Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 1103-1105, 2016
https://doi.org/10.5194/isprs-archives-XLI-B8-1103-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
24 Jun 2016
MAPPING OF THE SEAGRASS COVER ALONG THE MEDITERRANEAN COAST OF TURKEY USING LANDSAT 8 OLI IMAGES
T. Bakirman1, M. U. Gumusay1, and I. Tuney2 1YTU, Civil Engineering Faculty, 34220 Esenler Istanbul, Turkey
2Ege Universiy, Faculty of Science, 35100 Bornova Izmir, Turkey
Keywords: Seagrass, Cover, Landsat 8, Image Classification, Remote Sensing Abstract. Benthic habitat is defined as ecological environment where marine animals, plants and other organisms live in. Benthic habitat mapping is defined as plotting the distribution and extent of habitats to create a map with complete coverage of the seabed showing distinct boundaries separating adjacent habitats or the use of spatially continuous environmental data sets to represent and predict biological patterns on the seafloor. Seagrass is an essential endemic marine species that prevents coast erosion and regulates carbon dioxide absorption in both undersea and atmosphere. Fishing, mining, pollution and other human activities cause serious damage to seabed ecosystems and reduce benthic biodiversity. According to the latest studies, only 5–10% of the seafloor is mapped, therefore it is not possible to manage resources effectively, protect ecologically important areas. In this study, it is aimed to map seagrass cover using Landsat 8 OLI images in the northern part of Mediterranean coast of Turkey. After pre-processing (e.g. radiometric, atmospheric, water depth correction) of Landsat images, coverage maps are produced with supervised classification using in-situ data which are underwater photos and videos. Result maps and accuracy assessment are presented and discussed.
Conference paper (PDF, 1291 KB)


Citation: Bakirman, T., Gumusay, M. U., and Tuney, I.: MAPPING OF THE SEAGRASS COVER ALONG THE MEDITERRANEAN COAST OF TURKEY USING LANDSAT 8 OLI IMAGES, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 1103-1105, https://doi.org/10.5194/isprs-archives-XLI-B8-1103-2016, 2016.

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