Shoreline Change Research Articles

Storm's influence on long-term shoreline evolution along Casablanca-Mohammedia (Morocco)

Coastal erosion assessment has emerged as one of the most significant instruments for making decisions and offering effective solutions for coastal regions. Mohammedia-Casablanca's shoreline constantly changes due to natural and man-made erosion and accretion. This research uses historical aerial photographs, wave analysis data, geographic information system (GIS) tools, and statistical methods to evaluate spatial and temporal shoreline changes from 1969 to 2020. The analysis of storminess and rates of shoreline change is also discussed jointly in three sediment cells. For this, energy parameters are determined to characterize storm-induced impacts. The Digital Shoreline Analysis System (DSAS) calculated shoreline change using End Point Rate (EPR), Shoreline Change Envelope (SCE), and Net Shoreline Movement (NSM) methods. Out of 2477 transects placed at 30-meter intervals along the study area, approximately 39% of the transects show erosion, and the rest indicate accretion (61%). Over the entire study period (51 years), the analysis of shoreline evolution does not show a clear correlation with storm parameters. The only period in which the shoreline shift correlates with storm activity is 1969–1982. Storms were frequent and intense during this time, and the erosion was at its maximum (over 66% of the coastline). Outside this period, accretion has occurred even during periods of intense storms, as was the case here between 2009 and 2020, when accretion affected 70.1% of the Mohammadia-Casablanca coastline. This suggests that the recent installation of marine structures (groynes, seawalls, dikes, jetties, and piers) multiplied after 1982 has positively affected the rate of coastal erosion.

Analysis of shoreline changes in the city of Gorontalo using remote sensing technology

Coastal areas are essential for economic activities but are also vulnerable to environmental changes caused by human activities. Remote sensing technology can help monitor shoreline changes efficiently and accurately related to the spatial-temporal dynamics of the local area's coastline, which is needed to develop an effective coastal management strategy. By using the Modified Normalized Difference Water Index (MNDWI) water index method for shoreline extraction, the results show that the addition of coastal areas (accretion) as part of the dominant process for coastal equilibrium in almost all coastal regions in Gorontalo City during the 2000-2022 period, experienced trend acceleration significantly during the 2015-2022 period with an increase in the accretion rate of 60.15%. The accretion rate in this period has resulted in an increase in the land area of the coastal zone by 425.44% compared to the accretion that occurred during the 2000-2015 period. The findings of this study can be used as a basis for further research regarding the impact of human activities on coastal ecosystems and the effectiveness of coastal management strategies for Gorontalo City.Keywords: Google earth engine; coastal equilibrium; landsat; sentinel-2; MNDWI

SPATIO-TEMPORAL SCALES OF LAND COVER AND SHORELINE DYNAMICS IN BANAYBANAY, DAVAO ORIENTAL, PHILIPPINES USING AVAILABLE OPTICAL SATELLITE IMAGERY

Abstract. Shoreline dynamics are often the most visible indicators of changes that occur in coastal areas. It is essential to consider a shoreline's physical location while evaluating changes on a temporal and chronological scale. The shoreline in Banaybanay, Davao Oriental, has undergone significant land use changes, leading to negative impacts on related coastal processes, including mariculture conditions in the area. This study aims to determine changes in land cover and shoreline in Banaybanay’s coastal barangays by analyzing satellite images from 1989–2021 using remote sensing, GIS, and Digital Shoreline Analysis Systems (DSAS). The study found that rapid land cover changes in the area were primarily driven by development growth, urbanization, mining, and human activities. The Net Shoreline Movement (NSM), End Point Rate (EPR), and Linear Regression Rate (LRR) results indicated accretion in Banaybanay’s coastal areas, corresponding to an increase in built-ups and barren from 1989–2021. Characterization of land cover and shoreline change revealed high erosion associated with land cover change of barren-water and grassland/brushland-water with a maximum erosion value of −1.19 m/yr. Conversely, very high accretion was mainly characterized by land cover change of water-built-up, barren-built-up, and water-barren with a maximum accretion value of 9.58 m/yr.

Tingkat Kerapatan Mangrove dan Perubahan Garis Pantai Tahun 2016-2022 Menggunakan Citra Satelit Sentinel-2A di Kecamatan Bungus Teluk Kabung

This study aims to, (1) Know the distribution and extent of mangrove land in Bungus Teluk Kabung District, (2) Know the density of mangroves in Bungus Teluk Kabung District, (3) Know the changes in coastline in Bungus Teluk Kabung District, (4) Know the relationship between mangrove density with changes in coastline in Bungus Teluk Kabung District. The research method used is descriptive quantitative, with data presented in the form of tables and maps. Based on the results of the study, (1) Changes in mangrove land area in 2016-2022 amounted to 84.04 ha to 94.39 ha spread in the sub-district of Teluk Kabung Tengah and Teluk Kabung Selatan. (2) The level of mangrove density in 2016 and 2022 is equally dominated by the density level of tight and then followed by the level of very tight, moderate, sparse and very sparse, where the tight level in 2016 is 81.57 ha in 2022 is 80.78 ha. (3) Shoreline changes in 2016-2022 are divided into 5 sectors. (4) The presence of mangroves does not significantly affect the occurrence of shoreline changes in the form of abrasion.

Evaluation of Shoreline Alteration Along theJagatsinghpur District Coast, India (1990–2020) using DSAS

This scientific investigation provides valuable insights into the dynamics of shoreline alteration in the Jagatsinghpur district coast, facilitating informed decision-making for implementing coastal protection strategies. This study presents a comprehensive assessment of shoreline alteration along the 55.045 km stretch of the Jagatsinghpur district coast in India from 1990 to 2020. Landsat 5 TM and 8 OLI satellite image data were used for the analysis. The quantification of erosion and deposition shoreline change rates are computed through a semi-automated approach employing four statistical methods SCE, NSM, EPR, and LLR in the Digital Shoreline Analysis System (DSAS). The coastline was divided into four zones at the tehsil level, resulting in the generation of 5149 transects, categorized as Paradip tehsil-I, Abhyachandpur tehsil-II, Ersama tehsil-III, and Balikud tehsil-IV. The analysis revealed significant erosion in specific areas, including Paradip town in Zone I, Nuagan in Zone II, Zone III, and Kusupur in Zone IV. The decision matrix showed an urgent need for erosion rectification in specific regions. The results indicate the necessity of implementing coastal protection measures in Zone III, B, and D subregions in Zone I and D and F subregions in Zone II. Meanwhile, in Zone IV, subregions A and B necessitate attention.

Design and application of coastal erosion indicators using satellite and drone data for a regional monitoring program

Coastal erosion is a complex issue that affects landforms at various spatio-temporal scales, with concerns rising due to the impending threats of climate change. Given the increasing availability of coastal shoreline data, we identify a gap in present coastal management methods: the need for a simple and cost-effective mechanism to track and compare shoreline trends, to inform high-level reporting, down to local management scales. This study introduces simplified, automated erosion indicators, demonstrated for 20 morphologically diverse beach sites across the temperate coast of Victoria, Australia. The methods utilise coastal drone surveys (2018–2023; 560 surveys) and satellite-derived shorelines (Digital Earth Australia Coastlines, 1988 to 2021). Two tools are introduced: (1) the Erosion Warning Indicator, for high-level reporting, reducing multiple aspects of shoreline change (long-term vs. short-term; widespread vs. hotspot) to a simplified scoring system allowing overall site assessment and comparison across sites; and (2) the Erosion Hotspot Detector, to aid local managers to automatically identify and analyse emerging erosion areas. Results for a 2-year period (2021-22) indicate one site with a high erosion warning level, and four sites with a moderate level. Tracking the indicator over time (2018–2022) identifies two sites with persistently high erosion warning levels (Apollo Bay and Marengo). Importantly, the indicators also highlight areas where recent erosion trends differ from longer-term patterns (e.g., Inverloch), allowing re-evaluation of short-term expenditure on management interventions, without impacting longer-term adaptation pathways. The erosion indicators presented here hold value for coastal managers in many parts of the world. If comparable approaches are introduced and shared at scale, we will collectively be better equipped and informed to respond to future challenges to our coastlines.

Inlet-adjacent beach and shoreline variability at decadal scales

Beaches provide storm protection and economic benefit for coastal communities and also host important habitats for keystone species, especially in the state of Florida. However, sea level rise, coastal construction, and intensifying storms are resulting in coastal erosion, which often requires informed mitigation and management strategies. This study aims to explore decadal-scale trends in morphology change and shoreline variability of inlet-adjacent beaches in Jupiter, Florida. Data from three locations over a period of three decades were analyzed to determine volumetric and contour changes above the shoreline (0 m elevation) and across the entire profile. The largest variability in decadal morphology change was measured at beaches closest to Jupiter Inlet. Substantial shoreline and beach changes were also associated with periods of higher storm activity. Variability in storm events, nourishment trends, and longshore sediment transport also influenced decadal morphologic change. To best adapt to coastal change and develop comprehensive beach-inlet management plans, it is imperative to understand past trends of shoreline variability and beach-nearshore erosion and accretion patterns. Results of this study demonstrate an approach to elucidate decadal patterns in morphology changes and drivers of change.

Impacts of anthropogenic structures in long- and short-term shoreline evolution of Santa Marta Bay (Colombian Caribbean)

Interaction of Anthropic interventions (rigid structures) with coasts is an essential aspect for understanding their geomorphic evolution and incorporating these data into adequate coastal management. This study analyses the short and long-term behavior (1985 to 2019) of shoreline at Santa Marta Bay (Caribbean - Colombia) and their relationship with coastal protection structures. The shoreline variations were analyzed through aerial photographs and satellite images using DSAS tools. The short-term assessment showed initial intense 1985–1991 erosion, with an average retreat speed rate of − 1.6 m·y− 1. It changed gradually since 2003, due to the construction of rigid structures and beach nourishment, decreasing shoreline retreat and even a progradation rate of 0.2 m·y− 1 was observed. The 2009–2019 period, despite recording a positive average value, exhibited a high percentage of erosion profiles. Therefore, in a decadal or long-term analysis (1985–2019), despite engineering works present positive results in the short term, new interventions are required. The coastal erosion is not uniform along the shoreline, because the area is a closed bay with small sediment inputs, the variations in erosion and accretion rates change with human intervention and the installation of new structures. Therefore, quantifying the scale and rate of shoreline changes and correlating them with anthropogenic structures is an essential step in assessing shoreline vulnerability.

Shoreline delineation and change analysis in response to sea level rise and coastal bathymetry along the coast of Visakhapatnam, India using high-resolution optical imagery

Shoreline delineation and change analysis in response to sea level rise and coastal bathymetry along the coast of Visakhapatnam, India using high-resolution optical imagery

PyShoreVolume 1.0.0: A Python based Shoreline Change and beach Volumetric Change Analysis tool

Shoreline Change Analysis (SCA) and Volumetric Change Analysis (VCA) are of growing importance to coastal managers throughout the world. The volume, resolution and accuracy of shoreline configurations are gradually improving, which demands tools for efficient processing and analysis. The limited number of systems that combine the two analysis types have lengthy workflows or require commercial software licences, with no current tool that automates VCA from a time series of Digital Elevation Models (DEM’s). We present a new, dedicated and open-source package for automating SCA and VCA in the Python environment. It is designed with a user-friendly interface and workflow, delivers efficient processing speeds, automatically generates map based graphical outputs and computes a full range of positional statistics. We verify the package delivers equivalent outputs to existing tools (AMBUR, DSAS) and demonstrate strong performance by reconstructing erosion and accretion over the last twenty years along the beaches of the Taw and Torridge Estuary, North Devon, UK, a region known to have a complex sediment and morphometric dynamics.

Numerical Analysis of Shoreline Changes along the Coast Batu Hiu-Bojong Salawe, Pangandaran Regency, West Java Province, Indonesia

Shoreline change poses a significant challenge in coastal regions, leading to issues such as abrasion, soil erosion, and the loss of valuable land. This problem is prevalent in various areas of Pangandaran, particularly in the Batu Hiu-Bojong Salawe coastal region of Pangandaran Regency, West Java, Indonesia. The objective of this study is to analyse and quantify the distance and rate of shoreline changes occurring over a decade (2010-2019) in the Batu Hiu-Bojong Salawe coastal area. Utilizing ArcMap software and the Digital Shoreline Analysis System (DSAS), this research aims to provide insights into the coastal dynamics, drawing analytical points from comparable studies for a comprehensive understanding. Batu Hiu's western coast faces substantial erosion (29.70m, LLR 3.10 m/year, EPR 3.22 m/year), while the east experiences accretion (52.76m, LLR/EPR 5.49 m/year, 5.72 m/year). Coastal dynamics, influenced by rocky structures, lead to sedimentation and erosion. Bojong Salawe Beach sees noteworthy accretion (83.01m, LRR/EPR 8.88 m/year, 9.00 m/year), with a maximum at transect 85 (134.5m, LRR 14.27 m/year, EPR 14.58 m/year). Erosion at transects 104 and 107 averages 30.47m, with LLR/EPR rates of 3.41 m/year and 3.3 m/year. The Cijulang River estuary contributes to coastal stability, resulting in significant accretion. This information is vital for coastal management, offering insights to address erosion and accretion impacts in Batu Hiu and Bojong Salawe coastal areas.

Detecting Shoreline Changes on the Beaches of Hainan Island (China) for the Period 2013–2023 Using Multi-Source Data

This study presents an in-depth analysis of the dynamic beach landscapes of Hainan Island, which is located at the southernmost tip of China. Home to over a hundred natural and predominantly sandy beaches, Hainan Island confronts significant challenges posed by frequent marine natural disasters and human activities. Addressing the urgent need for long-term studies of beach dynamics, this research involved the use of CoastSat to extract and analyze shoreline data from 20 representative beaches and calculate the slopes of 119 sandy beaches around the island for the period from 2013 to 2023. The objective was to delineate the patterns of beach evolution that contribute to the prevention of sediment loss, the mitigation of coastal hazards, and the promotion of sustainable coastal zone management. By employing multi-source remote sensing imagery and the CoastSat tool, this investigation validated slope measurements across selected beaches, demonstrating consistency between the calculated and actual distances despite minor anomalies. The effective use of the finite element solution (FES) in the 2014 global tidal model for tidal corrections further aligned the coastlines with the mean shoreline, underscoring CoastSat’s utility in enabling precise coastal studies. The analysis revealed significant seasonal variations in shoreline positions, with approximately half of the monitored sites showing a seaward progression in summer and a retreat in winter, which were linked to variations in wave height. The southern beaches exhibited distinct seasonal variations, which contrasted with the general trend due to differing wave impacts. The western and southern shores showed erosion, while the northern and eastern shores displayed accretion. The calculated slopes across the island indicated that the southern beaches had steeper slopes, while the northern areas exhibited more pronounced slope variations due to wave and tidal impacts. These findings highlight the critical role of integrated coastal management and erosion control strategies in safeguarding Hainan Island’s beaches. By understanding the mechanisms driving seasonal and regional shoreline changes, effective measures can be developed to mitigate the impacts of erosion and enhance the resilience of coastal ecosystems amidst changing environmental conditions. This research provides a foundational basis for future efforts aimed at the sustainable development and utilization of coastal resources on Hainan Island.

Dynamic shoreline alterations and their impacts on Olive Ridley Turtle (Lepidochelys olivacea) nesting sites in Gahirmatha Marine Wildlife Sanctuary, Odisha (India)

Currently, sea turtle habitats are being altered by climate change and human activities, with habitat loss posing an urgent threat to Indian sea turtles. Thus, the objective of this study is to analyze the dynamic shoreline alterations and their impacts on Olive Ridley Sea Turtle (ORT) nesting sites in Gahirmatha Marine Wildlife Sanctuary from 1990 to 2022. Landsat satellite images served as input datasets to assess dynamic shoreline changes. This study assessed shoreline alterations and their rates across 929 transects divided into four zones using the Digital Shoreline Analysis System (DSAS) software. The results revealed a significant 14-km northward shift in the nesting site due to substantial coastal erosion, threatening the turtles' Arribada. This study underscores the need for conservation efforts to preserve nesting environments amidst changing coastal landscapes, offering novel insights into the interaction between coastal processes and marine turtle nesting behaviors.

Shoreline Changes and Sediment Transport along Nhat Le Coast, Vietnam

One of the most beautiful beaches in Northern Vietnam, Nhat Le, has recently experienced severe erosion as a result of the ensemble interaction of natural factors, such as tropical cyclones, extreme weather events, and human activities. Consequently, negative impacts on tourism and social and economic development have been recorded. This paper aims to provide a deep understanding of the changes in shoreline and longshore sediment transport at Nhat Le estuary based on two modules of LITDRIFT and LITLINE of the LITPACK software package combined with geospatial analysis. The rate of change statistics is calculated using the Digital Shoreline Analysis System (DSAS) from 30-year multi-temporal satellite data (1989-2019) for multiple historical shoreline positions. The Module of LITDRIFT is employed to estimate sediment transport and the shoreline position calculated from the LITLINE module. These data are then compared with measured topographic data and satellite images. Wave climate conditions are incorporated into the LITDRIFT module to identify the volume of sediment transport along the coast on seasonal and annual bases. The results illustrate that a mean erosion rate of about 2 m per year was observed in the southern sandspit of Nhat Le from 1989 to 2019. This rate reaches 4.5 m per year during 2009-2019.

Geospatial analysis of shoreline and areal dynamics in the Ganges deltaic island of Bangladesh using the GIS-DSAS technique

Manpura Island, located at the mouth of the Ganges-Brahmaputra-Meghna (GBM) River estuary, is a well-known Ganges deltaic island prone to severe erosion. This study aims to identify shoreline and areal changes in Manpura Island of Bangladesh from 1990 to 2020 using the digital shoreline analysis system (DSAS), a plugin of ArcGIS. The estimation of shoreline variability was primarily described for four segments of the Island: Segment A in the north, Segment B in the west, Segment C in the south, and segment D in the east. It was observed that all four segments of the study area are vulnerable to high rates of shoreline erosion. Landward movement was high in Segment A where Net Shoreline Movement (NSM) was −4000.1 m. Landward movement was also high in Segments B and C with the NSM of −1084.7 m and −1021.6 m, respectively. According to the End Point Rate (EPR) and Linear Regression Rate (LRR), Segment A exhibited a very dynamic feature, with an average shoreline change rate of −24.7 m/yr and −24.2 m/yr, respectively. In Segment C, the average shoreline change rate was −8.5 m/yr for EPR and −9.1 m/yr for LRR. Approximately 392 transects were constructed in the four segments of the island, with approximately 330–334 showing landward movement and 58–62 showing seaward movement. Nevertheless, the island lost about 28.4 km2 in land area and gained only around 2.3 km2 of its original landmass during the study period. The total loss of shoreline length was about 11.5 km (0.4 km/yr), while the total loss of land area was about 26.1 km2 (0.9 km2/yr). The main factors of shoreline change in the study region is likely to be high river discharge, stormy climate and, human interference. The results of this study are useful for the proper management and planning of Manpura Island. However, they can also be used in statistical approaches to forecasting possible shoreline locations in the future under double pressure of climate change and human activities.

Coastal transgressive dunefield evolution as a response to multi-decadal shoreline erosion

The Younghusband Peninsula coastal barrier extends ∼190 km and is predominantly comprised of a mix of active, semi-stabilised and stabilised (relict) transgressive and parabolic dunefields. Wave driven shoreline erosion has triggered the rapid development of a transgressive dunefield along a portion the peninsula. This study focuses on a ∼2 km region with the highest regional erosion rates (> −2.0 m/year since 1988), and which has experienced rapid destabilisation and subsequent landward translation of the dunefield. Aerial LIDAR derived datasets of the barrier system from 2008 and 2018 and eight drone photogrammetry surveys between August 2020 and April 2022 are used to compare the rates of change across the beach-dune system. The net and intra-survey changes are used to show the short- to medium-term system response and illustrate the relationship of sediment dynamics to the developing morphology and structure of the dunefield. Shoreline change rates (m/yr) are sourced from the Digital Earth Australia coastlines dataset which provides annual rates for continental Australia from a Landsat time series (1988–2021). When the rate of shoreline change is segmented from the total dataset to the study time-period (2008–2021), the average resulting rates show an increase from −2.2 m/yr to −3.3 m/yr, respectively. This coincides with a landward advance rate of >10 m/yr from 2008 of the dunefield edge, with the fastest eroding dune toes corresponding to regions with the highest rate of dunefield translation and transgression. Net volumetric totals and their ratios of gain to loss of sediments show that significant sediment is lost to offshore during the retrogradation of the dunefield as only a fraction of the stoss slope sediment is transferred landwards. All regions of the dunefield exhibit a net loss of sediments but the high-temporal resolution shows that the magnitude of 3D changes varies through time. An adapted model of erosional stoss slope evolution and dunefield development is advanced and a temporal model of transgressive dunefield evolution is synthesised.

Application of Artificial Intelligence for Monitoring Shoreline Changes in the Central Coast of Vietnam

The identification and monitoring of coastline and shoreline plays an important role in coastal erosion assessment. The deep learning models can be a potential tool to detect the coastlines and shorelines in Vietnam using ultra-high resolution satellite images. The aims of the study are: i) To propose a set of indicators to determine the coastlines and shoreline; ii) To build deep machine learning models that automatically interpret the coastlines and shorelines on ultra-high resolution remote sensing images; and iii) To apply developed deep learning (DL) models to monitor coastal erosion in central Vietnam. Eight DL models were implemented based on four artificial intelligence network structures, including U-Net, U2-Net, U-Net3+, and DexiNed. Satellite images collected through Google Earth Pro software were used as input for all models. As a result, the U-Net model has been effectively applied to coasts in Cu De, Lai Giang, and Bien Lo estuaries,. The output results were used to calculate the rate of erosion/accretion in these areas. Additionally, the study indicated that coastline is a suitable criterion in assessing coastal erosion under the impact of sea level rise during storms. On the other hand, shoreline is a suitable criterion in assessing tidal fluctuations or instantaneous movements of wave currents during the year.
 

Evaluation of beach response due to construction of submerged detached breakwater

Submerged detached breakwaters (SDBWs) have increasingly been used in recent times as an alternative against their emergent counterpart (EDBWs) to mitigate erosion because the former do not spoil the seascape. Both of these structures are (usually) constructed using precast concrete blocks or natural granite rocks, hence becoming permeable structures. For an EDBW, a parabolic bay shape equation can be readily used to estimate the planar shape of the shoreline behind the structure, but there is still no approach to estimate how the shoreline behind the SDBW is formed. In this study, we estimated how the shoreline is balanced by examining how the dominant wave direction changes due to the diffraction of the transmitted wave generated after the installation of the SDBW from the long-term wave directional spectrum. The change in dominant wave direction was determined under the shoreline gradient condition where littoral drift does not occur, considering the diffraction phenomenon due to the difference in transmitted waves. This means that the shape of the equilibrium shoreline changes to face perpendicular to the dominant wave direction. As a meaningful result, when the transmittance is 0, it converges to the well-known empirical equation of EDBW. The present methodology is validated by comparing the observed data (wave and shoreline change) from two beaches (Anmok and Bongpo-Cheonjin Beaches) on the eastern coast of Korea. This rational approach to shoreline changes behind permeable SDBWs will help in proactive review work for coastal management as well as beach erosion mitigation.

Variations in biophysical characteristics of mangroves along retreating and advancing shorelines

Mangrove shoreline retreat or advance is a natural process in a mangrove delta. However, due to various natural and anthropogenic stressors, mangrove shoreline retreat is the second largest cause of mangrove loss globally. It is important to understand the scale at which mangrove shoreline changes are causing biophysical changes along the mangrove shorelines and, in turn, understand if certain biophysical characteristics can explain the changes along the shoreline. This will help identify the response of mangroves to shoreline changes. Videography and spatial mapping were used to study temporarily and permanently changing mangrove shorelines in the Sundarbans, the largest mangrove forest in the world (~10,000 km2), located in India and Bangladesh. Data was collected along a ~ 239 km shoreline at 54 sites. 36.4 % of all the studied shorelines were experiencing major retreat, 63.8 % and 27.2 % of all (major and minor) retreating areas had 1–25 % and > 25 % dead trees. The biophysical characteristics statistically (P < 0.0001) associated with retreating mangrove shorelines were – cliff-type shoreline profiles, number of dead trees, and absence of stream and grass, with shoreline profiles as the strongest predictor of shoreline retreat. Moreover, 68.7 % and 73 % of historically retreating shorelines had a cliff-type shoreline profile and Excoecaria agallocha as the dominating species, respectively. Moreover, due to the strong correlation between historical changes and current shoreline types, it was concluded that characteristics along the shoreline are partly a product of historical shoreline transitions. Thus, the present status of the shoreline can not only predict the history of the shoreline but can also give insights into the future biophysical changes in the mangrove forests.

Evolutionary dynamics of island shoreline in the context of climate change: insights from extensive empirical evidence

ABSTRACT The evolution and future trajectory of island shorelines, amidst global climate change, are of increasing concern to governments, communities and researchers worldwide. However, the field of island studies is often hampered by a lack of data and inconsistent methodologies, leading to an inadequate understanding of the processes driving shoreline changes on islands within the context of climate change. This research aims to bridge this gap by analyzing islands in Southeast Asia, the Indian Ocean and the Mediterranean Sea from 1990 to 2020 using remote sensing. Of over 13,000 islands examined, approximately 12% experienced significant shifts in shoreline positions. The total shoreline length of these islands approaches 200,000 km, with 7.57% showing signs of landward erosion and 6.05% expanding seaward. Human activities, particularly reclamation and land filling, were identified as primary drivers of local shoreline transformations, while natural factors have a comparatively minor impact. Moreover, the ongoing rise in sea levels is identified as an exacerbating factor for coastal erosion rather than the primary cause. Drawing from these findings, we propose several adaptive measures for islands in response to climate change. Taken together, this research provides comprehensive data and a basis for decision-making for sustainable development of island territories.