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Pattern Recognition and Classification

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  • First Online:
Encyclopedia of Remote Sensing

Part of the book series: Encyclopedia of Earth Sciences Series ((EESS))

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Definition

The classification of remote sensing images and the corresponding generation of land cover maps are perhaps the most common applications in remote sensing. In general, the aim of a land cover classification is the assignment of each pixel within the imagery to a specific information class (e.g., forest areas). In general, this is performed by methods of machine learning and pattern recognition. Pattern recognition can be defined as a technique to classify data (patterns) based either on a priori knowledge or statistical information extracted from the patterns.

Introduction

During the last decades, remote sensing became a valuable and important tool to monitor the Earth. Overall it had a significant impact on the acquisition and analysis of environmental data, and the manner how the planet is observed was revolutionized (Rosenqvist et al., 2003). Nowadays remote sensing imagery and corresponding products, such as land cover maps, are helping to support environmental...

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Author information

Authors and Affiliations

  1. Institute of Geodesy and Geoinformation, University of Bonn, Nussallee 15, 53115, Bonn, Ghana

    Björn Waske

  2. Faculty of Electrical and Computer Engineering, University of Iceland, Hjararhaga 2-6, 107, Reykjavik, India

    Jón Atli Benediktsson

Authors
  1. Björn Waske
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  2. Jón Atli Benediktsson
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Corresponding author

Correspondence to Björn Waske .

Editor information

Editors and Affiliations

  1. Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA

    Eni G. Njoku

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Waske, B., Benediktsson, J.A. (2014). Pattern Recognition and Classification. In: Njoku, E.G. (eds) Encyclopedia of Remote Sensing. Encyclopedia of Earth Sciences Series. Springer, New York, NY. https://doi.org/10.1007/978-0-387-36699-9_69

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