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Developments and Advances in Intelligent Systems and Applications pp 1–13Cite as

Advanced Classification of Remote Sensing High Resolution Imagery. An Application for the Management of Natural Resources

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 718))

Abstract

In the last decades, there has been a decline in ecosystems natural resources. The objective of the study is to develop advanced image processing techniques applied to high resolution remote sensing imagery for the ecosystem conservation. The study area is focused in three ecosystems from The Canary Islands, Teide National Park, Maspalomas Natural Reserve and Corralejo and Islote de Lobos Natural Park. Different pre-processing steps have been applied in order to acquire high quality imagery. After an extensive analysis and evaluation of pansharpening techniques, Weighted Wavelet ‘à trous’ through Fractal Dimension Maps, in Teide and Maspalomas scenes, and Fast Intensity Hue Saturation, in Corralejo scene, are used, then, a RPC (Rational Polymodal Coefficients) model performs the orthorectification and finally, the atmospheric correction is carried out by the 6S algorithm. The final step is to generate marine and terrestrial thematic products using advanced classification techniques for the management of natural resources. Accurate thematic maps have already been obtained in Teide National Park. A comparative study of both pixel-based and object-based (OBIA) approaches was carried out, obtaining the most accurate thematic maps in both of them using Support Vector Machine classifier.

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Acknowledgements

This research has been supported by the ARTEMISAT (CGL2013-46674-R) project, funded by the Spanish Ministerio de Economía y Competitividad). Moreover, the authors want to acknowledge to the Teide National Park conservation managers (Jose Luis Martín Esquivel y Manuel Marrero Gómez) for defining the classes of interest and examining the results obtained. This work was completed while E. I-U was a Ph.D. student in the IOCAG Doctoral Program in Oceanography and Global Change and funded by the Spanish Ministerio de Economía y Competitividad with a FPI grant (BES-2014-069426).

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Authors and Affiliations

  1. Instituto de Oceanografía y Cambio Global, IOCAG, Universidad de Las Palmas de Gran Canaria, ULPGC, Las Palmas de Gran Canaria, Spain

    Edurne Ibarrola-Ulzurrun & Javier Marcello

  2. Facultad de Informática, Departamento de Arquitectura y Tecnología de Sistemas Informáticos, Universidad Politécnica de Madrid, Madrid, Spain

    Edurne Ibarrola-Ulzurrun & Consuelo Gonzalo-Martin

Authors
  1. Edurne Ibarrola-Ulzurrun
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  2. Javier Marcello
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  3. Consuelo Gonzalo-Martin
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Correspondence to Edurne Ibarrola-Ulzurrun .

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Editors and Affiliations

  1. DEI, University of Coimbra , Coimbra, Portugal

    Álvaro Rocha

  2. DSI, University of Minho, Guimarães, Portugal

    Luís Paulo Reis

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Ibarrola-Ulzurrun, E., Marcello, J., Gonzalo-Martin, C. (2018). Advanced Classification of Remote Sensing High Resolution Imagery. An Application for the Management of Natural Resources. In: Rocha, Á., Reis, L. (eds) Developments and Advances in Intelligent Systems and Applications. Studies in Computational Intelligence, vol 718. Springer, Cham. https://doi.org/10.1007/978-3-319-58965-7_1

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  • DOI: https://doi.org/10.1007/978-3-319-58965-7_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-58963-3

  • Online ISBN: 978-3-319-58965-7

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