Shoreline Extraction and Change Detection using 1:5000 Scale Orthophoto Maps: A Case Study of Latvia-Riga

Year 2015, Volume: 2 Issue: 3, 1 - 6, 31.12.2015

Bülent Bayram , İnese Janpaule Mustafa Oğurlu Salih Bozkurt Hatice Çatal Reis , Dursun Zafer Şeker

https://doi.org/10.30897/ijegeo.303552

Cited By: 6

Abstract

Coastal management requires rapid, up-to-date, and
correct information. Thus, the determination of coastal movements and its
directions has primary importance for coastal managers. For monitoring the
change of shorelines, remote sensing data, very high resolution aerial images
and orthophoto maps are utilized for detections of change on shorelines. It is
possible to monitor coastal changes by extracting the coastline from orthophoto
maps. Along the Baltic Sea and Riga Gulf, Latvian coastline length is 496 km.
It is rich of coastal resources and natural biodiversity.  Around 120 km of coastline are affected by
significant coastal changes caused by climate change, storms, erosion, human
activities and other reasons and they must be monitored. In this study, an
object-oriented approach has been proposed to detect shoreline and detect the
changes by using 1:5000 scaled orthophoto maps of Riga-Latvia (3bands, R, G,
and NIR) in the years of 2007 and 2013. As many of the authors have mentioned,
object-oriented classification method can be more successful than the
pixel-based methods especially for high resolution images to avoid
mix-classification. In the presented study the eCognition object-oriented fuzzy
image processing software has been used. The results were compared to the
results derived from manual digitizing. Extracted and manually digitized
shorelines have been divided in 5 m segments in x axis. The y coordinates of
the new nodes were taken from the original “.dxf” file or computed by
interpolation. Thus, the RMS errors of selected points were calculated

Keywords

Shoreline extraction, object-oriented classification, image processing, change detection, orthophoto map

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