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Visualization of Farm Land Use by Classifying Satellite Images

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Cooperative Design, Visualization, and Engineering (CDVE 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11151))

Abstract

Land use mapping is becoming increasingly important in agriculture. Nowadays, satellite visualizations of farmland are available. On the other hand, the machine learning techniques have been advanced rapidly. This paper comprehensively investigates the use of the recently developed machine learning techniques to automatize land use mapping. Our comprehensive experiments are reported. The results of comparison experiments have demonstrated the performance of the algorithms on land use mapping.

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Author information

Authors and Affiliations

  1. Charles Sturt University, Albury, NSW, 2640, Australia

    Xiaojin Liao & Xiaodi Huang

  2. Swinburne University of Technology, Melbourne, VIC, 3122, Australia

    Weidong Huang

Authors
  1. Xiaojin Liao
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  2. Xiaodi Huang
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  3. Weidong Huang
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Corresponding author

Correspondence to Weidong Huang .

Editor information

Editors and Affiliations

  1. University of Balearic Islands, Palma de Mallorca, Spain

    Yuhua Luo

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Cite this paper

Liao, X., Huang, X., Huang, W. (2018). Visualization of Farm Land Use by Classifying Satellite Images. In: Luo, Y. (eds) Cooperative Design, Visualization, and Engineering. CDVE 2018. Lecture Notes in Computer Science(), vol 11151. Springer, Cham. https://doi.org/10.1007/978-3-030-00560-3_40

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  • DOI: https://doi.org/10.1007/978-3-030-00560-3_40

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00559-7

  • Online ISBN: 978-3-030-00560-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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