Java and Bali Shoreline Change Detection Based on Structural Similarity Index Measurement of Multispectral Images


  • I Gede Wahyu Surya Dharma Universitas Bali Internasional
  • I Gede Karang Komala Putra Universitas Bali Internasional



SSIM, HMRF, Shoreline, Multispectral Image


The abstract effectively delineates the pertinent issues addressed in the research, presenting a clear exposition of the challenges associated with coastline monitoring in Indonesia. The methodology is well-defined, incorporating the utilization of Landsat images, Structural Similarity Index Measurement (SSIM), and the application of Hidden Markov Random Field for segmentation. Moreover, the influence of Indonesia's equatorial positioning on cloud cover and the subsequent application of morphological operations are appropriately highlighted. However, it is crucial to provide explicit details regarding the research findings. Specifically, the abstract should elucidate the specific outcomes or results obtained from the conducted experiments or analyses. This addition would enhance the clarity and scientific robustness of the abstract, ensuring that it accurately reflects the research objectives and their corresponding achievements. Inclusion of quantitative data or statistical analyses would be particularly valuable in this regard. This would not only bolster the abstract but also furnish a more comprehensive overview of the study's empirical contributions.


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How to Cite

Dharma IGWS, Putra IGKK. Java and Bali Shoreline Change Detection Based on Structural Similarity Index Measurement of Multispectral Images. TIERS [Internet]. 2023Dec.25 [cited 2024Jul.12];4(2):92-103. Available from: