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Reseach Article

Satellite Image Classification Methods and Techniques: A Review

by Sunitha Abburu, Suresh Babu Golla
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 119 - Number 8
Year of Publication: 2015
Authors: Sunitha Abburu, Suresh Babu Golla
10.5120/21088-3779

Sunitha Abburu, Suresh Babu Golla . Satellite Image Classification Methods and Techniques: A Review. International Journal of Computer Applications. 119, 8 ( June 2015), 20-25. DOI=10.5120/21088-3779

@article{ 10.5120/21088-3779,
author = { Sunitha Abburu, Suresh Babu Golla },
title = { Satellite Image Classification Methods and Techniques: A Review },
journal = { International Journal of Computer Applications },
issue_date = { June 2015 },
volume = { 119 },
number = { 8 },
month = { June },
year = { 2015 },
issn = { 0975-8887 },
pages = { 20-25 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume119/number8/21088-3779/ },
doi = { 10.5120/21088-3779 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:03:31.581985+05:30
%A Sunitha Abburu
%A Suresh Babu Golla
%T Satellite Image Classification Methods and Techniques: A Review
%J International Journal of Computer Applications
%@ 0975-8887
%V 119
%N 8
%P 20-25
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Satellite image classification process involves grouping the image pixel values into meaningful categories. Several satellite image classification methods and techniques are available. Satellite image classification methods can be broadly classified into three categories 1) automatic 2) manual and 3) hybrid. All three methods have their own advantages and disadvantages. Majority of the satellite image classification methods fall under first category. Satellite image classification needs selection of appropriate classification method based on the requirements. The current research work is a study on satellite image classification methods and techniques. The research work also compares various researcher's comparative results on satellite image classification methods.

References
  1. Muhammad, S. , Aziz, G. , Aneela, N. and Muhammad, S. 2012. "Classification by Object Recognition in SatelliteImages by using Data Mining". In Proc. Proceedings of the World Congress on Engineering (WCE 2012), Vol I, July 4 - 6, London, U. K.
  2. Chaichoke, V. , Supawee, P. , Tanasak, V. and Andrew, K, S. 2011. "A Normalized Difference Vegetation Index (NDVI) Time-Series of Idle Agriculture Lands: A Preliminary Study", Engineering Journal. Vol. 15, Issue 1, pp. 9-16.
  3. Zheng, X. , Sun, X. , Fu, K. and Hongqi Wang, 2013. "Automatic Annotation of Satellite Images via Multifeature Joint Sparse Coding With Spatial Relation Constraint", IEEE Geoscience and Remote Sensing Letters, VOL. 10, NO. 4, JULY 2013, pp. 652-656.
  4. Anders Karlsson, 2003. "Classification of high resolution satellite images", August 2003, available at http://infoscience. epfl. ch/record/63248/files/TPD_Karlsson. pdf.
  5. Amanda Briney, 2014. "An Overview of Remote Sensing", May 16, 2014. [online] available at http://geography. about. com/od/geographictechnology/a/remotesensing. htm
  6. Soliman, O, S. and Mahmoud, A. S. , 2012. "A classification system for remote sensing satellite images using support vector machine with non-linear kernel functions", In proc. 8th International Conference on Informatics and Systems (INFOS), IEEE, 14-16 May 2012, pp. BIO-181,BIO-187, Cairo.
  7. Horning, N. 2004. "Land cover classification methods", Version 1. 0. American Museum of Natural History, Center for Biodiversity and Conservation. Available at http://biodiversityinformatics. amnh. org.
  8. Murugeswari, P. and Manimegalai, D. 2012. "Color Textured Image Segmentation Using ICICM – Interval Type-2 Fuzzy C-means Clustering Hybrid Approach", Engineering Journal, Vol. 16, No. 5, pp. 115-126.
  9. Al-Ahmadi, F, S. and Hames, A, S. 2009. "Comparison of Four Classification Methods to Extract Land Use and Land Cover from Raw Satellite Images for Some Remote Arid Areas, Kingdom of Saudi Arabia", Journal of King Abdulaziz University-Earth Sciences, Vol. 20, No. 1, pp: 167-191.
  10. Ahmed, R. , Mourad, Z. , Ahmed, B, H. and Mohamed, B. 2009. "An Optimal Unsupervised Satellite image Segmentation Approach Based on Pearson System and k-Means Clustering Algorithm Initialization", International Science Index, Vol. 3, No. 11, pp. 948-955.
  11. Shabnam Jabari and Yun Zhang, 2013. " Very High Resolution Satellite Image Classification Using Fuzzy Rule-Based Systems", Algorithms, vol. 6, no. 4, pp. 762-781.
  12. Chandrakala, M. and Amsaveni, R. 2013. "Classification of Remote Sensing Image Areas Using Surf Features and Latent Dirichlet Allocation", International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 3, Issue 9, pp. 178-182.
  13. David M. Blei, Andrew Y. and Michael I, J. 2003. "Latent dirichlet allocation", The Journal of Machine Learning Research, ACM, Volume 3, pp. 993-1022.
  14. Jesus, M. , Almendros-Jiménez. , Luis Domene. , and José A. Piedra-Fernández, 2013. "A framework for Ocean Satellite Image Classification Based on Ontologies", IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, VOL. 6, NO. 2, APRIL 2013, pp. 1048-1063.
  15. Martin Kuba, "OWL 2 and SWRL Tutorial" [online] available at http://dior. ics. muni. cz/~makub/owl/.
  16. Bjorn Frohlich. , Eric Bach. , Irene Walde. , Soren Hese. , Christiane Schmullius, and Joachim Denzler. 2013. "Land Cover Classification of Satellite Images using Contextual Information", ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume II-3/W1, pp. 1-6.
  17. Selim Aksoy. 2006. "Spatial Techniques for Image Classification," in C. H. Chen, ed. , Signal and Image Processing for Remote Sensing, CRC Press, pp. 491-513.
  18. Hurd, J. D. , Civco, D, L. , Gilmore, M. , Prisloe, L. and Wilson, E. 2006. "Tidal wetlandclassification from Landsat imagery using an integrated pixel-based andobject-based classification approach". In Proc. 2006 ASPRS Annual Convention, Reno.
  19. Jensen, J, R. 2005. "Introductory Digital Image Pro-cessing: A Remote Sensing Perspective", 3rd Edition, Up-per Saddle River: Prentice-Hall, 526 p.
  20. Tso, B. and Mather, P, M. 2009. "Classification Methods for Remotely Sensed Data", 2nd Ed. Chapter 2-3, Taylor and Francis Group, America.
  21. Richards, J, A. 2013. "Remote Sensing Digital Image Analysis", Springer-Verlag, Berlin, 5th Ed. 496 p.
  22. Munyati, C. H. "Use of Principal Component Analysis (PCA) of Remote Sensing Images in Wetland Change Detection on the Kafue Flats, Zambia", Geocarto Int. Vol. 19, No. 3, PP. 11-22.
  23. Kanika, K. , Anil, K, G. and Rhythm, G. 2013. "A Comparative Study of Supervised Image Classification Algorithms for Satellite Images", International Journal of Electrical, Electronics and Data Communication, Vol. 1, Issue 10, pp. 10-16.
  24. Offer, R. and Arnon, K. 2011. "Comparison of Methods for Land-Use Classification Incorporating Remote Sensing and GIS Inputs", EARSeL eProceedings, Vol. 10, No. 1, pp. 27-45.
  25. Aykut, A. , Eronat, A, H. and Necdet, T. 2004. "Comparing Different Satellite Image Classification Methods: An Application in Ayvalik District, Western Turkey",In Proc. XXth ISPRS Congress Technical Commission, ISPRS, Vol. XXXV Part B4, July 12-23, Istanbul, Turkey.
  26. Jamshid, T. , Nasser, L. and Mina, F. 2013. "Satellite Image Classification Methods and Landsat 5tm Bands", Cornell University Library.
  27. Shila, H, N. and Ali, R, S. 2010. "Comparison of Land Covers Classification Methods in Etm+ Satellite Images (Case Study: Ghamishloo Wildlife Refuge)", Journal of Environmental Research and Development, Vol. 5, No. 2, pp. 279-293.
  28. Maryam, N. , Vahid, M, Z. and Mehdi, H. 2014. "Comparing different classifications of satellite imagery in forest mapping (Case study: Zagros forests in Iran)", International Research Journal of Applied and Basic Sciences, Vol. 8, No. 7, pp. 1407-1415.
  29. Manoj, P. , Astha, B. , Potdar, M, B. , Kalubarme, M, H. and Bijendra, A. 2013. "Comparison of Various Classification Techniques for Satellite Data", International Journal Of Scientific & Engineering Research, Vol. 4, Issue 2, pp. 1-6.
  30. Subhash, T. , Akhilesh, S. and Seema, S. 2012. "Comparison of Different Image Classification Techniques for Land Use Land Cover Classification: An Application in Jabalpur District of Central India", International Journal of Remote Sensing and GIS, Vol. 1, Issue 1, pp. 26-31.
  31. Malgorzata, V, W. , Anikó, K. and rzsébet, V. 2012. "Comparison of Different Image Classification Methods in Urban Environment", In Proc. International Scientific Conference on Sustainable Development & Ecological Footprint, March 26-27 2012, Sopron, Hungary.
Index Terms

Computer Science
Information Sciences

Keywords

Satellite Image Classification Summary of reviews