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Remote Sensing Image Mining

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Spatial Data Mining

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Abstract

Remote sensing (RS) images are one of the main spatial data sources. The variability of image data types and their complex relationships are the main difficulties that face SDM. This chapter covers a combination of inductive learning and Bayesian classification to classify RS images, the use of rough sets to describe and classify images and extract thematic information; image retrieval based on spatial statistics; and image segmentation, facial expression analysis, and recognition utilizing cloud model and data field mapping.

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Author information

Authors and Affiliations

  1. Wuhan University, Wuhan, China

    Deren Li

  2. Beijing Institute of Technology, Beijing, China

    Shuliang Wang

  3. Tsinghua University, Beijing, China

    Deyi Li

Authors
  1. Deren Li
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  2. Shuliang Wang
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  3. Deyi Li
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Corresponding author

Correspondence to Deren Li .

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© 2015 Springer-Verlag Berlin Heidelberg

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Li, D., Wang, S., Li, D. (2015). Remote Sensing Image Mining. In: Spatial Data Mining. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48538-5_9

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  • DOI: https://doi.org/10.1007/978-3-662-48538-5_9

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-48536-1

  • Online ISBN: 978-3-662-48538-5

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