Automatic Semi-Global Artificial Shoreline Subpixel Localization Algorithm for Landsat Imagery

Shoreline mapping using satellite remote sensing images has the advantages of large-scale surveys and high efficiency. However, low spatial resolution, various geometric morphologies and complex offshore environments prevent accurate positioning of the shoreline. This article proposes a semi-global...

Full description

Saved in:
Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Switzerland), 2019-08, Vol.11 (15), p.1779
Main Authors: Song, Yan, Liu, Fan, Ling, Feng, Yue, Linwei
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Automation
Beaches
Classification
Image processing
Image segmentation
intensity integral error
Laboratories
Landsat
Landsat satellites
Localization
Localization method
Mapping
Mathematical morphology
Methods
Pixels
Remote sensing
Satellite imagery
semi-global subpixel localization
shoreline mapping
Shoreline protection
Shorelines
Soil erosion
Spatial discrimination
Spatial resolution
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Shoreline mapping using satellite remote sensing images has the advantages of large-scale surveys and high efficiency. However, low spatial resolution, various geometric morphologies and complex offshore environments prevent accurate positioning of the shoreline. This article proposes a semi-global subpixel shoreline localization method that considers utilizing morphological control points to divide the initial artificial shoreline into segments of relatively simple morphology and analyzing the local intensity homogeneity to calculate the intensity integral error. Combined with the segmentation-merge-fitting method, the algorithm determines the subpixel location accurately. In experiments, we select five artificial shorelines with various geometric morphologies from Landsat 8 Operational Land Imager (OLI) data. The five subpixel artificial shoreline RMSE results lie in the range of 3.02 m to 4.77 m, with line matching results varying from 2.51 m to 3.72 m. Thus, it can be concluded that the proposed subpixel localization algorithm is effective and applicable to artificial shoreline in various geometric morphologies and is robust to complex offshore environments, to some extent.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs11151779