Shoreline Extraction in SAR Image Based on Advanced Geometric Active Contour Model

Abstract

Rapid and accurate extraction of shoreline is of great significance for the use and management of sea area. Remote sensing has a strong ability to obtain data and has obvious advantages in shoreline survey. Compared with visible-light remote sensing, synthetic aperture radar (SAR) has the characteristics of all-weather and all-day working. It has been well-applied in shoreline extraction. However, due to the influence of natural conditions there is a problem of weak boundary in extracting shoreline from SAR images. In addition, the complex micro topography near the shoreline makes it difficult for traditional visual interpretation and image edge detection methods based on edge information to obtain a continuous and complete shoreline in SAR images. In order to solve these problems, this paper proposes a method to detect the land–sea boundary based on a geometric active contour model. In this method, a new symbolic pressure function is used to improve the geometric active-contour model, and the global regional smooth information is used as the convergence condition of curve evolution. Then, the influence of different initial contours on the number and time of iterations is studied. The experimental results show that this method has the advantages of fewer iteration times, good stability and high accuracy.

Remote Sensing-Based Automatic Detection of Shoreline Position: A Case Study in Apulia Region

“…For a specific study area, the employed shoreline indicator is often related to the data availability. Common data sources used to monitor coastlines are historical land-based photographs, coastal maps and charts, aerial photographs [17], beach surveys [18], LiDAR [19], remote sensing techniques [20][21][22][23][24][25][26][27], video imaging systems [28][29][30][31], and GPS [32][33][34].…”

Statistical Analysis for Tidal Flat Classification and Topography Using Multitemporal SAR Backscattering Coefficients

“…The heights of the waterlines can be measured from in situ data or marine hydraulic models, and a gridded DEM is created using spatial interpolation techniques [20]. Although waterline extraction is simple and fast, it is sensitive to noise and the edge location is not accurate with only a limited number of remote sensing images [15,21]. Although this method is still commonly used, DEM generation is constrained between the highest and lowest level of acquired images and provides contour lines without the representation of small scale topographic features, such as localized tidal tributaries [7,22].…”

Editorial for the Special Issue “Remote Sensing of the Oceans: Blue Economy and Marine Pollution”

“…Detection of targets such as marine raft aquaculture, moving vessels, and the shoreline [1][2][3]; • Observation of spatio-temporal pattern of oil spills and coastal marine litter [4][5][6]; • Study of natural sea processes, including typhoon-induced storm surges, sub-mesoscale eddies and migration of the along-slope counter-flow [7][8][9]; • Analysis of scattering and spectral properties of the sea surface [10,11].…”

“…Those goals have been pursued using multi-platform and multi-frequency remote sensing tools together with theoretical models, numerical simulations, and in-situ measurements. Most of the study exploited satellite data, including microwave-synthetic aperture radar (SAR) imagery collected in single-, dual-and quad-polarimetric imaging modes, radar altimeters [1][2][3][4][5]7,11], and optical-spin-scanning radiometers and spectroradiometers [7,8]. Other studies used airborne or shore-based sensors, including UAV cameras and high-frequency (HF) coastal radars [6,9].…”

“…In [2], the problem of shoreline extraction is addressed by means of single-polarization (under horizontal transmit) C-band spaceborne Radarsat-2 SAR images. An improved geometric active contour model is proposed, which resulted in a fast, stable and accurate extraction of the land/sea boundary.…”