Paper Info
Title
Automated Coastline Detection From Landsat 8 Oli/Tirs Images With The Presence Of Inland Water Bodies In Andaman
Abstract
Coastline detection, and monitoring have different research challenges. Global warming, deforestation, and sea level rising have several adverse effects on coastlines such as, erosion, coastline recession, loss of biodiversity, etc. In the past, various techniques have been proposed to detect, and monitor coastlines. While detecting coastlines, most of the techniques do not consider removing inland water bodies. The objective of this work is to remove inland water bodies, in the process of detection of coastlines. For accomplishing this task, we propose to use difference of Coal Mine Index (CMI) and Normalized Difference Water Index (NDWI) to separate water bodies from other regions. Subsequently, inland water bodies are identified from this set by computing and analyzing their contours, and removed to provide coastlines. Overall, this work presents a novel automated method of coastline detection with the presence of inland water bodies having precision, and recall of 80%, and 82.35%, respectively.
Year
DOI
Venue
2020
10.1109/IGARSS39084.2020.9324366
IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM
Keywords
DocType
Citations 
Coastline, Contour Detection, Coal Mine Index, Normalized Difference Water Index, K-Means Clustering, Inland Water Body, Landsat 8
Conference
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Rajdeep Mondal100.34
Jit Mukherjee200.68
Jayanta Mukhopadhyay300.68