A Comparison of Landsat-8 OLI, Sentinel-2 MSI and PlanetScope Satellite Imagery for Assessing Coastline Change in El-Alamein, Egypt

The objective of this study was to provide an assessment of coastline extraction and change analysis using different sensors from three satellites over time. Imagery from Landsat-8 OLI, Sentinel-2A MSI, and PlanetScope-3B were used to detect geomorphological changes along the El-Alamein coastline on the Mediterranean Sea between August 2016 and August 2021. The normalized difference water index (NDWI) was applied to automate, detect and map water bodies based on thresholding techniques and coastline extraction. The extracted coastlines were analyzed using geographic information systems (GIS)-based digital shoreline analysis system (DSAS.v5) model, a GIS software tool for the estimation of shoreline change rates calculated through two statistical techniques: net shoreline movement (NSM) and end point rate (EPR). The results indicate that measuring coastline morphological change using satellite-based imagery depends very much on the resolution of the imagery. It is necessary to tailor the selection of imagery to the accuracy of the measurement needed. Higher resolution imagery such at PlanetScope (3 m) produces higher resolution measurements. However, medium resolution imagery from Landsat may be sufficiently good for objectives requiring less spatial resolution.

Exploring the Spatial–Temporal Analysis of Coastline Changes Using Place Name Information on Hainan Island, China

A coastline is the boundary zone between land and sea, an active zone of human social production activities and an area where the ecology is fragile and easy to change. The traditional method to analyze temporal and spatial changes in the coastline is to extract the coastline through remote sensing, LiDAR, and field sampling and analyze the temporal and spatial changes with statistical data. The coastline extracted by these methods has high spatial and temporal resolution, but it requires remote sensing images and data obtained by other sensors, so it is impossible to extract coastlines from before the emergence of remote sensing technology. This paper improves the coastline generation algorithm. Firstly, a triangulated irregular network is used to generate the preliminary rough coastline, and then, each line segment is optimized with Python language according to the influence range of the place names to further approach the real coastline. The accuracy of the coastline extracted by this method can reach 80% within 500 m, which is of great significance in the mapping and analysis of small- and medium-scale coastlines. This paper analyzes the changes in the coastline of Hainan Island before the founding of China (pre-founding) and in modern times and analyzes the impact of coastal development on coastline change. Through the analysis, it is found that, from before the founding of the People’s Republic of China to the present, the natural coastline of Hainan Island has become shorter, the artificial coastline has become longer, and the coastline generally presents a trend of advancing toward the ocean. This method realizes coastline construction under the condition of missing remote sensing images and puts forward a new way to study historical coastline changes.

COASTLINE CHANGE ANALYSIS ON BALI ISLAND USING SENTINEL-1 SATELLITE IMAGERY

Bali is well-known as a popular tourism location for both local and foreign tourists. There are nine areas designated for tourism, eight of which are coastal. However, due to coastal erosion, the coastline of Bali is changing every year. The purpose of this study is to determine the changes that took place between 2015 and 2020 using Sentinel-1 satellite imagery. The study was conducted along the coastline of Bali Island at coordinates 08° 53' 35.5648" S, 114° 24' 41.8359" E and 08° 00' 46.7865" S, 115° 44' 17.5928" E. The coastlines were identified using the Otsu image thresholding method and linear tidal correction was performed. The coastline change analysis was made using the transect method. Ground truths were conducted in representative areas where major changes had occurred, either as a result of abrasion or accretion. According to the Sentinel-1 analysis, the coastline changes in Bali during the period 2015 – 2020 were mainly caused by abrasion, apart from at Buleleng, which were generally caused by accretion. Abrasion in Bali is dominantly affected by strong currents and high waves meanwhile accretion which having weak currents and low waves was more affected by human factor such as the construction in this study area.

ANALYSIS OF COASTLINE CHANGES ON THE POTENTIAL OF MANGROVE FORESTS ON BENGKALIS ISLAND, RIAU PROVINCE

This study was conducted from January to February 2021 in coastal areas of Bengkalis Regency that is in Riau Province. This study aims to know the coastline changes to the potency of mangrove forests in that area. Field data was collected by survey methods such as direct observation and questioners, and it used different times of satellite imageries to find out the coastline changes over time. The results showed that the coastline of this regency had changed as much as 1036 Ha in average from the year of 1988 to 2020. It was due to coastal abrasion, wave actions, and reduction of mangrove forests; the coastline change reached 12.02 meters per year as the highest. The mangrove forest in the region of this regency plays important roles to the local life, the local economy, and the coastal waters; it was for fishermen, charcoal production, coastal tourism, and transportation as well.

Sea level dynamics and coastal erosion in the Baltic Sea region

There are a large number of geophysical processes affecting sea level dynamics and coastal erosion in the Baltic Sea region. These processes operate on a large range of spatial and temporal scales and are observed in many other coastal regions worldwide. This, along with the outstanding number of long data records, makes the Baltic Sea a unique laboratory for advancing our knowledge on interactions between processes steering sea level and erosion in a climate change context. Processes contributing to sea level dynamics and coastal erosion in the Baltic Sea include the still ongoing viscoelastic response of the Earth to the last deglaciation, contributions from global and North Atlantic mean sea level changes, or contributions from wind waves affecting erosion and sediment transport along the subsiding southern Baltic Sea coast. Other examples are storm surges, seiches, or meteotsunamis which primarily contribute to sea level extremes. Such processes have undergone considerable variation and change in the past. For example, over approximately the past 50 years, the Baltic absolute (geocentric) mean sea level has risen at a rate slightly larger than the global average. In the northern parts of the Baltic Sea, due to vertical land movements, relative mean sea level has decreased. Sea level extremes are strongly linked to variability and changes in large-scale atmospheric circulation. The patterns and mechanisms contributing to erosion and accretion strongly depend on hydrodynamic conditions and their variability. For large parts of the sedimentary shores of the Baltic Sea, the wave climate and the angle at which the waves approach the nearshore region are the dominant factors, and coastline changes are highly sensitive to even small variations in these driving forces. Consequently, processes contributing to Baltic sea level dynamics and coastline change are expected to vary and to change in the future, leaving their imprint on future Baltic sea level and coastline change and variability. Because of the large number of contributing processes, their relevance for understanding global figures, and the outstanding data availability, global sea level research and research on coastline changes may greatly benefit from research undertaken in the Baltic Sea.

Land Cover and Coastline Change Assessment of Nijhum Dwip, Bangladesh, using Geospatial Analysis

Nijhum Dwip is a southern island of Bangladesh isolated from the mainland, in the convergence of the Meghna River and the Bay of Bengal. This island has studied through overlay analysis and supervised classification by geospatial and remote sensing technique, over 38 years (1980-2018) using multitemporal Landsat MSS, TM, OLI, and TIRS satellite images with identification of historical changes. This landform is facing frequent shifting of its coastline and leading to sequential changes on the land surface. Analysis revealed substantial growth of settlement and agricultural land whereas significant lessening on vegetation cover and open space. In 1990 agricultural land was 4.47 km2 (13.29%) and improved to 9.16 km2 (19.17%) in 2018. Similarly, settlement also increased from 1.92 km2 (4.79%) in 1999 to 5.72 km2 (11.97%) in 2018. Conversely, vegetation was primarily 8.02 km2 (27.71%), 18.70 km2 (55.61%), 20.97 km2 (52.29%), 18.47 km2 (36.28%) and 15.28 km2 (31.98%) in 1980,1990,1999, 2010 and 2018, indicating declination. As well, water bodies and open space also fluctuated through the period because of geomorphological processes and human intervention. Besides, the least and highest unstable char land was 1.15 km2 (3.42%) and 1.68 km2 (5.80%) in 1990 and 1980.

Mapping Mangrove Opportunities with Open Access Data: A Case Study for Bangladesh

Mangroves protect coastal areas against hazards like storms or cyclones by attenuating waves and currents, and by trapping floating debris during extreme events. Bangladesh is a very vulnerable country to floods and cyclones, and part of its coastal system is thus being upgraded to a higher safety standard. These upgrades include embankment reinforcement and mangrove afforestation schemes seawards of the embankments. To further strengthen the implementation of combined green–grey infrastructure in future programs, identifying potential mangrove development sites near the polder systems is a necessary first step. We thus developed a tool to systematically identify mangrove sites throughout the coastal area based on open access data. This method identifies potential sites for mangrove development based on their distance from existing mangrove patches and suggests the required technique to implement the vegetation depending on the rate of coastline change. Our method showed that approximately 600 km of the coastal stretches placed seawards of embankments are within 10 km of existing mangroves, and could thus be potential sites for mangrove establishment. Out of those 600 km, we identified 140 km of coastline where the landwards polders are particularly vulnerable to flooding. The sites with highest restoration potential and priority are located in Galachipa, Hatiya, Bhola, Manpura, Khangona, and Boro Moheshkhali. More detailed data collection and local assessments are recommended prior to executing mangrove afforestation schemes. Nevertheless, this method could serve as a useful systematic tool for feasibility studies that identify mangrove opportunities in data-scarce areas and help to prioritize data collection at the sites of highest interest.

Evaluating and Visualizing Drivers of Coastline Change: A Lake Ontario Case Study

Environmental and climatic changes are disproportionately felt in coastal communities, where drivers of coastline change are complicated with continued development. This study analyzed the coastline change of Lake Ontario in the Town of Lincoln, Ontario, Canada, using a mixed-methods two-phased approach that is novel to the study area. The first phase of the methodology included a coastline change analysis using historical aerial photographs in a geographic information system to identify the most vulnerable sections of the coastline. To better understand the calculated changes, the second phase explored the roles of select climatic and non-climatic drivers of coastline change, such as historic storms and land use changes. The results indicated that four main areas of Lincoln’s coast were more vulnerable, with rates of erosion between −0.32 and −0.66 m/yr between 1934 and 2018. Sections of coastline that had less erosion included those that were more heavily vegetated, attempted a cooperative protection approach, or utilized revetment stones in areas without steep banks. This methodology can help municipalities understand coastline change in a more holistic way to increase their adaptive capacity and allows for the creation of useful visualizations that better communicate to residents and town staff the level of vulnerability of their coasts.