Coastline Zone Extraction Using Landsat-8 Oli Imagery, Case Study: Bodrum Peninsula, Turkey

Abstract

Coastline extraction is a fundamental work for coastal resource management and coastal environmental protection. Today, by using digital image processing techniques, coastline extraction can be done with remote sensing imagery systems. In this study, Landsat 8 Operational Land Imagery (OLI) data have been the main data source due to free access and sufficient spatial resolution for coast line extraction. This research is focused on determining the coastline length and measuring land area by using Landsat 8 OLI satellite image for Bodrum Peninsula, Turkey. Three commonly used methods have been applied in order to determine sea-land boundary line and its length, and area of the study area. The Automatic Water Extraction Index (AWEI), Iterative Self-Organizing Data Analysis Technique (ISODATA) unsupervised classification technique and on screen digitizing method was chosen for identification of coastal boundaries. Results of coastline length and land areas of Bodrum by using AWEI, ISODATA and on-screen digitizing are compared with each other. This study shows that with using optimal threshold value, AWEI can be used for coast line extraction method with coherently for Landsat 8 OLI satellite imagery. The overall results show that coastline extraction from satellite imagery can be done with sufficient accuracy using spectral water indices instead of time consuming on-screen digitizing.

Detection of Shoreline Changes With Automated Water Extraction Index (AWEI) In Galur District, Kulon Progo Regency

“…Judging by the extraction results, the separation of water bodies from land is good which is also due to the special characteristics of water which absorbs more MIR light than NIR light, in the threshold algorithm water pixels with a value equal to or greater than the predetermined threshold value are classified as bodies. water, while for pixels that have values below the threshold, they are classified as water/land free [16]. Similar to [17] Change detection through imagery is utilized for disaster monitoring, resource supervision, and detecting changes in a studied object.…”

Forecasting future scenarios of coastline changes in Turkiye's Seyhan Basin: a comparative analysis of statistical methods and Kalman Filtering (2033–2043)

“…In addition, AWEI, an index developed in 2014 (Feyisa et al 2014), was used in this study to automatically distinguish between water and land from satellite imagery. This index is derived from satellite imagery, especially Landsat, and is widely used to detect water surfaces (Guo et al 2017;Fisher et al 2016;Isiacik Colak et al 2019;Wicaksono and Wicaksono 2019). AWEI highlights differences between water and land using a combination of pixel values in various spectral bands.…”

Application of remote sensing technique for shoreline change detection in Ninh Binh and Nam Dinh provinces (Vietnam) during the period 1988 to 2018 based on water indices

“…In the next step, the surface reflectance value can be calculated using "dark object subtraction" (DOS) atmospheric correction method [Chavez, 1988[Chavez, , 1996. This method estimates the atmospheric contributions to a surface spectrum by measuring homogeneous surfaces over a range of illumination conditions.…”

“…AWEI nsh is mainly used in areas with an urban background, while AWEIsh is primarily designed to remove shadow pixels [Ji and Gong, 2017]. The AWEI index is also used in a number of studies and proves its effectiveness when compared to other water indices [Acharya et al, 2018a[Acharya et al, , 2018bColak et al, 2018;Ji et al, 2015;Mustafa et al, 2017;Masocha et al, 2018]. Jiang et al [2014] were developed An Automated Method for Extracting Rivers and Lakes (AMERL) by combining NDWI, MNDWI, AWEI sh and AWEI nsh water indices to identify water pixels, especially mixed water pixels in shallow or narrow water bodies [Jiang et al, 2014].…”