Year 2020, Volume 7 , Issue 2, Pages 213 - 220 2020-08-15

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

Adalet DERVİSOGLU [1] , Burhan Baha BİLGİLİOĞLU [2] , Nur YAĞMUR [3]


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.
Coastline, Classification, Wetland, Remote sensing, Pixel-based, Object-based, Duden Lake
  • 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.
Primary Language en
Subjects Engineering
Journal Section Research Articles
Authors

Orcid: 0000-0001-7455-4282
Author: Adalet DERVİSOGLU (Primary Author)
Institution: ISTANBUL TECHNICAL UNIVERSITY
Country: Turkey


Orcid: 0000-0001-6950-4336
Author: Burhan Baha BİLGİLİOĞLU
Institution: GÜMÜŞHANE ÜNİVERSİTESİ
Country: Turkey


Orcid: 0000-0002-5915-6929
Author: Nur YAĞMUR
Institution: ISTANBUL TECHNICAL UNIVERSITY
Country: Turkey


Dates

Publication Date : August 15, 2020

Bibtex @research article { ijegeo713307, journal = {International Journal of Environment and Geoinformatics}, issn = {}, eissn = {2148-9173}, address = {}, publisher = {Cem GAZİOĞLU}, year = {2020}, volume = {7}, pages = {213 - 220}, doi = {10.30897/ijegeo.713307}, title = {Comparison of Pixel-Based and Object-Based Classification Methods in Determination of Wetland Coastline}, key = {cite}, author = {Dervi̇soglu, Adalet and Bi̇lgi̇li̇oğlu, Burhan Baha and Yağmur, Nur} }
APA Dervi̇soglu, A , Bi̇lgi̇li̇oğlu, 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 . DOI: 10.30897/ijegeo.713307
MLA Dervi̇soglu, A , Bi̇lgi̇li̇oğlu, B , Yağmur, N . "Comparison of Pixel-Based and Object-Based Classification Methods in Determination of Wetland Coastline" . International Journal of Environment and Geoinformatics 7 (2020 ): 213-220 <https://dergipark.org.tr/en/pub/ijegeo/issue/54146/713307>
Chicago Dervi̇soglu, A , Bi̇lgi̇li̇oğlu, B , Yağmur, N . "Comparison of Pixel-Based and Object-Based Classification Methods in Determination of Wetland Coastline". International Journal of Environment and Geoinformatics 7 (2020 ): 213-220
RIS TY - JOUR T1 - Comparison of Pixel-Based and Object-Based Classification Methods in Determination of Wetland Coastline AU - Adalet Dervi̇soglu , Burhan Baha Bi̇lgi̇li̇oğlu , Nur Yağmur Y1 - 2020 PY - 2020 N1 - doi: 10.30897/ijegeo.713307 DO - 10.30897/ijegeo.713307 T2 - International Journal of Environment and Geoinformatics JF - Journal JO - JOR SP - 213 EP - 220 VL - 7 IS - 2 SN - -2148-9173 M3 - doi: 10.30897/ijegeo.713307 UR - https://doi.org/10.30897/ijegeo.713307 Y2 - 2020 ER -
EndNote %0 International Journal of Environment and Geoinformatics Comparison of Pixel-Based and Object-Based Classification Methods in Determination of Wetland Coastline %A Adalet Dervi̇soglu , Burhan Baha Bi̇lgi̇li̇oğlu , Nur Yağmur %T Comparison of Pixel-Based and Object-Based Classification Methods in Determination of Wetland Coastline %D 2020 %J International Journal of Environment and Geoinformatics %P -2148-9173 %V 7 %N 2 %R doi: 10.30897/ijegeo.713307 %U 10.30897/ijegeo.713307
ISNAD Dervi̇soglu, Adalet , Bi̇lgi̇li̇oğlu, Burhan Baha , Yağmur, Nur . "Comparison of Pixel-Based and Object-Based Classification Methods in Determination of Wetland Coastline". International Journal of Environment and Geoinformatics 7 / 2 (August 2020): 213-220 . https://doi.org/10.30897/ijegeo.713307
AMA Dervi̇soglu A , Bi̇lgi̇li̇oğlu B , Yağmur N . Comparison of Pixel-Based and Object-Based Classification Methods in Determination of Wetland Coastline. International Journal of Environment and Geoinformatics. 2020; 7(2): 213-220.
Vancouver Dervi̇soglu A , Bi̇lgi̇li̇oğlu B , Yağmur N . Comparison of Pixel-Based and Object-Based Classification Methods in Determination of Wetland Coastline. International Journal of Environment and Geoinformatics. 2020; 7(2): 213-220.