Monitoring Of Shoreline Changes Research Articles

Satellite, drone and video camera multi-platform monitoring of coastal erosion at an engineered pocket beach: A showcase for coastal management at Elmina Bay, Ghana (West Africa)

Regular monitoring of coastal areas is a prerequisite to evade any imminent erosive disaster. However, data-driven decisions become more uncertain when a monitoring platform is unable to capture events of a certain frequency. Erosion along Ghana’s coastline is endemic as in most of the Gulf of Guinea countries in West Africa. The current challenge is how to document and understand the dimensions of erosion despite limited human and logistical capacity. In the present study, shoreline change was assessed by an intensive multi-platform data collection strategy deployed for a year at Elmina Bay, Ghana through the use of drones, a shore-based camera, Sentinel satellite images and a dumpy level. The potential causes and areas of erosion at Elmina were clearly identified at a very fine scale by our sediment budget calculations. While a section of the beach in front of the Elmina Castle was adequately protected by the presence of jetties , downdrift of the larger unprotected portion of the beach was out of balance with high erosion rates. Furthermore, the results revealed that frequent, local video cameras and drones are more effective for operational monitoring of shoreline changes at all time scales. Satellite imagery is also a potential alternative tool, but its low temporal resolution, compared with video cameras, makes it unsuitable for detecting daily or event-based beach changes, and is of low accuracy for practitioners and management decisions.

Coastal Wetland Shoreline Change Monitoring: A Comparison of Shorelines from High-Resolution WorldView Satellite Imagery, Aerial Imagery, and Field Surveys

Shoreline change analysis is an important environmental monitoring tool for evaluating coastal exposure to erosion hazards, particularly for vulnerable habitats such as coastal wetlands where habitat loss is problematic world-wide. The increasing availability of high-resolution satellite imagery and emerging developments in analysis techniques support the implementation of these data into shoreline monitoring. Geospatial shoreline data created from a semi-automated methodology using WorldView (WV) satellite data between 2013 and 2020 were compared to contemporaneous field-surveyed Global Position System (GPS) data. WV-derived shorelines were found to have a mean difference of 2 ± 0.08 m of GPS data, but accuracy decreased at high-wave energy shorelines that were unvegetated, bordered by sandy beach or semi-submergent sand bars. Shoreline change rates calculated from WV imagery were comparable to those calculated from GPS surveys and geospatial data derived from aerial remote sensing but tended to overestimate shoreline erosion at highly erosive locations (greater than 2 m yr−1). High-resolution satellite imagery can increase the spatial scale-range of shoreline change monitoring, provide rapid response to estimate impacts of coastal erosion, and reduce cost of labor-intensive practices.

Shoreline change monitoring for coastal zone management using multi-temporal Landsat data in Mahi River estuary, Gujarat State

Coastline changes are caused by sea-level rise, erosion and anthropogenic activities, and have important consequences on coastal ecosystems and communities. In this study, shore line changes during the last 40 years near the Mahi estuarine belt in the Gulf of Khambhat region have been monitored using multi-temporal Landsat data from 1978 to 2018. Multi-date Landsat digital data with 10-year interval from 1978 to 2018 was downloaded from the website https://earthexplorer.usgs.gov/ . The Landsat data covering the study area with 15-km buffer was extracted and analyzed for monitoring the changes in the shoreline. The Normalized Difference Water Index (NDWI) images were also generated for delineation of the shoreline. The data was analyzed using the Digital Shoreline Analysis System in ArcGIS software, which provides a set of tools permitting transects-based calculation of shoreline displacement. A total number of 10 transects from the centre of the village up to the coast line were marked on the multi-date Landsat digital data. The changes in the shoreline from the centre of the village were calculated using the End Point Rate (EPR) and temporal linear regression model to predict future shoreline position. The decadal shoreline change indicated that shoreline has continuously increased from 113.9 to 831.4 m during the 40-year period from 1978 to 2018, respectively. This indicates that total migration of shoreline towards the land area of the study village during the last 40 years (1978 to 2018) was 1590.5 m with an alarming annual rate of change of 39.76 m year−1, which is very remarkably high and alarming which may lead to any future disaster for the study village. The coastline was not significantly changing until 1988; however, change in coastline is exponentially faster from 1989 to 2018. The linear regression method was adopted for predicting the shoreline change rates over the entire period of the study from 1978 to 2018 and from 2018 to 2028 and 2038. The results of shoreline change prediction for future 10 years (2028) and 20 years (2038) indicate the average predicted transect length of 1908 m and 1543 m, respectively. With the projected estimates of shoreline change during next 20 years at the rate of almost 120 m/year, it appears that the Chokari village may get submerged in the sea water. The analysis of change in the land surface area of the Chokari village indicated that it has decreased from 12.45 to 9.63 km2, which indicates that area reduced by 2.8 km2 may be due to the erosion along the river-bed which is the result of change in the shoreline during the last 40 years. Based on these results of shoreline change analysis, it is recommended that the Government of Gujarat needs to take immediate steps to protect the Chokari village from submergence by adopting Integrated Coastal Zone management strategies.

THE ROLE OF GEOTEXTILE TUBE AS LOW-CRESTED BREAKWATERS IN RESTORING SEVERE BEACH EROSION PROBLEM AT PEBUAHAN BEACH IN BALI ISLAND

Pebuahan Beach in Jembrana Regency, Bali has experienced severe beach erosion since the construction of the Nusantara Pengambengan fishing port, 10 km east of Pebuahan. Efforts to countermeasure the coastal problem has been carried out by many local residents, but failed due to strong longshore drift. Through a collaboration between the Research Center for Water Resources, the Bali Penida River Basin, and PT. Geotechnical Systemindo, the implementation of low-crested breakwaters (LCB) or PEGAR, made of Woven Geotextile Tubes was initiated. Four woven geotextile tubes C12.9 m with length varied from 20 m to 25 m were installed to form LCB with the length of 60 m, at distance to the coast of 50 m. The monitoring of shoreline changes was conducted over the 3 months after its installation, which shows the formation of a new shoreline with the amount of deposited sand of 185.8 m3. The breaking wave on LCB crest results in successfully controlling the longshore current, hence the longshore drift settles behind the LCB to form a new coastline. It is expected this field study can be treated as an additional input to improve LCB Guideline and to expand LCB effectiveness scope not only apply to shallow wave conditions and beaches such as on North coast of Java, but also can be applied more universally to a deeper coastal waters with high wave conditions.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/AFzvkvYY2Do

Investigating the performance of sentinel-2A and Landsat 8 imagery in mapping shoreline changes

Regular detection and timely monitoring of shoreline evolution are essentially needed in order to identify areas that require further investigation and protection. Possibilities for regular monitoring of shoreline changes are better facilitated now with high-frequency revisit times of Landsat-Sentinel-2 virtual constellation. Accordingly, this study aimed at investigating the performance of Landsat 8 and Sentinel-2A satellite imagery in mapping shoreline changes. The specific objectives were to 1) create reference data of shoreline erosion, accretion and seafilling using very high spatial resolution data, 2) compare the results of shoreline changes by using Landsat 8 and Sentinel-2A imagery respectively, and 3) complete the inventory of shoreline changes between 1962 and 2016. A Quickbird panchromatic imagery (0.6 m) of 2010 was employed in combination with aerial photography (0.5 m) from 1962 for the generation of reference data using a traditional photo-interpretation method. Then, geographic object-based image analysis (GEOBIA) was employed to map changes in the shoreline between 1962 (i.e., reference shoreline) and 2016 using Sentinel-2A (10 m) and Landsat 8 panchromatic band (15 m) imagery, consecutively. The use of Sentinel-2A image provided slightly better accuracy results when compared with those from the Landsat 8 image. Accordingly, an inventory of Lebanese shoreline evolution between 1962 and 2016 was completed using the Sentinel-2A classification results. The combined use of Landsat-Sentinel-2 imagery is expected to generate reliable data records for continuous monitoring of shoreline changes.

Impact of Land Subsidence and Sea Level Rise Influence Shoreline Change in The Coastal Area of Demak

Climate change has a negative impact on the environment, one of which is the phenomenon of sea level rise. Sea level rise has a devastating effect on marine coastal areas such as shoreline abrasion. Sea level rise has caused a reduction in land, one area on the north coast of Java affected is located in Demak. Demak is a coastal area that has the potential for a shoreline abrasion because of sea level rise and a decrease in the land surface. Monitoring of shoreline changes needs to be monitored in order to find out the magnitude of the shoreline changes and the impact caused by reduced a mainland. One method that can be used to monitor shoreline changes is to use remote sensing technology. Satellite imagery can produce changes in shoreline abrasion without coming to the objects directly. This study aims to assess sea level rise and land subsidence resulting in changes in the shoreline in Demak. The data used are Jason-1 and Jason altimetry satellite data 2, Landsat 7 ETM + satellite imagery in 2011 and Landsat 8 in 2016. Altimetry satellite data is processed to obtain sea level rise on the coast of the Java Sea. Sea Level Anomaly (SLA) data processing uses Inverse Distance Weight (IDW) interpolation. The rise in sea level is determined by the analysis of linear trends from the processing of altimetry satellite data. The separation between water and land boundaries from Landsat satellite imagery uses the band ratio method on Green bands and NIR bands. shoreline changes are calculated using DSAS (Digital Shoreline Analysis System). The results of data processing obtained an average sea level rise in the Java Sea in 2011 to 2016 of + 6.80 mm/year. The highest increase was in Jakarta waters of +11.043 mm / year and the lowest was in Surabaya waters with an increase of +3.85 mm/year. The increase in Semarang waters was + 5.52 mm/year which was used as validation with the tidal data of Semarang. The average change in coastline in the Demak region is -119.08 m. Demak experienced a land subsidence of +2,078 to -8,376 cm/years. The biggest abrasion occurred in Sayung Subdistrict of -691 m. The largest accretion occurred in the District of Wedung + 512.48 m. Based on the results of the increase in water level in the coastal areas of the island of Java and land subsidence that occurred in Demak caused a fairly wide shoreline abrasion.

Historical Monitoring of Shoreline Changes in the Cua Dai Estuary, Central Vietnam Using Multi-Temporal Remote Sensing Data

Cua Dai is one of the major estuarine areas in Central Vietnam that plays a significant role in local maritime transport, fisheries, and tourism activities. This paper presents a study that monitored the shoreline dynamics of the Cua Dai estuary over a period of 50 years (1964–2014) by using field survey data, geographic information systems techniques, and multi-temporal satellite remote sensing images (ALOS-AVNIR2 and Landsat imageries). The assessment of shoreline changes was divided into three phases: 1964–1980, 1981–2000, and 2001–2014. The results revealed that over the last 50 years, shoreline changes dramatically occurred between 1964 and 1980. The general trends of erosion and accretion at the Cua Dai estuary show that the river mouth moved towards the south due to the erosion of shorelines in the north and the river bank in the south of the Cua Dai estuary. The study outcomes can provide essential information for planning, zoning, and sustainable development activities of the coastal zones in the context of climate change.

Automatic super-resolution shoreline change monitoring using Landsat archival data: a case study at Narrabeen–Collaroy Beach, Australia

Long-term monitoring of shoreline changes is of significant importance for coastal erosion prediction and coastal planning. This paper presents the use of the Landsat archival dataset over 29 years to monitor shoreline changes at Narrabeen–Collaroy Beach, Australia. For each scene of Landsat data, a vector-based shoreline at subpixel level was automatically extracted by employing the super-resolution border segmentation method. Monthly cross-shore beach profile surveys at five locations along the beach are used as ground truth data to assess the results. The experimental results show that after the correction of tidal effects the RMSEs of the time-series shorelines at the five locations are all less than 10 m; RMSEs of annual mean shorelines are within 5.7 m. These results were achieved within the context that the Narrabeen–Collaroy Beach has been observed to vary in width by up to 80 m during this same period. In addition, the observed variabilities in shoreline change at different locations along the 3.6-km long embayment are also clearly observed from Landsat-derived results. The results indicate the feasibility of Landsat data for long-term shoreline change monitoring.

Shoreline Change Monitoring using High Resolution Digital Photogrammetric Technique

ABSTRACT Ahn, Y.; Shin, B., and Kim, K.-H., 2017. Shoreline change monitoring using high resolution digital photogrammetric technique. In: Lee, J.L.; Griffiths, T.; Lotan, A.; Suh, K.-S., and Lee, J. (eds.), The 2nd International Water Safety Symposium. Journal of Coastal Research, Special Issue No. 79, pp. 204–208. Coconut Creek (Florida), ISSN 0749-0208. Shoreline change has been measured with conventional surveying techniques such as Total station, GNSS, EDM etc. These measurements provide short/long term variation of nearshore evolution which enables us to estimate erosional and accretion sediment volume of the beach. This observation of ocean morphology currently has been utilized through the advance of optical imaging system and related digital image analysis. When deployed with proper viewing geometry, ground based digital imaging system can provide higher spatial/temporal resolution of shoreline change than satellite remote sensing data. In this study, we focus on generating time series of shore l...

Fuzzy Classification for Shoreline Change Monitoring in a Part of the Northern Coastal Area of Java, Indonesia

This study presents an unsupervised fuzzy c-means classification (FCM) to observe the shoreline positions. We combined crisp and fuzzy methods for change detection. We addressed two perspectives of uncertainty: (1) uncertainty that is inherent to shoreline positions as observed from remote sensing images due to its continuous variation over time; and (2) the uncertainty of the change results propagating from object extraction and implementation of shoreline change detection method. Unsupervised FCM achieved the highest kappa (κ) value when threshold (t) was set at 0.5. The highest κ values were 0.96 for the 1994 image. For images in 2013, 2014 and 2015, the κ values were 0.95. Further, images in 2003, 2002 and 2000 obtained 0.93, 0.90 and 0.86, respectively. Gradual and abrupt changes were observed, as well as a measure of change uncertainty for the observed objects at the pixel level. These could be associated with inundations from 1994 to 2015 at the northern coastal area of Java, Indonesia. The largest coastal inundations in terms of area occurred between 1994 and 2000, when 739 ha changed from non-water and shoreline to water and in 2003–2013 for 200 ha. Changes from water and shoreline to non-water occurred between 2000 and 2002 (186 ha) and in 2013–2014 (65 ha). Urban development in flood-prone areas resulted in an increase of flood hazards including inundation and erosion leading to the changes of shoreline position. The proposed methods provided an effective way to present shoreline as a line and as a margin with fuzzy boundary and its associated change uncertainty. Shoreline mapping and monitoring is crucial to understand the spatial distribution of coastal inundation including its trend.

Shoreline Change Monitoring in Nellore Coast at East Coast Andhra Pradesh District Using Remote Sensing and GIS

The shoreline is one of the most important features on earth’s surface. They are highly dynamic and ever changing. Changes are over time scales including minutes, hours, decades and Centuries. Spatial scales vary from local to regional to worldwide. Although change is continuously occurring, it doesn’t occur in a constant manner. Many factors influence these changes including the type of shoreline (rocky, sandy), wave activity, tidal variations, storms and human impacts. The shoreline change study is necessary for updating the shoreline change maps and management of natural resources. Shorelines are the key element in coastal GIS and provide the most information on coastal landform dynamics. The frequently monitoring coast only to accesses variation of shoreline changes. In this paper investigate the shoreline changes of Nellore district in Andhra Pradesh coast, as well as find the quantity of the erosion and accretion rate. Using multi-temporal resolution satellite data (TM & LISS III, IV) and Geographic information system (GIS) for past 25 years period i.e., from 1989 to 2015. Nellore having length of coast line is 167 km for this study used. The resultant coastal maps were used to estimate the geomorphologic changes and shifting of the shoreline position. This integrated study is found useful for exploring accretion and erosion processes in the region. About 87.6 km of coastline was found to be accreting nature with average of +1.40 m/yr followed by 38.4 km of coastal line eroding with average of -1.36 m/yr and stable coastline of 41.4 km was found. This study demonstrates that combined use of satellite imagery and statistical method such as linear regression for shoreline change analysis are helpful for erosion monitoring and preventive measure.

Shoreline changes interpreted from multi-temporal aerial photographs and high resolution satellite images: Wotje Atoll, Marshall Islands

Wotje Atoll is located at 9°25′N and 170°04′E within the Republic of the Marshall Islands in the central Pacific Ocean. As on other atolls, the islands perched along the rim of Wotje are low-lying and considered highly vulnerable to the impacts of climate change. A widely anticipated impact of continued sea level rise is the chronic erosion of island shorelines. Using a combination of aerial photographs and satellite imagery shoreline changes are assessed over a 67-year period characterized by rising sea level. Results indicate that between 1945 and 2010 shoreline accretion is more prevalent than erosion, with an average Net Shoreline Movement (NSM) of +1.74m, indicating accretion. Shorelines were accretionary along the lagoon, ocean and channel facing shorelines, as well as on elongate spits and small islands. A high-frequency assessment of shoreline change on a subset of islands in the east of Wotje reveals that islands were stable, with a balance between shoreline accretion and erosion. Shorelines interpreted from high resolution satellite imagery captured between 2004 and 2012 indicate that shorelines within this sample of islands are largely in an erosive state. The post-2004 shift toward erosion may be sea level rise induced, or part of an unresolved shoreline oscillation. This study demonstrates the critical need for improved shoreline change monitoring within atoll settings in order to assess sea level rise impacts along island shorelines.

Detecting coastline change from satellite images based on beach slope estimation in a tidal flat

Beach heights and tidal variation have large impacts on the accuracy of estimates of coastline position and its historical changes of a wider and flatter beach based on remote sensing data. This study presents an approach to analysis of waterline movement based on the beach slope, estimated from two effective images with Landsat images data. Two images acquired at different stages of the tide were processed to delineate accurately the position of the waterline. Then waterlines were assigned heights using elevations predicted by a two-dimensional non-linear tidal assimilation model. Beach slope can be calculated piecewise using the heighted shorelines based on the equiangular triangle theory. The positions of the national tidal height datum coastline can be obtained by the beach slope calculation method to accurately monitor the changing of coastline. A change in the coastline of the southwest tidal flat of the Yellow River delta, from Tianshuigou to the Xiaoqing River mouth, was detected by combining field measurements of profiles and bathymetric data. The root mean squared error (RMSE) of the calculated slope of the intertidal zone was one order of magnitude less than the measured slope. The minimum error of self-consistency check is 0.2%. The RMSE between the coastlines estimated by the proposed method and those surveyed data varies from 53.98m to 217.72m. It is shown that this method is more suitable for the two years and over the time scales of shoreline change monitoring. To assess erosion/accretion patterns in the tidal flat, and the controlling factors, the volume of the beach was investigated as a possible indicator. The accepted coastline position and changes in the beach volume were used to monitor the changing pattern of accretion and erosion along the coast southwest of the recent Yellow River mouth.

Assessment of shoreline changes along the Lithuanian Baltic Sea coast during the period 1947–2010

Shoreline position measurements at various time instants can be used to derive quantitative estimates of the rate of shoreline change and help to understand the magnitude and timing of erosion or accretion processes. Aerial photographs and topographic maps from 1947 to 2010 have been used to derive instantaneous shoreline positions, from which shoreline change rates have been estimated using statistical parameters: shoreline change envelope (SCE), net shoreline movement (NSM), and end-point rate (EPR). Non-metric multi-dimensional scaling (nMDS) has been applied for shoreline classification into dynamic sectors. This study was carried out along 90.6 km of Lithuanian Baltic Sea coast over the time span 1947 to 2010. The study demonstrated that combined use of cartographic data and statistical methods could be a reliable method for shoreline related studies. Application of such data seems to be trustworthy in qualitative monitoring of shoreline changes, while it is the only available method for long term studies.

Spatio-temporal shoreline changes along the southern Black Sea coastal zone

The Black Sea is experiencing human-induced ecological degradation along its coastal zone. As part of the Coastal Zone Management strategy, regular monitoring of shoreline changes plays an important role. Growing population in coastal zones creates extra pressure on shores which leads to the creation of new land filling areas (accretion). Moreover, a recently completed highway construction caused a catastrophic impact on coastal areas of the southern part of the Black Sea and needs to be taken into account. The main purpose of this article is to determine the pattern of shoreline changes along the Turkish coast of the Black Sea. Remote sensing is used to identify and evaluate hot spots of shoreline changes. A developed algorithm automatically extracts the coast line position by processing satellite images covering the period of 1987 to 2001. The maximum and minimum shoreline changes in terms of erosion and accretion were 118 to 53 and 95 to 635 m, respectively. More significant changes have been determined in the eastern part than the western part of the Black Sea. The locations with higher changes were mainly accretion regions along the study area. It can be concluded that coastal movements mainly caused by humans induced impacts at the coasts of the Black Sea. Coastal accretion is significant at the most part of the Turkish Black Sea coast and might be related to a recently constructed international highway.

Sea level and coastal erosion require large‐scale monitoring

There is a coastward migration of the world's population, which is occurring at the same time as rising sea level and shoreline recession; this is the definition of a collision course. Rates of beach erosion along the U.S. east coast average slightly less than a meter per year, putting expensive beachfront development at risk to storm impact. Global sea levels have risen about 20 cm in the last century; relative rates of rise have more than doubled this amount in some areas due to land subsidence. Future sea levels are projected to rise significantly faster than occurred in the 20th century, resulting in acceleration of the present rate of shore recession.There is much debate about future rates of sea level rise, and even some disagreement about the historical rate based on analysis of tide gauge records [IPCC, 2001; Douglas etal, 2001]. An array of satellites are providing the requisite measurements to determine global sea level changes in concert with tide gauges and terrestrial references. At the same time, new technologies such as airborne and spaceborne laser mapping are beginning to provide the data sets necessary for three‐dimensional monitoring of shoreline changes.