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Coastline Difference Measurement (CDM) Method

Year 2020, Volume: 7 Issue: 1, 1 - 5, 26.04.2020
https://doi.org/10.30897/ijegeo.706792

Abstract

Coastline Difference Measurement (CDM) Method is designed to provide a fast and practical way to obtain distance differences between 2 taut zonal coastlines. Comparison purposes could be considered as change detection to monitoring coastal zones or obtaining accuracies while studying coastline extraction methods. In this study CDM method is explained over a coastline extraction case. In this example case, CDM method is used to measure accuracy of the estimated coastline via Extra Trees (ET) machine learning model. Main advantages and limitations of the methods are explained.

References

  • Buitinck, L.; Louppe, G.; Blondel, M.; Pedregosa, F.; Mueller, A.; Grisel, O.; Niculae, V.; Prettenhofer, P.; Gramfort, A.; Grobler, J.; Layton, R.; VanderPlas, J.; Joly, A.; Holt, B.; Varoquaux, G. API design for machine learning software: experiences from the scikit-learn project. ECML PKDD Workshop: Languages for Data Mining and Machine Learning, 2013, pp. 108–122.
  • Gazioğlu C, Yücel Y Z, Burak S., Okuş, E. and Alpar, B. (1997). Coastline change and inadequate management between Kilyos and Karaburun shoreline. Turkish Journal of Marine Sciences, 3(2): 111–122.
  • Kavzoğlu, T., Cölkesen, I. (2009). A kernel functions analysis for support vector machines for land cover classification. International Journal of Applied Earth Observation and Geoinformation, 11, 352-359.
  • Kaya, H. (2010). The Role of Local Governments in Integrated Coastal Areas Management. IU PhD thesis, Istanbul.
  • Paravolidakis, V., Ragia, L., Mairogiorgou, K., Zerkavis, ME. (2018). Automatic Coastline Extraction Using Edge Detection and Optimization Procedures, Geosciences 8, 407-425.
  • Pedregosa, F.; Varoquaux, G.; Gramfort, A.; Michel, V.; Thirion, B.; Grisel, O.; Blondel, M.; Prettenhofer, P.; Weiss, R.; Dubourg, V.; Vanderplas, J.; Passos, A.; Cournapeau, D.; Brucher, M.; Perrot, M.; Duchesnay, E. (2011). Scikit-learn: Machine Learning in Python. Journal of Machine Learning Research, 12, 2825–2830.
  • Python Software Foundation. Python Language Reference, version 3.8. Available at http://www.python.org
  • Simav, Ö., Şeker, DZ., Gazioğlu, C. (2013). Coastal inundation due to sea level rise and extreme sea state and its potential impacts: Çukurova Delta case, Turkish Journal of Earth Sciences 22 (4), 671-680, 706792 Coastline Difference Measurement (CDM) Method.
  • Yu, L., Porwal, A., Holden, EJ., Dentith, MC. (2012). Towards automatic lithological classification from remote sensing data using support vector machines. Computers & Geosciences, 45, 229-239.
  • Zhang, T., Yang, X., Hu, S., Su, F. (2013). Extraction of Coastline in Aquaculture Coast from Multispectral Remote Sensing Images: Object-Based Region Growing Integrating Edge Detection, Remote Sens. 5, 4470-4487.
Year 2020, Volume: 7 Issue: 1, 1 - 5, 26.04.2020
https://doi.org/10.30897/ijegeo.706792

Abstract

References

  • Buitinck, L.; Louppe, G.; Blondel, M.; Pedregosa, F.; Mueller, A.; Grisel, O.; Niculae, V.; Prettenhofer, P.; Gramfort, A.; Grobler, J.; Layton, R.; VanderPlas, J.; Joly, A.; Holt, B.; Varoquaux, G. API design for machine learning software: experiences from the scikit-learn project. ECML PKDD Workshop: Languages for Data Mining and Machine Learning, 2013, pp. 108–122.
  • Gazioğlu C, Yücel Y Z, Burak S., Okuş, E. and Alpar, B. (1997). Coastline change and inadequate management between Kilyos and Karaburun shoreline. Turkish Journal of Marine Sciences, 3(2): 111–122.
  • Kavzoğlu, T., Cölkesen, I. (2009). A kernel functions analysis for support vector machines for land cover classification. International Journal of Applied Earth Observation and Geoinformation, 11, 352-359.
  • Kaya, H. (2010). The Role of Local Governments in Integrated Coastal Areas Management. IU PhD thesis, Istanbul.
  • Paravolidakis, V., Ragia, L., Mairogiorgou, K., Zerkavis, ME. (2018). Automatic Coastline Extraction Using Edge Detection and Optimization Procedures, Geosciences 8, 407-425.
  • Pedregosa, F.; Varoquaux, G.; Gramfort, A.; Michel, V.; Thirion, B.; Grisel, O.; Blondel, M.; Prettenhofer, P.; Weiss, R.; Dubourg, V.; Vanderplas, J.; Passos, A.; Cournapeau, D.; Brucher, M.; Perrot, M.; Duchesnay, E. (2011). Scikit-learn: Machine Learning in Python. Journal of Machine Learning Research, 12, 2825–2830.
  • Python Software Foundation. Python Language Reference, version 3.8. Available at http://www.python.org
  • Simav, Ö., Şeker, DZ., Gazioğlu, C. (2013). Coastal inundation due to sea level rise and extreme sea state and its potential impacts: Çukurova Delta case, Turkish Journal of Earth Sciences 22 (4), 671-680, 706792 Coastline Difference Measurement (CDM) Method.
  • Yu, L., Porwal, A., Holden, EJ., Dentith, MC. (2012). Towards automatic lithological classification from remote sensing data using support vector machines. Computers & Geosciences, 45, 229-239.
  • Zhang, T., Yang, X., Hu, S., Su, F. (2013). Extraction of Coastline in Aquaculture Coast from Multispectral Remote Sensing Images: Object-Based Region Growing Integrating Edge Detection, Remote Sens. 5, 4470-4487.
There are 10 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Research Articles
Authors

Osman İsa Çelik 0000-0002-3788-9988

Cem Gazioğlu 0000-0002-2083-4008

Publication Date April 26, 2020
Published in Issue Year 2020 Volume: 7 Issue: 1

Cite

APA Çelik, O. İ., & Gazioğlu, C. (2020). Coastline Difference Measurement (CDM) Method. International Journal of Environment and Geoinformatics, 7(1), 1-5. https://doi.org/10.30897/ijegeo.706792