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Kaplan G., Avdan U.

4th International Workshop on Geoinformation Science / 4th ISPRS International Workshop on Multi-Dimensional and Multi-Scale Spatial Data Modeling (GeoAdvances), Safranbolu, Turkey, 14 - 15 October 2017, vol.4-4, pp.271-277 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 4-4
  • Doi Number: 10.5194/isprs-annals-iv-4-w4-271-2017
  • City: Safranbolu
  • Country: Turkey
  • Page Numbers: pp.271-277
  • Keywords: Wetlands, Remote Sensing, Sentinel-2, Classification, NDVI, NDWI, DIFFERENCE WATER INDEX, VEGETATION, LANDSAT, NDVI, NDWI
  • Anadolu University Affiliated: Yes


Mapping and monitoring of wetlands as one of the world's most valuable natural resource has gained importance with the developed of the remote sensing techniques. This paper presents the capabilities of Sentinel-2 successfully launched in June 2015 for mapping and monitoring wetlands. For this purpose, three different approaches were used, pixel-based, object-based and index-based classification. Additional, for more successful extraction of wetlands, a combination of object-based and index-based method was proposed. It was proposed the use of object-based classification for extraction of the wetlands boundaries and the use of Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) for classifying the contents within the wetlands boundaries. As a study area in this paper Sakarbasi spring in Eskisehir, Turkey was chosen. The results showed successful mapping and monitoring of wetlands with kappa coefficient of 0.95.