Automated shoreline detection using natural colour composite on SPOT 5 satellite imagery

Research output: Contribution to journalArticle

Abstract

Monitoring the dynamics changes of the shoreline shape is crucial since it will heavily affect the environment and socio-economic at the region. A manual system to monitor the shoreline, especially through ground work observation is expansive and requires a lot of labor works. Hence, an autonomous system is needed by the authority to observe any shoreline change to come out with mitigation plan as early as possible. This paper proposes an automatic shoreline extraction technique for satellite imagery based on natural colour composite. The proposed technique is tested using SPOT 5 satellite imagery of Malaysia coastal area. The accuracy of the system was obtained by calculating Root Mean Square Error (RMSE) between the estimated shoreline and shoreline on the ground truth image. The results showed that the RMSE values obtained are less than 100 pixels for most of the tested images.

Original languageEnglish
Pages (from-to)4601-4604
Number of pages4
JournalAdvanced Science Letters
Volume23
Issue number5
DOIs
Publication statusPublished - 1 May 2017

Fingerprint

Satellite Imagery
Satellite imagery
SPOT
Mean square error
satellite imagery
shoreline
Color
Composite
Roots
Malaysia
Composite materials
Autonomous Systems
Monitor
Pixel
Pixels
Economics
Observation
Personnel
Monitoring
shoreline change

Keywords

  • Natural colour composite
  • Threshold
  • Vegetation indices

ASJC Scopus subject areas

  • Health(social science)
  • Computer Science(all)
  • Education
  • Mathematics(all)
  • Environmental Science(all)
  • Engineering(all)
  • Energy(all)

Cite this

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abstract = "Monitoring the dynamics changes of the shoreline shape is crucial since it will heavily affect the environment and socio-economic at the region. A manual system to monitor the shoreline, especially through ground work observation is expansive and requires a lot of labor works. Hence, an autonomous system is needed by the authority to observe any shoreline change to come out with mitigation plan as early as possible. This paper proposes an automatic shoreline extraction technique for satellite imagery based on natural colour composite. The proposed technique is tested using SPOT 5 satellite imagery of Malaysia coastal area. The accuracy of the system was obtained by calculating Root Mean Square Error (RMSE) between the estimated shoreline and shoreline on the ground truth image. The results showed that the RMSE values obtained are less than 100 pixels for most of the tested images.",
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AU - Ismail, Siti Zaleha

AU - Zulkifley, Mohd Asyraf

AU - Hussain, Aini

AU - Mustafa, Mohd. Marzuki

AU - Muad, Anuar Mikdad

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N2 - Monitoring the dynamics changes of the shoreline shape is crucial since it will heavily affect the environment and socio-economic at the region. A manual system to monitor the shoreline, especially through ground work observation is expansive and requires a lot of labor works. Hence, an autonomous system is needed by the authority to observe any shoreline change to come out with mitigation plan as early as possible. This paper proposes an automatic shoreline extraction technique for satellite imagery based on natural colour composite. The proposed technique is tested using SPOT 5 satellite imagery of Malaysia coastal area. The accuracy of the system was obtained by calculating Root Mean Square Error (RMSE) between the estimated shoreline and shoreline on the ground truth image. The results showed that the RMSE values obtained are less than 100 pixels for most of the tested images.

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