Abstract
This paper presents a land cover feature extraction technique based on the extended species abundance model of biogeography [15, 18] where we consider the HSI as a function of different combinations of SIVs depending upon the characteristics of the habitat under consideration as an extension to the classical BBO [33, 39]. Making use of the proposed hypotheses, we calculate the HSI of each of the habitats representing the image pixels using two different functions namely entropy and standard deviation and hence maximize the classification efficiency achieved by adapting to dynamic changes in the HSI function definition. The proposed algorithm has been successfully tested on two different multi-spectral satellite image datasets. We also incorporate the above extended model in our previously designed hybrid bio-inspired intelligent classifier [16] and compare its performance with the original hybrid classifier and twelve other classifiers on the 7-Band Alwar Image.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Alpaydin, E.: Introduction to Machine Learning. MIT Press, United States of America (2004)
Bansal, S., Gupta, D., Panchal, V.K., Kumar, S.: Swarm Intelligence Inspired Classifiers in Comparison with Fuzzy and Rough Classifiers: A Remote Sensing Approach. In: Ranka, S., et al. (eds.) IC3 2009. CCIS, vol. 40, pp. 284–294. Springer, Heidelberg (2009)
Bhattacharya, A., Chattopadhyay, P.K.: Application of biogeography-based optimization for solving multi-objective economic emission load dispatch problems. Electric Power Components and Systems 38(3), 340–365 (2010)
Blum, C.: Ant colony optimization: Introduction and recent trends. Phys. Life Reviews 2, 353–373 (2005)
Bratton, D., Kennedy, J.: Defining a Standard for Particle Swarm Optimization. In: Proceedings of the 2007 IEEE Swarm Intelligence Symposium, Honolulu, Hawaii, USA (2007)
Clerc, M.: Particle Swarm Optimization. ISTE Publishing, Amsterdam (2006)
Currie, D.J.: Global Ecology and Biogeography. Blackwell Publishing Ltd., U.K (2012)
Dorigo, M., Stuetzle, T.: Ant Colony Optimization. MIT Press (2004)
Otero, F.E.B., Freitas, A.A., Johnson, C.G.: cAnt-Miner: An Ant Colony Classification Algorithm to Cope with Continuous Attributes. Springer, Heidelberg (2008)
Holden, N., Freitas, A.A.: A hybrid particle swarm/ant colony algorithm for the classification of hierarchical biological data. In: IEEE Swarm Intelligence Symposium (SIS 2005), pp. 100–107 (2005)
Goel, L., Panchal, V.K., Gupta, D.: Embedding Expert knowledge to Hybrid Bio-Inspired Techniques- An Adaptive Strategy Towards Focused Land Cover Feature Extraction. International Journal of Computer Science & Information Security 8(2), 244–253 (2010) ISSN: 1947-5500
Goel, L., Gupta, D., Panchal, V.K.: Performance Governing Factors of BBO for Land Cover Feature Extraction: An Analytical Study. In: World Congress on Information and Communication Technologies (WICT), pp. 165–170. IEEE Xplore (2011), doi:10.1109/WICT.2011.6141237
Goel, L., Gupta, D., Panchal, V.K.: Biogeography and Plate Tectonics based Optimization for Water body Extraction in Satellite Images. In: Deep, K., Nagar, A., Pant, M., Bansal, J.C. (eds.) Proceedings of the International Conf. on SocProS 2011. AISC, vol. 131, pp. 1–13. Springer, Heidelberg (2012)
Goel, L., Gupta, D., Panchal, V.K.: Information Sharing in Swarm Intelligence Techniques: A Perspective Application for Natural Terrain Feature Elicitation. International Journal of Computer Applications 32(2), 34–40 (2011)
Goel, L., Gupta, D., Panchal, V.K.: Dynamic model of Blended Biogeography based Optimization for Land Cover Feature Extraction. In: Parashar, M., Kaushik, D., Rana, O.F., Samtaney, R., Yang, Y., Zomaya, A. (eds.) IC3 2012. CCIS, vol. 306, pp. 8–19. Springer, Heidelberg (2012)
Goel, L., Gupta, D., Panchal, V.K.: Hybrid bio-inspired techniques for land cover feature extraction: A remote sensing perspective. Applied Soft Computing 12(2), 832–849 (2012)
Goel, L., Gupta, D., Panchal, V.K., Abraham, A.: Taxonomy of Computational Intelligence: A Remote Sensing Perspective. In: World Congress on Nature and Biologically Inspired Computing (NaBIC), November 5-9, pp. 200–206. IEEE Publications, Mexico City (2012), doi:10.1109/NaBIC.2012.6402262
Goel, L., Gupta, D., Panchal, V.K.: Extended Species Abundance Models of Biogeography Based Optimization. In: IEEE Conference on Computational Intelligence, Modelling and Simulation (CIMSim), pp. 7–12. IEEE Xplore and CSDL, Kuantan (2012)
Goldberg, D.: Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley, Reading (1989)
Gupta, D., Das, B., Panchal, V.K.: A Methodical Study for the Extraction of Landscape Traits Using Membrane Computing Technique. In: GEM 2011, WORLDCOMP (2011)
Gupta, S., Arora, A., Panchal, V.K., Goel, S.: Extended Biogeography based Optimization for Natural Terrain Feature Classification from Satellite Remote Sensing Images. In: Aluru, S., Bandyopadhyay, S., Catalyurek, U.V., Dubhashi, D.P., Jones, P.H., Parashar, M., Schmidt, B. (eds.) IC3 2011. CCIS, vol. 168, pp. 262–269. Springer, Heidelberg (2011)
Hand, D.J.: Construction and Assessment of Classification Rules. Wiley (1997)
Johal, N.K., Singh, S., Kundra, H.: A hybrid FPAB/BBO Algorithm for Satellite Image Classification. International Journal of Computer Applications 6(5), 31–36 (2010)
Kang, F., Li, J., Xu, Q.: Damage detection based on improved particle swarm optimization using vibration data. Applied Soft Computing 12(8), 2329–2335 (2012)
Kiefer, R.W., Lillesand, T.M.: Principles of Remote Sensing (2006)
Kumar, S., Gupta, D., Panchal, V.K., Kumar, S.: Enabling Web Services for Classification of Satellite Images. In: International Conference on Semantic Web and Web Services (SWWS 2009), Orlando, FL, USA (2009)
Long III, W., Shobha Srihar, N.: Land cover classification of SSC image: unsupervised and supervised classification using ERDAS Imagine. In: Proceedings of Geoscience and Remote Sensing Symposium, Unsupervised and Supervised Classifications (IGARSS 2004), vol. 4, pp. 20–24 (2004)
Ma, H.: An analysis of the equilibrium of migration models for biogeography-based optimization. Information Sciences 180, 3444–3464 (2010)
Ma, H., Simon, D.: Blended Biogeography based optimization for constrained optimization. Engineering Applications of Artificial Intelligence 24(3), 517–525 (2011)
Ma, H., Ni, S., Sun, M.: Equilibrium Species Counts and Migration Model Tradeoffs for Biogeography based Optimization. In: IEEE Conference on Decision and Control, pp. 3306–3310 (2009)
Ǿhrn, A., Komorowski, J.: A Rough Set tool kit for analysis of data. In: Proc. 3rd International Joint Conference on Information Sciences, Durham, NC, pp. 403–407 (1997)
Omkar, S.N., Manoj, K.M., Mudigere, D., Muley, D.: Urban Satellite Image Classification using Biologically Inspired Techniques. In: Proceedings of IEEE International Symposium on Industrial Electronics, Vigo, Spain, pp. 1767–1772 (2007)
Panchal, V., Singh, P., Kaur, N., Kundra, H.: Biogeography based satellite image classification. International Journal of Computer Science and Information Security 6(2), 269–274 (2009)
Panchal, V.K., Singhal, N., Kumar, S., Bhakna, S.: Rough-fuzzy Sets Tie-up for Geospatial Information. In: ISRO’s International Conference on Emerging Scenario in Space Technology & Applications (ESSTA 2008), Chennai, vol. 1 (2008)
Pappula, L.: Application of real coded genetic algorithm for target sensing. In: Sixth International Conference on Sensing Technology (ICST), Kolkata, India, pp. 69–72 (2012)
Parpinelli, S., Lopes, H.S., Freitas, A.A.: Data Mining with an Ant Colony Optimization Algorithm. IEEE Transactions on Evolutionary Computation, Special Issue on Ant Colony Algorithms 6(4), 321–332 (2002)
Pawlak, Z.: Rough Set Theory and its Applications to Data Analysis. Cybernetics and Systems 29(7), 661–688 (1998)
Pawlak, Z.: Rough Sets. International Journal of Computer and Information Science 11, 341–356 (1982)
Simon, D.: Biogeography Based Optimization. IEEE Transactions on Evolutionary Computation 12(6), 702–713 (2008)
Simon, D.: A Dynamic System Model of Biogeography based Optimization. Applied Soft Computing 11(8), 5652–5661 (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Goel, L., Gupta, D., Panchal, V.K. (2013). Land Cover Feature Extraction of Multi-spectral Satellite Images Based on Extended Species Abundance Model of Biogeography. In: Gavrilova, M.L., Tan, C.J.K., Abraham, A. (eds) Transactions on Computational Science XXI. Lecture Notes in Computer Science, vol 8160. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45318-2_4
Download citation
DOI: https://doi.org/10.1007/978-3-642-45318-2_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-45317-5
Online ISBN: 978-3-642-45318-2
eBook Packages: Computer ScienceComputer Science (R0)