Open AccessSemi-Automatic Extraction of The Threshold Segmentation of Coastline Based on Coastline Type
Author(s) -
Tan Yu,
Shuwen Xu,
Xinyu Zhou,
Pedro Reviriego,
Bingxu Zhang
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/690/1/012019
Subject(s) - shore , segmentation , extraction (chemistry) , remote sensing , satellite , image segmentation , adaptability , computer science , point (geometry) , artificial intelligence , geology , computer vision , mathematics , engineering , oceanography , chemistry , chromatography , aerospace engineering , biology , geometry , ecology
Using remote sensing images to extract the shoreline is an important means of studying coastlines. In this paper, we propose a semi-automatic coastline extraction method based on the coastline type that uses region segmentation and edge detection image processing. Based on selected Landsat 4-5 TM and Landsat 8 OLI_TIRS satellite images of Chongming Island from 1985 to 2017, we find that the point control method, neighborhood marking method, and targeted selection based on different shoreline types significantly improve the calculation efficiency, have good adaptability, and produce highly accurate shoreline extraction.