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Quasi-based hierarchical clustering for land cover mapping using satellite images

Senthilnath, J and Raj, Ankur and Omkar, SN and Mani, V and Kumar, Deepak (2013) Quasi-based hierarchical clustering for land cover mapping using satellite images. In: 7th International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA 2012) , DEC 14-16, 2012, ABV Indian Inst Informat Technol & Management Gwalior, Madhya Pradesh, INDIA, pp. 53-64.

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Official URL: http://dx.doi.org/10.1007/978-81-322-1041-2_5

Abstract

This paper presents an improved hierarchical clustering algorithm for land cover mapping problem using quasi-random distribution. Initially, Niche Particle Swarm Optimization (NPSO) with pseudo/quasi-random distribution is used for splitting the data into number of cluster centers by satisfying Bayesian Information Criteria (BIC). Themain objective is to search and locate the best possible number of cluster and its centers. NPSO which highly depends on the initial distribution of particles in search space is not been exploited to its full potential. In this study, we have compared more uniformly distributed quasi-random with pseudo-random distribution with NPSO for splitting data set. Here to generate quasi-random distribution, Faure method has been used. Performance of previously proposed methods namely K-means, Mean Shift Clustering (MSC) and NPSO with pseudo-random is compared with the proposed approach - NPSO with quasi distribution(Faure). These algorithms are used on synthetic data set and multi-spectral satellite image (Landsat 7 thematic mapper). From the result obtained we conclude that use of quasi-random sequence with NPSO for hierarchical clustering algorithm results in a more accurate data classification.

Item Type: Conference Paper
Series.: Advances in Intelligent Systems and Computing
Publisher: SPRINGER-VERLAG BERLIN
Additional Information: Copyright for this article belongs to SPRINGER-VERLAG BERLIN, GERMANY.
Keywords: Niche Particle Swarm Optimization;Faure sequence;Hierarchical clustering
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Division of Mechanical Sciences > Aerospace Engineering(Formerly Aeronautical Engineering)
Date Deposited: 22 Mar 2013 12:12
Last Modified: 27 Mar 2013 06:20
URI: http://eprints.iisc.ac.in/id/eprint/46177

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