Shoreline Extraction Based on an Active Connection Matrix (ACM) Image Enhancement Strategy

Abstract

Coastal environments are facing constant changes over time due to their dynamic nature and geological, geomorphological, hydrodynamic, biological, climatic and anthropogenic factors. For these reasons, the monitoring of these areas is crucial for the safeguarding of the cultural heritage and the populations living there. The focus of this paper is shoreline extraction by means of an experimental algorithm, called J-Net Dynamic (Semeion Research Center of Sciences of Communication, Rome, Italy). It was tested on two types of image: a very high resolution (VHR) multispectral image (WorldView-2) and a high resolution (HR) radar synthetic aperture radar (SAR) image (Sentinel-1). The extracted shorelines were compared with those manually digitized for both images independently. The results obtained with the J-Net Dynamic algorithm were also compared with common algorithms, widely used in the literature, including the WorldView water index and the Canny edge detector. The results show that the experimental algorithm is more effective than the others, as it improves shoreline extraction accuracy both in the optical and SAR images.

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

“…The positioning accuracy was determined using the snakes algorithm. In [27], J-Net Dynamic which is an experimental algorithm was applied on a high-resolution Sentinel-1 SAR image for the first time.…”

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].…”

Coastline Difference Measurement (CDM) Method

“…Irregular and variable geometrical aspects of coastlines could cause uncertainties while comparing spatial differences in area of interests. Comparison purposes could be considered as change detection to monitoring coastal zones (Nassar et al, 2019;Yulianto et al, 2019) or obtaining accuracies while studying coastline extraction methods (Wicaksono et al, 2019;Zollini et al, 2020). While measuring differentiation from a point in the reference coastline, simple point-to-point measuring results could vary according to measurement direction.…”