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International Conference on Geoinformatics and Data Analysis

ICGDA 2022: Geoinformatics and Data Analysis pp 95–105Cite as

OSM-GAN: Using Generative Adversarial Networks for Detecting Change in High-Resolution Spatial Images

Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT,volume 143)

Abstract

Detecting changes to built environment objects such as buildings/roads/etc. in aerial/satellite (spatial) imagery is necessary to keep online maps and various value-added LBS applications up-to-date. However, recognising such changes automatically is not a trivial task, and there are many different approaches to this problem in the literature. This paper proposes an automated end-to-end workflow to address this problem by combining OpenStreetMap (OSM) vectors of building footprints with a machine learning Generative Adversarial Network (GAN) model - where two neural networks compete to become more accurate at predicting changes to building objects in spatial imagery. Notably, our proposed OSM-GAN architecture achieved over 88% accuracy predicting/detecting building object changes in high-resolution spatial imagery of Dublin city centre.

Keywords

  • Change detection
  • Remote sensing
  • OpenStreetMap
  • Generative Adversarial Networks
  • GIS

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Notes

  1. 1.

    https://github.com/phillipi/pix2pix.

  2. 2.

    https://wiki.openstreetmap.org/wiki/Overpass_API.

  3. 3.

    https://docs.opencv.org/4.5.2/.

  4. 4.

    https://numpy.org/.

  5. 5.

    https://www.osi.ie/about/open-data/.

  6. 6.

    https://www.ichec.ie/about/infrastructure/kay.

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Acknowledgments

The authors wish to thank all contributors involved with the OpenStreetMap project. This research is funded by Technological University Dublin College of Arts and Tourism, SEED FUNDING INITIATIVE 2019–2020.

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Authors and Affiliations

  1. Technological University Dublin, Dublin, Ireland

    Lasith Niroshan & James D. Carswell

Authors
  1. Lasith Niroshan
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  2. James D. Carswell
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Corresponding author

Correspondence to Lasith Niroshan .

Editor information

Editors and Affiliations

  1. Multidimensional Signal Processing Group, Ecole Centrale Marseille, Marseille Cedex 13, France

    Prof. Salah Bourennane

  2. Department of Geography, Faculty of Science, Masaryk University, Brno, Czech Republic

    Petr Kubicek

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Niroshan, L., Carswell, J.D. (2022). OSM-GAN: Using Generative Adversarial Networks for Detecting Change in High-Resolution Spatial Images. In: Bourennane, S., Kubicek, P. (eds) Geoinformatics and Data Analysis. ICGDA 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 143. Springer, Cham. https://doi.org/10.1007/978-3-031-08017-3_9

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