Journal of the Indian Society of Remote Sensing

, Volume 46, Issue 8, pp 1223–1232 | Cite as

An Extended Approach of Particle Swarm Optimization for Shoreline Extraction from RASAT Imagery

  • Hatice Catal ReisEmail author
  • Bülent Bayram
  • Salih Bozkurt
  • Abdulkadir Ince
  • Nusret Demir
  • Dursun Zafer Seker
Research Article


This study presents an extended shoreline detection approach from pansharpened images of Turkish RASAT satellite which covers red, green and blue bands of the optical spectrum with 15 m ground resolution and panchromatic band with 7.5 m spatial resolution. The Lake Ercek of Turkey has been selected as the study area, which is a tectonic lake and home to a variety of water birds. The satellite images of the lake taken in 2013 and 2014 were considered for analysis. The proposed shoreline extraction system consists of a sequence of image processing steps in which simple linear clustering (SLIC) and particle swarm optimization (PSO) are the main components. SLIC was used to create superpixels that form basis for object-based image analysis while PSO was employed for classifying objects into corresponding classes. The resulting images still contained unwanted artefacts; therefore, a post-processing step was performed to improve the accuracy of segmentation by applying thresholding, morphological processing, and manual editing for noise removal. The proposed framework was applied on two temporal RASAT images to test the variations of defined parameter settings. The success of the proposed system was to obtain shorelines with satisfying accuracy without using NIR band. Finally, the extracted shorelines were vectorised and compared with manually digitized shorelines from pansharpened satellite images for accuracy assessment.


Particle swarm optimization Simple linear clustering Image processing Shoreline extraction 



This study presents the preliminary results of the algorithms which will also be used in the project entitled “Automatic 3D Shoreline Extraction and Analysis from UAV and UAV-LIDAR Data for Sustainable Shoreline Monitoring: Case Study of Terkos (Istanbul)” which is supported by TUBITAK (The Scientific and Technological Research Council of Turkey) with Project Number 115Y718.


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Copyright information

© Indian Society of Remote Sensing 2018

Authors and Affiliations

  • Hatice Catal Reis
    • 1
    Email author
  • Bülent Bayram
    • 2
  • Salih Bozkurt
    • 2
  • Abdulkadir Ince
    • 2
  • Nusret Demir
    • 3
  • Dursun Zafer Seker
    • 4
  1. 1.Department of Geomatics EngineeringGumushane UniversityGumushaneTurkey
  2. 2.Department of Geomatics EngineeringYildiz Technical UniversityEsenler, IstanbulTurkey
  3. 3.Department of Space Science and Technologies, Faculty of ScienceRemote Sensing Application and Research CentreAntalyaTurkey
  4. 4.Department of Geomatics EngineeringIstanbul Technical UniversityMaslak, IstanbulTurkey

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