Quantitative Validation Assessment on Shorelines Extracted from Image Classification Techniques of Medium Resolution Satellite Images Based on Change Analysis

Authors

  • Syaifulnizam Abd Manaf Intelligent Computing Research Group, Faculty of Computer Science and Information Technology, Universiti Putra Malaysia
  • Norwati Mustapha Intelligent Computing Research Group, Faculty of Computer Science and Information Technology, Universiti Putra Malaysia
  • Md Nasir Sulaiman Intelligent Computing Research Group, Faculty of Computer Science and Information Technology, Universiti Putra Malaysia
  • Nor Azura Husin Intelligent Computing Research Group, Faculty of Computer Science and Information Technology, Universiti Putra Malaysia
  • Helmi Zulhaidi Mohd Shafri Geospatial Information Science Research Centre, Faculty of Engineering, Universiti Putra Malaysia
  • Mohd Radzi Abdul Hamid Coastal Management and Oceanography Research Centre, National Hydraulic Research Institute of Malaysia

Keywords:

Image classification, Medium resolution satellite image, Shoreline extraction, Validation assessment,

Abstract

Shoreline extraction provides the boundary information of land and water, which helps monitor erosions or accretions of coastal zones. Such monitoring can be performed by using satellite images rather than by using traditional ground survey. To date, shorelines can be extracted from satellite images with a high degree of accuracy by using satellite image classification techniques based on machine learning, which helps identify the land and water classes of shorelines. In this study, the results of extracted shorelines of 11 classifiers were validated by using a reference shoreline provided by the local authority. Specifically, the validation assessment was performed using Mean Shoreline Change method to examine the differences between the extracted shorelines and the reference shoreline. The research findings showed that SVM Linear attained the highest number of transects and the lowest mean distances between extracted shorelines and reference shoreline, thus rendering it as the most effective image classification technique in demarcating land and water classes. Furthermore, the findings showed that the accuracy of the extracted shoreline was not directly proportional to the accuracy of the image classification, and smoothing operation using PAEK affected the quality of extracted shorelines. Moreover, the tolerance setting that was ten times the spatial resolution of satellite images was observed to be the most optimal configuration.

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Published

2017-09-15

How to Cite

Abd Manaf, S., Mustapha, N., Sulaiman, M. N., Husin, N. A., Mohd Shafri, H. Z., & Abdul Hamid, M. R. (2017). Quantitative Validation Assessment on Shorelines Extracted from Image Classification Techniques of Medium Resolution Satellite Images Based on Change Analysis. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(2-12), 67–73. Retrieved from https://jtec.utem.edu.my/jtec/article/view/2772

Issue

Vol. 9 No. 2-12: The Challenge of Computer and Engineering in Building Sustainable Service Systems II

Section

Articles

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