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Year 2020, Volume: 7 Issue: 2, 213 - 220, 15.08.2020
https://doi.org/10.30897/ijegeo.713307

Abstract

References

  • Abbas, A. W., Minallh, N., Ahmad, N., Abid, S. A. R., Khan, M. A. A. (2016). K-Means and ISODATA clustering algorithms for landcover classification using remote sensing. Sindh University Research Journal-SURJ (Science Series), 48(2), pp. 315-318.
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  • Burak, S. A., Doğan, E., Gazioğlu, C. (2004). Impact of urbanization and tourism on coastal environment. Ocean & Coastal Management, 47, 515-527.
  • Büyüksalih, İ., Gazioğlu, C., Büyüksalih, G., Müftüoğlu, AE., Demir, V. (2009). Object- oriented image analysis method of using in Coastal Zone, The Nineth International Conference on the Mediterranean Coastal Environment, 1-10.
  • Carleer, A. P. and Wolff, E. (2006). Region-Based classification potential for land cover classification with very high spatial resolution satellite data, in Proceedings of 1st International Conference on Object-based Image Analysis, Austria, Vol. XXXVI, ISSN 1682-1777, 4-5.
  • Doğanyiğit, R. (2016). Works on Lakes and Wetlands. http://www.suyonetimi.gov.tr/ (Turkish)
  • Dronova, I., Gong, P., Wang, L. (2011). Object-based analysis and change detection of major wetland cover types and their classification uncertainty during the low water period at Poyang Lake, China. Remote Sensing of Environment, 115(12), 3220-3236.
  • Esetlili, MT., Bektaş Balçık, F., Balık Şanlı, f., Üstüner, M., Kalkan, K., Göksel, Ç., Gazioğlu, C. Kurucu, Y. (2018). Comparison of Object and Pixel-Based Classifications For Mapping Crops Using Rapideye Imagery: A Case Study Of Menemen Plain, Turkey,International Journal of Environment and Geoinformatics (IJEGEO), 5(2), 231-243.
  • Guariglia, A., Buonamassa, A., Losurdo, A., Saladino, R., Trivigno, M. L., Zaccagnino, A., Colangelo, A., (2006). A multisource approach for coastline mapping and identification of shoreline changes. Annals of geophysics, 49(1).
  • Haibo, Y., Zongmin, W., Hongling, Z., Yu, G. (2011). Water body extraction methods study based on RS and GIS. Procedia Environmental Sciences, 10, pp. 2619-2624.
  • Kalkan, K., Bayram, B., Maktav, D., Sunar, F. (2013). Comparison of support vector machine and object based classification methods for coastline detection. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 7, W2.
  • Kaplan, G., Avdan, U. (2017). Object-based water body extraction model using Sentinel-2 satellite imagery. European Journal of Remote Sensing, 50(1), pp. 137-143.
  • Li, X. & Damen, M. C. (2010). Coastline change detection with satellite remote sensing for environmental management of the Pearl River Estuary, China. Journal of Marine Systems, 82, pp. 54-61.
  • Lillesand, T., Kiefer, R. W. Chipman, J. (2014). Remote sensing and image interpretation. John Wiley & Sons. Rasuly, A., Naghdifar, R. Rasoli, M. (2010). Monitoring of Caspian Sea coastline changes using object-oriented techniques. Procedia Environmental Sciences, 2, pp. 416-426.
  • Shang, K., Zhang, X., Dong, Z. Zhang, X. (2012). Information extraction method on coastal wetland using TM data: A case study in Dongying, Shandong, China. In 2012 Second International Workshop on Earth Observation and Remote Sensing Applications (pp. 77-81). IEEE.
  • Strahler, A.H., 1980. The use of prior probabilities in maximum likelihood classification of remotely-sensed data. Remote Sensing of Environment, 10, pp. 135–163.
  • URL1:https://www.sentinel-hub.com/eoproducts/ndwi-normalized-difference-water-index
  • Zeki, S. (2012). Assessing microbial water quality by membrane filtration and quantitative polymerase chain reaction (qPCR) methods at Golden Horn (PhD thesis). Istanbul University, Istanbul, Turkey.

Comparison of Pixel-Based and Object-Based Classification Methods in Determination of Wetland Coastline

Year 2020, Volume: 7 Issue: 2, 213 - 220, 15.08.2020
https://doi.org/10.30897/ijegeo.713307

Abstract

Tuz Lake and its surrounding lakes (Tersakan Lake, Duden Lake, Bolluk Lake, Esmekaya Lake, Kopek Lake, Akgol) are placed in the Central Anatolia region. These lakes maintain the ecosystem integrity and make a good habitat for numerous bird species, especially flamingos. The Duden Lake is located within the boundaries of the Tuz Lake Special Environmental Protection Area and was declared as a protected area in 1992. The surface and underground water around Kulu District of Konya feed the Duden Lake, which is tectonically formed through the Kulu Stream. The lake with the average area of 860 hectares is unfortunately in risk of extinction. Remote sensing has been the most useful tool to obtain spatial and temporal information about wetlands and it provides up-to-date, accurate, and cost-effective information. Remote sensing methods and applications are used quite effectively on wetlands. The traditional pixel-based classification method is applied to different satellite images in wetlands over many decades, and the usage of object-based classification method has started recently comparing to the pixel-based one. This study aimed to determine the coastline of the wetlands. Sentinel 2 satellite images, which provide free access and high spatial resolution, are used to observe the coastline of Duden Lake through the usage of pixel-based and object-based classification methods in all the seasons. The applicability of the methods in determination of shallow wetland coastline is studied and evaluated. The results of the pixel-based and the object-based classification images are compared by accuracy assessment.

References

  • Abbas, A. W., Minallh, N., Ahmad, N., Abid, S. A. R., Khan, M. A. A. (2016). K-Means and ISODATA clustering algorithms for landcover classification using remote sensing. Sindh University Research Journal-SURJ (Science Series), 48(2), pp. 315-318.
  • Alesheikh, A. A., Ghorbanali, A., Nouri, N. (2007). Coastline change detection using remote sensing. International Journal of Environmental Science & Technology, 4(1), pp. 61-66.
  • Algancı, U., Sertel, E., Kaya, Ş. (2018). Determination of the olive trees with object based classification of Pleiades satellite image", International Journal of Environment and Geoinformatics (IJEGEO) 132-139.
  • Blaschke, T., Hay, G. J., Weng, Q., Resch, B. (2011). Collective sensing: Integrating geospatial technologies to understand urban systems-an overview. Remote Sensing, 3(8), 1743-1776.
  • Burak, S. A., Doğan, E., Gazioğlu, C. (2004). Impact of urbanization and tourism on coastal environment. Ocean & Coastal Management, 47, 515-527.
  • Büyüksalih, İ., Gazioğlu, C., Büyüksalih, G., Müftüoğlu, AE., Demir, V. (2009). Object- oriented image analysis method of using in Coastal Zone, The Nineth International Conference on the Mediterranean Coastal Environment, 1-10.
  • Carleer, A. P. and Wolff, E. (2006). Region-Based classification potential for land cover classification with very high spatial resolution satellite data, in Proceedings of 1st International Conference on Object-based Image Analysis, Austria, Vol. XXXVI, ISSN 1682-1777, 4-5.
  • Doğanyiğit, R. (2016). Works on Lakes and Wetlands. http://www.suyonetimi.gov.tr/ (Turkish)
  • Dronova, I., Gong, P., Wang, L. (2011). Object-based analysis and change detection of major wetland cover types and their classification uncertainty during the low water period at Poyang Lake, China. Remote Sensing of Environment, 115(12), 3220-3236.
  • Esetlili, MT., Bektaş Balçık, F., Balık Şanlı, f., Üstüner, M., Kalkan, K., Göksel, Ç., Gazioğlu, C. Kurucu, Y. (2018). Comparison of Object and Pixel-Based Classifications For Mapping Crops Using Rapideye Imagery: A Case Study Of Menemen Plain, Turkey,International Journal of Environment and Geoinformatics (IJEGEO), 5(2), 231-243.
  • Guariglia, A., Buonamassa, A., Losurdo, A., Saladino, R., Trivigno, M. L., Zaccagnino, A., Colangelo, A., (2006). A multisource approach for coastline mapping and identification of shoreline changes. Annals of geophysics, 49(1).
  • Haibo, Y., Zongmin, W., Hongling, Z., Yu, G. (2011). Water body extraction methods study based on RS and GIS. Procedia Environmental Sciences, 10, pp. 2619-2624.
  • Kalkan, K., Bayram, B., Maktav, D., Sunar, F. (2013). Comparison of support vector machine and object based classification methods for coastline detection. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 7, W2.
  • Kaplan, G., Avdan, U. (2017). Object-based water body extraction model using Sentinel-2 satellite imagery. European Journal of Remote Sensing, 50(1), pp. 137-143.
  • Li, X. & Damen, M. C. (2010). Coastline change detection with satellite remote sensing for environmental management of the Pearl River Estuary, China. Journal of Marine Systems, 82, pp. 54-61.
  • Lillesand, T., Kiefer, R. W. Chipman, J. (2014). Remote sensing and image interpretation. John Wiley & Sons. Rasuly, A., Naghdifar, R. Rasoli, M. (2010). Monitoring of Caspian Sea coastline changes using object-oriented techniques. Procedia Environmental Sciences, 2, pp. 416-426.
  • Shang, K., Zhang, X., Dong, Z. Zhang, X. (2012). Information extraction method on coastal wetland using TM data: A case study in Dongying, Shandong, China. In 2012 Second International Workshop on Earth Observation and Remote Sensing Applications (pp. 77-81). IEEE.
  • Strahler, A.H., 1980. The use of prior probabilities in maximum likelihood classification of remotely-sensed data. Remote Sensing of Environment, 10, pp. 135–163.
  • URL1:https://www.sentinel-hub.com/eoproducts/ndwi-normalized-difference-water-index
  • Zeki, S. (2012). Assessing microbial water quality by membrane filtration and quantitative polymerase chain reaction (qPCR) methods at Golden Horn (PhD thesis). Istanbul University, Istanbul, Turkey.
There are 20 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Research Articles
Authors

Adalet Dervisoglu 0000-0001-7455-4282

Burhan Baha Bilgilioğlu 0000-0001-6950-4336

Nur Yağmur 0000-0002-5915-6929

Publication Date August 15, 2020
Published in Issue Year 2020 Volume: 7 Issue: 2

Cite

APA Dervisoglu, A., Bilgilioğlu, B. B., & Yağmur, N. (2020). Comparison of Pixel-Based and Object-Based Classification Methods in Determination of Wetland Coastline. International Journal of Environment and Geoinformatics, 7(2), 213-220. https://doi.org/10.30897/ijegeo.713307