Discovering similarities in Landsat satellite images using the K-means method

Ariza Colpas Paola Patricia, Oviedo Carrascal Ana Isabel, De La Hoz Franco Emiro

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations


This article different ways for the treatment and identification of similarities in satellite images. By means of the systematic review of the literature it is possible to know the different existing forms for the treatment of this type of objects and by means of the implementation that is described, the operation of the K-means algorithm is shown to help the segmentation and analysis of characteristics associated to the color. In this type of objects, a descriptive analysis of the results thrown by the method is finally carried out.

Original languageEnglish
Pages (from-to)129-136
Number of pages8
JournalProcedia Computer Science
StatePublished - 2020
Externally publishedYes
Event11th International Conference on Ambient Systems, Networks and Technologies, ANT 2020 / 3rd International Conference on Emerging Data and Industry 4.0, EDI40 2020 / Affiliated Workshops - Warsaw, Poland
Duration: 6 Apr 20209 Apr 2020

Bibliographical note

Publisher Copyright:
© 2020 The Authors. Published by Elsevier B.V.All rights reserved.


  • Clustering
  • Multiclustering
  • Multimedia Multidimensional Georreferenced Objects
  • Satellite Images


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