/10.1016/s0034-4257(99)00022-x
14. J. N. Hird and G. J. McDermid, "Noise reduction of NDVI time series: An empirical comparison of selected techniques," Remote Sensing of Environment, Vol. 113, pp. 248-258, 2009. DOI: https://doi.org/10.1016/j.rse.2008.09.003 https://doi.org/10.1016/j.rse.2008.09.003
15. J. Gu, X. Li, C. Huang and G. S. Okin, "Simplified data assimilation method for reconstructing time-series MODIS NDVI data," Advanced Space Research, Vol. 44, pp. 501-509, 2009. DOI: https://doi.org/10.1109/igarss.2008.4779536 https://doi.org/10.1109/igarss.2008.4779536
16. P. Jonsson and L. Eklundh, "Seasonality extraction by function fitting to time series of satellite sensor data," IEEE Trans. of Geoscience Remote Sensing, Vol. 40, No. 8, pp. 1824-1832, 2002. DOI: https://doi.org/10.1109/tgrs.2002.802519 https://doi.org/10.1109/tgrs.2002.802519
17. P. Jonsson and L. Eklundh, "TIMESAT-A program for analyzing time-series of satellite sensor data," Computers and Geoscience, Vol. 30, pp. 833-845, 2004. DOI: https://doi.org/10.1016/j.cageo.2004.05.006 https://doi.org/10.1016/j.cageo.2004.05.006
18. M. E. Jakubauskas, D. R. Legates and J. H. Kastens, "Harmonic Analysis of Time-Series AVHRR NDVI Data," Photogrammetric Engineering and Remote Sensing, Vol. 67, No. 4, pp. 461-470, 2001.
19. S-H Lee, "Reconstruction and Change Monitoring of Image Series," Korean Journal of Remote Sensing, Vol. 18, pp. 157-170, 2002.
20. S-H Lee, "Speckle Removal of SAR Imagery Using a Point-Jacobian Iteration MAP Estimation," Korean Journal of Remote Sensing, Vol. 23, pp. 33-42, 2007.
21. S-H Lee, "Adaptive Reconstruction of Harmonic Time Series Using Point-Jacobian Iteration MAP Estimation and Dynamic Compositing: Simulation Study," Korean Journal of Remote Sensing, Vol. 24, pp. 79-89, 2008. DOI: https://doi.org/10.7780/kjrs.2014.30.6.12 https://doi.org/10.7780/kjrs.2014.30.6.12
22. S-H Lee, "Adaptive Reconstruction of Multi-periodic Harmonic Time Series with Only Negative Errors: Simulation Study," Korean Journal of Remote Sensing, 26(6), pp.721-730, 2010. DOI: https://doi.org/10.1109/igarss.2011.6049230 https://doi.org/10.1109/igarss.2011.6049230
23. M. Jung and E. Chang, "NDVI-based land-cover change detection using harmonic analysis," International Journal of Remote Sensing, Vol. 36. No. 4, pp. 1097-1113 2014. DOI: https://doi.org/10.7780/kjrs.2013.29.4.1 https://doi.org/10.7780/kjrs.2013.29.4.1
24. P. Bloomfield, Fourier analysis of time series: An introduction, Wiley, NY, 1976.