Optical-flow-based approach for the detection of shoreline changes using remote sensing data

Majed Bouchahma, Walid Barhoumi, Wanglin Yan, Hamood Al Wardi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This research presents an automatic method to detect and evaluate the shoreline changes from Landsat satellite images. In fact, a method, that we called Lukas-Kanade Adapted for Coastal Changes (LKA2C), has been developed to calculate and detect the changes around the study region. Mainly the proposed method is based on SURF algorithm to detect the study region from the satellite image. Then, Canny edge detector was used on NDWI images to detect the shorelines. Finally, the pyramidal Lukas-Kanade optical flow algorithm was adapted to detect and to calculate the rates of changes. Realized experiments on real satellite images of the island of Djerba in Tunisia proved the effectiveness of the proposed method.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE/ACS 14th International Conference on Computer Systems and Applications, AICCSA 2017
PublisherIEEE Computer Society
Pages184-189
Number of pages6
Volume2017-October
ISBN (Electronic)9781538635810
DOIs
Publication statusPublished - 2018 Mar 7
Event14th IEEE/ACS International Conference on Computer Systems and Applications, AICCSA 2017 - Hammamet, Tunisia
Duration: 2017 Oct 302017 Nov 3

Other

Other14th IEEE/ACS International Conference on Computer Systems and Applications, AICCSA 2017
CountryTunisia
CityHammamet
Period17/10/3017/11/3

Fingerprint

Optical flows
Remote sensing
Satellites
Detectors
Experiments

Keywords

  • Coastal changes
  • DSCF
  • LKA2C
  • Lukas-Kanade
  • Optical flow
  • SURF

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Signal Processing
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Bouchahma, M., Barhoumi, W., Yan, W., & Wardi, H. A. (2018). Optical-flow-based approach for the detection of shoreline changes using remote sensing data. In Proceedings - 2017 IEEE/ACS 14th International Conference on Computer Systems and Applications, AICCSA 2017 (Vol. 2017-October, pp. 184-189). IEEE Computer Society. https://doi.org/10.1109/AICCSA.2017.173

Optical-flow-based approach for the detection of shoreline changes using remote sensing data. / Bouchahma, Majed; Barhoumi, Walid; Yan, Wanglin; Wardi, Hamood Al.

Proceedings - 2017 IEEE/ACS 14th International Conference on Computer Systems and Applications, AICCSA 2017. Vol. 2017-October IEEE Computer Society, 2018. p. 184-189.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Bouchahma, M, Barhoumi, W, Yan, W & Wardi, HA 2018, Optical-flow-based approach for the detection of shoreline changes using remote sensing data. in Proceedings - 2017 IEEE/ACS 14th International Conference on Computer Systems and Applications, AICCSA 2017. vol. 2017-October, IEEE Computer Society, pp. 184-189, 14th IEEE/ACS International Conference on Computer Systems and Applications, AICCSA 2017, Hammamet, Tunisia, 17/10/30. https://doi.org/10.1109/AICCSA.2017.173
Bouchahma M, Barhoumi W, Yan W, Wardi HA. Optical-flow-based approach for the detection of shoreline changes using remote sensing data. In Proceedings - 2017 IEEE/ACS 14th International Conference on Computer Systems and Applications, AICCSA 2017. Vol. 2017-October. IEEE Computer Society. 2018. p. 184-189 https://doi.org/10.1109/AICCSA.2017.173
Bouchahma, Majed ; Barhoumi, Walid ; Yan, Wanglin ; Wardi, Hamood Al. / Optical-flow-based approach for the detection of shoreline changes using remote sensing data. Proceedings - 2017 IEEE/ACS 14th International Conference on Computer Systems and Applications, AICCSA 2017. Vol. 2017-October IEEE Computer Society, 2018. pp. 184-189
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