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International Conference on Computational Science and Its Applications

ICCSA 2020: Computational Science and Its Applications – ICCSA 2020 pp 270–282Cite as

Assessing Satellite Image Time Series Clustering Using Growing SOM

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 12253)

Abstract

Mapping Earth land use and cover changes is crucial to understand agricultural dynamics. Recently, analysis of time series extracted from Earth observation satellite images has been widely used to produce land use and cover information. In time series analysis, clustering is a common technique performed to discover patterns on data sets. In this work, we evaluate the Growing Self-Organizing Maps algorithm for clustering satellite image time series and compare it with Self-Organizing Maps algorithm. This paper presents a case study using satellite image time series associated to samples of land use and cover classes, highlighting the advantage of providing a neutral factor (called spread factor) as a parameter for GSOM, instead of the SOM grid size.

Keywords

  • Growing Self-Organized Map
  • Land use and cover
  • Machine learning

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Author information

Authors and Affiliations

  1. National Institute for Space Research (INPE), Astronautas Avenue 1758, São José dos Campos, 12227-010, São Paulo, Brazil

    Rodrigo de Sales da Silva Adeu, Karine Reis Ferreira, Pedro R. Andrade & Lorena Santos

Authors
  1. Rodrigo de Sales da Silva Adeu
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  2. Karine Reis Ferreira
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  3. Pedro R. Andrade
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  4. Lorena Santos
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Corresponding author

Correspondence to Rodrigo de Sales da Silva Adeu .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Prof. Dr. Osvaldo Gervasi

  2. University of Basilicata, Potenza, Potenza, Italy

    Beniamino Murgante

  3. Chair- Center of ICT/ICE, Covenant University, Ota, Nigeria

    Prof. Sanjay Misra

  4. University of Cagliari, Cagliari, Italy

    Dr. Chiara Garau

  5. University of Cagliari, Cagliari, Italy

    Ivan Blečić

  6. Clayton School of Information Technology, Monash University, Clayton, VIC, Australia

    David Taniar

  7. Department of Information Science, Kyushu Sangyo University, Fukuoka, Japan

    Dr. Bernady O. Apduhan

  8. University of Minho, Braga, Portugal

    Ana Maria A. C. Rocha

  9. Polytechnic University of Bari, Bari, Italy

    Prof. Eufemia Tarantino

  10. Polytechnic University of Bari, Bari, Italy

    Prof. Carmelo Maria Torre

  11. Department of Neurology, University of Massachusetts Medical School, Worcester, MA, USA

    Prof. Yeliz Karaca

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da Silva Adeu, R.d.S., Ferreira, K.R., Andrade, P.R., Santos, L. (2020). Assessing Satellite Image Time Series Clustering Using Growing SOM. In: , et al. Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science(), vol 12253. Springer, Cham. https://doi.org/10.1007/978-3-030-58814-4_19

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  • DOI: https://doi.org/10.1007/978-3-030-58814-4_19

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