An Approach Based on Landsat Images for Shoreline Monitoring to Support Integrated Coastal Management—A Case Study, Ezbet Elborg, Nile Delta, Egypt

Abstract

Monitoring the dynamic behavior of shorelines is an essential factor for integrated coastal management (ICM). In this study, satellite-derived shorelines and corresponding eroded and accreted areas of coastal zones have been calculated and assessed for 15 km along the coasts of Ezbet Elborg, Nile Delta, Egypt. A developed approach is designed based on Landsat satellite images combined with GIS to estimate an accurate shoreline changes and study the effect of seawalls on it. Landsat images for the period from 1985 to 2018 are rectified and classified using Supported Vector Machines (SVMs) and then processed using ArcGIS to estimate the effectiveness of the seawall that was constructed in year 2000. Accuracy assessment results show that the SVMs improve images accuracy up to 92.62% and the detected shoreline by the proposed method is highly correlated (0.87) with RTK-GPS measurements. In addition, the shoreline change analysis presents that a dramatic erosion of 2.1 km2 east of Ezbet Elborg seawall has occurred. Also, the total accretion areas are equal to 4.40 km2 and 10.50 km2 in between 1985-and-2000 and 2000-and-2018, respectively, along the southeast side of the study area.

Assessing the Impacts of Rising Sea Level on Coastal Morpho-Dynamics with Automated High-Frequency Shoreline Mapping Using Multi-Sensor Optical Satellites

“…Among supervised classification methods, support vector machine is a well-known method for land-sea classification. Elnabwy, et al [45] classified Landsat images using SVM to extract instantaneous shorelines along the coasts of Nile Delta. Studies have also employed neural network classification to discriminate sand and water features [34].…”

Change Detection in Multispectral Remote Sensing Images with Leader Intelligence PSO and NSCT Feature Fusion

“…As a result, the shoreline is exposed and a clear change in the boundary of the water is seen in the difference image. Four bands at spatial resolution 30 m, in the wavelength range (0.45-0.52 µm), (0.52-0.60 µm), (0.63-0.69 µm) and (0.76-0.90 µm) are selected for this study as they are suitable for the land cover and shoreline studies [4,25].…”

“…Change detection (CD) is the process of identifying changes occurred at a scene between two time points, using multi-temporal images. It is an active research area due to its numerous applications in real-life [1][2][3][4]. In this paper, the focus is on remote sensing change detection [2,5], owing to the following aspects.…”

“…Firstly, monitoring large area is possible with satellite imageries, which otherwise, is very time consuming and expensive or even not possible due to remote areas [3,6]. Secondly, quick and automated systems to monitor changes are extremely necessary for deploying timely actions in various realistic problems such as disaster management/assessment, monitoring land use/land cover changes or forest cover changes due to fire/infestations, urbanization and environmental monitoring, and oceanography [4,[6][7][8][9]. Though we find a profusion of CD techniques in the literature, most of these methods are application specific and highly depend on the spectral, spatial and sensor characteristics of the imageries used and cannot be considered as optimal [1,6,7,[10][11][12][13][14][15][16][17][18][19][20].…”

Assessing the Immediate Impact of Surrounding Land Uses on the Extents of Freshwater Body over Time in Madagascar - A Demonstrative Case Study of Itasy Lake -

“…Therefore, monitoring the extent of a lake boundary over time could provide useful information for assessing sedimentation. Although, field surveys have often been applied to monitor periodic changes in the positions of the lake's boundary (intersection between water surface and land) with high accuracy, these approaches are often labor-intensive, timeconsuming and expensive (Liu et al 2007;Natesan et al 2013;Elnabwy et al 2020). Recent studies show that sedimentation can be accessed by monitoring historical water boundary changes using Remote Sensing and Geographical Information Systems (GIS) techniques (Duru 2017).…”