Reconstruction the Missing Pixels for Landsat ETM+SLC-off Images Using Multiple Linear Regression Model

Asmaa S. Abdul Jabar, Ghazali B. Sulong, Loay E. George, Mohd Shafry, Zinah S. Abduljabar

Abstract


On 31 May 2003, the scan line corrector (SLC) of the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) sensor which compensates for the forward motion of the satellite in the imagery acquired  failed permanently, resulting in loss of the ability to scan about 20% of the pixels in each Landsat 7 SLC-off image. This permanent failure has seriously hampered the scientific applications of ETM+ images. In this study, an innovative gap filling approach has been introduced to recover the missing pixels in the SLC-off images using multi-temporal ETM+ SLC-off auxiliary fill images. A correlation is established between the corresponding pixels in the target SLC-off image and two fill images in parallel using the multiple linear regressions (MLR) model. Simulated and actual SLC-off ETM+ images were used to assess the performance of the proposed method by comparing with multi-temporal data based methods, the LLHM method which is based on simple linear regression (SLR) model. The qualitative and quantitative evaluations indicate that the proposed method can recover the value of un-scanned pixels accurately, especially in heterogeneous landscape and even with more temporally distant fill images.

Keywords


ETM+SLC-off images, gap filling, multiple Linear Regression (MLR), simple linear regression (SLR).

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References


Boloorani, A.D., Erasmi, S. and Kappas, M., 2008, February. Multi-source image reconstruction: exploitation of EO-1/ALI in Landsat-7/ETM+ SLC-off gap filling. In Electronic Imaging 2008 (pp. 681219-681219). International Society for Optics and Photonics.

Boloorani, A.D., Erasmi, S. and Kappas, M., 2008. Multi-source remotely sensed data combination: Projection transformation gap-fill procedure. Sensors, 8(7), pp.4429-4440.

Bonate, P. L., 2011. Linear Models and Regression:Ch.2, inUSA,(2nd Ed.): Pharmacokinetic- Pharmacodynamic Modeling and Simulation, Springer, Science+Business Media, LLC, pp.61-100.

Chen, F., Tang, L. and Qiu, Q., 2010, June. Exploitation of CBERS-02B as auxiliary data in recovering the Landsat7 ETM+ SLC-off image. In Geoinformatics, 2010 18th International Conference on (pp. 1-6). IEEE-USA.

Chen, F., Tang, L., Wang, C. and Qiu, Q., 2011. Recovering of the thermal band of Landsat 7 SLC-off ETM+ image using CBERS as auxiliary data. Advances in Space Research, 48(6), pp.1086-1093.

Chen, F., Ye, H. and Zhao, X., 2012. Making Use of the Landsat 7 SLC-off ETM+ Image Through Different Recovering Approaches. Rijeka, Croatia: INTECH Open Access Publisher.

Chen, J., Zhu, X., Vogelmann, J.E., Gao, F. and Jin, S., 2011. A simple and effective method for filling gaps in Landsat ETM+ SLC-off images. Remote Sensing of Environment, 115(4), pp.1053-1064.

Desai, M. and Ganatra, A., 2012. Survey on gap filling in satellite images and inpainting algorithm. International Journal of Computer Theory and Engineering, 4(3), p.341.

Guo, G., You, W., Qian, G. and Shao, W., 2015. Parallel maximum likelihood estimator for multiple linear regression models. Journal of Computational and Applied Mathematics, 273, pp.251-263.

He, Q., Shan, B., Ma, H., Chen, Y. and Wang, X., 2011, July. Research on Algorithms for Recovering Landsat-7 Gap Data. In Control, Automation and Systems Engineering (CASE), 2011 International Conference on (pp. 1-4). IEEE-USA.

Hossain, M. S., Bujang, J. S., Zakaria, M. H., and Hashim, M., 2015. Assessment of Landsat 7 Scan Line Corrector-off data gap-filling methods for seagrass distribution mapping. International Journal of Remote Sensing, 36(4), pp 1188-1215.

Hu, W., Li, M., Liu, Y., Huang, Q. and Mao, K., 2011, June. A new method of restoring ETM+ SLC-off images based on multi-temporal images. In Geoinformatics, 2011 19th International Conference on (pp. 1-4). IEEE-USA.

Jabar, A., S. , Sulong, G. and George, L.E., 2014. SURVEY ON GAP FILLING ALGORITHMS IN LANDSAT 7 ETM+ IMAGES. Journal of Theoretical & Applied Information Technology, 63(1).

Jiang, Y., Lan, T. and Wu, L., 2009, December. A Comparison Study of Missing Value Processing Methods in time series data mining. In Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on (pp.1-4). IEEE-USA.

Lu, G.Y. and Wong, D.W., 2008. An adaptive inverse-distance weighting spatial interpolation technique. Computers & Geosciences, 34(9), pp.1044-1055.

Markham, B.L., Storey, J.C., Williams, D.L. and Irons, J.R., 2004. Landsat sensor performance: history and current status. Geoscience and Remote Sensing, IEEE Transactions on, 42(12), pp.2691-2694.

Maxwell, S., 2004. Filling Landsat ETM+ SLC-off gaps using a segmentation model approach. Photogrammetric Engineering and Remote Sensing, 70(10), pp.1109-1112.

Maxwell, S.K., Schmidt, G.L. and Storey, J.C., 2007. A multi‐scale segmentation approach to filling gaps in Landsat ETM+ SLC‐off images. International Journal of Remote Sensing, 28(23), pp.5339-5356.

Mohammdy, M., Moradi, H.R., Zeinivand, H., Temme, A.J.A.M., Pourghasemi, H.R. and Alizadeh, H., 2014. Validating gap-filling of Landsat ETM+ satellite images in the Golestan Province, Iran. Arabian Journal of Geosciences, 7(9), pp.3633-3638.

Prasomphan, S., 2012, December. Imputing Landsat7 ETM+ with SLC-off image using the similarity measurement between two clusters. In Future Generation Communication Technology (FGCT), 2012 International Conference on (pp.190-195). IEEE-USA.

Pringle, M.J., Schmidt, M. and Muir, J.S., 2009. Geostatistical interpolation of SLC-off Landsat ETM+ images. ISPRS Journal of Photogrammetry and Remote Sensing, 64(6), pp.654-664.

Reza, M.M. and Ali, S.N., 2008. Using IRS products to recover 7ETM+ defective images. American Journal of Applied Sciences, 5(6), pp.618-625.

Roy, D.P., Ju, J., Lewis, P., Schaaf, C., Gao, F., Hansen, M. and Lindquist, E., 2008. Multi-temporal MODIS–Landsat data fusion for relative radiometric normalization, gap filling, and prediction of Landsat data. Remote Sensing of Environment, 112(6), pp.3112-3130.

Rulloni, V., Bustos, O. and Flesia, A.G., 2012. Large gap imputation in remote sensed imagery of the environment. Computational Statistics & Data Analysis, 56(8), pp.2388-2403.

Scaramuzza, P., Micijevic, E. and Chander, G., 2004. SLC gap-filled products phase one methodology. Landsat Technical Notes. Available from http://landsat.usgs.gov/documents/SLC_Gap_Fill_Methodology.

Shen, H., Li, X., Cheng, Q., Zeng, C., Yang, G., Li, H., and Zhang, L., 2015. Missing information reconstruction of remote sensing data: A technical review. IEEE Geoscience and Remote Sensing Magazine, 3(3), pp.61-85.

Storey, J., Scaramuzza, P., Schmidt, G. and Barsi, J., 2005, October. Landsat 7 scan line corrector-off gap filled product development. In Proceedings of Pecora, 16, pp. 23-27.

Sulong, G.,Sadiq, A. and Edwar , L., 2015. Single and Multi-source Methods for Reconstruction the Gaps in Landsat 7 ETM+ SLC-off Images. Research Journal of Applied Sciences, Engineering and Technology, 11(4), pp.423-428.

USGS & NASA., 2004, SLC-off Gap-Filled Products Gap-fill Algorithm Methodology:Phase2. Available from www.ga.gov.au/servlet/BigObjFileManager?bigobjid=GA4861.

Vavra, L. M., Fowler, D., 2010. Cramer’s Rule.

Wooldridge, J.M., 2012. Chapter 3: Multiple regression analysis: Estimation, in USA (5th Ed.), Introductory Econometrics, A Modern Approach,South Western.

Wulder, M.A., Ortlepp, S.M., White, J.C. and Maxwell, S., 2008. Evaluation of Landsat-7 SLC-off image products for forest change detection. Canadian Journal of Remote Sensing, 34(2), pp.93-99.

Zeng, C., Shen, H. and Zhang, L., 2013. Recovering missing pixels for Landsat ETM+ SLC-off imagery using multi-temporal regression analysis and a regularization method. Remote Sensing of Environment, 131, pp.182-194.

Zhang, C., Li, W. and Travis, D., 2007. Gaps‐fill of SLC‐off Landsat ETM+ satellite image using a geostatistical approach. International Journal of Remote Sensing, 28(22), pp.5103-5122.

Zhu, X. and Liu, D., 2014. MAP-MRF approach to Landsat ETM+ SLC-Off image classification. Geoscience and Remote Sensing, IEEE Transactions on, 52(2), pp.1131-1141.

Zhu, X., Liu, D. and Chen, J., 2012. A new geostatistical approach for filling gaps in Landsat ETM+ SLC-off images. Remote sensing of Environment, 124, pp.49-60.




DOI: http://dx.doi.org/10.14500/aro.10147
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Copyright (c) 2016 Asmaa S. Abdul jabar, Ghazali Sulong, Loay E. George, Mohd Shafrey, Zinah Abduljabar

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