Data Collection

The data collection involved a detailed search strategy using two sets of keywords. These keywords aimed to capture literature focusing on shoreline change, coastal erosion, and predictive modeling:

1. ALL FIELDS (“geographic information system” OR “GIS” OR “remote sensing” OR “RS” OR “satellite image” OR “predict*” OR “forecast*” OR “future” OR “multispectral image”)

2. ALL FIELDS (“shoreline chang*” OR “coastline chang*” OR “shoreline monitor*” OR “shoreline detect*” OR “coastal erosion” OR “DSAS” OR “kalman*” OR “Google Earth Engine” OR “sentinel” OR “Landsat”)

The search was conducted on 1 October 2024, yielding 2068 relevant articles. Conference proceedings, book chapters, and editorial letters were excluded from the scope of the study. The selected studies were ranked in descending order based on their citation counts, and the top 100 articles with the highest total citation counts were included in the study. The publications identified during the screening process were carefully evaluated to ensure their alignment with the objectives of the study. When the abstract and/or title information was insufficient, full-text access to the relevant publications was obtained to verify their content. Figure 1 presents a flowchart containing detailed information about the article selection process.

View Figure

• Download as Powerpoint
• Download Figure

Data Analysis Process

In this study, the most cited articles were selected and included in the analysis process. The normality of the data was assessed using the Shapiro-Wilk test; because of the lack of normal distribution, the Mann-Whitney U test was employed for comparative analyses. The relationship between publication age and citation performance and the correlation between total citation count and citation density were examined using the Pearson correlation coefficient method. The dataset used in the statistical analyses was divided into three distinct periods—1991–2001, 2002–12, and 2013–22—to evaluate temporal trends. For each period, the total citation counts and the citation density of the articles were analyzed. These assessments not only provide insight into the scientific impact of research on shoreline change but also illuminate how this impact has evolved over the years. The findings obtained through temporal analysis provide an opportunity to better understand the periodic scientific impact of the literature and to examine the structural changes in research trends more clearly.

The bibliometric analyses conducted in this study were performed using the open-source Bibliometrix R package (K-Synth, 2025), accessed through RStudio and developed in the R programming language. The analysis process was structured through the biblioShiny module, which provides a visual and interactive interface for the package. In the application, the methodological framework developed by Aria and Cuccurullo (2017) was followed, and the analysis proceeded in accordance with the recommended steps. The flowchart presented in Figure 2 shows the overall workflow of the bibliometric process. This approach has provided a foundation for evaluating the development of research activities in the field of shoreline change. The most influential studies, authors, and journals were found using citation and cocitation analyses, which also revealed connections between publications and the formation of research clusters in the field. Furthermore, a keyword analysis employing co-occurrence techniques revealed emerging research topics and dominant themes, providing insight into the thematic structure of shoreline change studies.

View Figure

• Download as Powerpoint
• Download Figure

Analysis of Published Documents

Figure 3 shows the yearly publication trend in shoreline change research, based on the 100 most cited articles. There is a clear increase in the number of studies published between 1991 and 2022, although the pace of growth varies across different periods. In the 1990s, interest in shoreline change was relatively limited, with only one or two publications during most years, except for a small peak in 1998 when four articles were published. This low output likely reflects the limited use of GIS, remote sensing, and DSAS. One early example of methodological study was conducted by Dolan, Fenster, and Holme (1991) and marks an important step in the development of the research area. At the beginning of the 2000s, the number of published articles remained low. In 2007, the number of articles reached five for the first time, followed by three in 2008 and five again in 2009. The peak publication number was nine in 2010, which is the highest number of annual total scientific publications in this field. This growth is closely linked to access to high-resolution satellite imagery, powerful data processing platforms like Google Earth Engine, and widespread use of tools like DSAS. In addition, global attention on environmental issues such as climate change, sea-level rise, and coastal erosion during this period played a major role in boosting interest and research activity in shoreline change (Gao et al., 2023; Nidhinarangkoon et al., 2023; Villagrán, Gómez, and Martínez, 2022). In 2013 and 2014, the number of publications stayed relatively high at eight published articles each year. However, after this period, a downward trend began. From 2015 to 2019, publication numbers varied between five and seven per year. In 2020, the number of publications declined to three, followed by two in 2021 and a single article in 2022. This decline is likely linked to the impact of the COVID-19 pandemic, which significantly affect fieldwork and slowed research activities and project development (Braga et al., 2022; Cavalli, 2024). However, the decline in publications may also be linked to a shift in research focus toward more holistic approaches, interdisciplinary studies, and different geographic scales. Structural factors such as changes in research funding priorities, a sense of methodological saturation in the field, and shifts in environmental policy may also have contributed. In this context, the decrease in shoreline change research likely reflects not only a change in scientific interest but also broader transformations in institutional and financial support systems (Apostolopoulos and Nikolakopoulos, 2021). As a result, the yearly distribution of the most cited publications on shoreline change from 1991 to 2022 demonstrates how technological advancement, increased data accessibility, and growing environmental threats have influenced scientific research in this field.

View Figure

• Download as Powerpoint
• Download Figure

Distribution of Research Articles across WoS Categories

Table 1 presents the distribution of articles across various WoS categories. The geosciences multidisciplinary category leads with 44 articles out of the total 100 articles. The high level of interest in this field is a comprehensive approach to geology, geomorphology, climate science, and environmental processes. Moreover, this category is the most favored in the relevant literature, because it encompasses both fundamental scientific research and applied studies, making it a focal point for interdisciplinary approaches. The second most important multidisciplinary category is environmental sciences, which contains 32 articles, indicating a strong interest in environmental issues. The interest stems primarily from the critical role of environmental impacts on natural systems, such as shoreline change (Dolan, Fenster, and Holme, 1991), coastal erosion (Coca and Ricaurte-Villota, 2022), sea-level rise (Davidson-Arnott, 2005), and climate change (Scavia et al., 2002), which are overwhelmingly included in this category. In this context, the environmental sciences literature has become an important source of reference for risk assessments and policy development processes involving coastal systems. The oceanography category contributes significantly to the literature with 24 articles and it aimed to understand physical processes in coastal environments. In addition, the geography physical category accounts for a substantial portion of the literature, with 23 articles, highlighting the frequent use of spatial analyses and physical geography–based approaches in research. The remote sensing category, with 18 articles, highlights the growing use of remote sensing technologies in research. Smaller yet notable contributions come from engineering ocean (13 articles), engineering civil (12 articles), and imaging science photographic technology (12 articles). The categories of water resources (10 articles) and marine freshwater biology (8 articles) round out the table, reflecting focused research on water and marine biology topics. In conclusion, the distribution of articles across WoS categories shows that the research is primarily focused on geosciences multidisciplinary, environmental sciences, and oceanography. Nonetheless, it shows that there are significant contributions in various engineering and technological categories, including geography physical, remote sensing, engineering ocean, and engineering civil. This distribution clearly reflects the interdisciplinary nature of shoreline change and future prediction research, as well as the growing scientific interest in environmental issues.

Table 1.Top 10 research fields in the WoS database among 100 analyzed articles.

View Fullscreen

Most Cited Publications

The number of citations a publication receives is widely acknowledged as an important indicator of its significance in its research field and potential interdisciplinary impact (Vidal et al., 2022). In shoreline change and future prediction research, analyzing the most highly cited studies allows the identification of pivotal contributions that have shaped the field’s development, as well as insight into the core topics addressed by these influential works. Table 2 summarizes the most cited studies that focused on the use of spatial technologies for shoreline change and future prediction, highlighting the effectiveness of the employed methodologies and emphasizing the interdisciplinary contributions that have significantly advanced the field. Dolan, Fenster, and Holme (1991) had 413 citations their article “Temporal Analysis of Shoreline Recession and Accretion.” This study introduced the Digital Shoreline Mapping System and DSAS as new tools for accurately mapping historical shorelines using maps and aerial photographs. It highlighted their ability to calculate shoreline change rates and improve the precision and efficiency of coastal mapping processes within a GIS environment. A study by Crowell, Leatherman, and Buckley (1991), titled “Historical Shoreline Change: Error Analysis and Mapping Accuracy” received 398 citations. In this study, methods for the collection, analysis, and computation of coastal erosion rates were evaluated using historical shoreline data. It emphasized the importance of data standardization, accuracy, and error assessment in predicting shoreline change and supporting coastal management programs. Alesheikh, Ghorbanali, and Nouri (2007) received 318 citations for their article titled “Coastline Change Detection Using Remote Sensing.” This study developed a new method based on histogram thresholding and band ratio techniques to detect shoreline changes at Urmia Lake using satellite images. The results showed that the lake’s area decreased by approximately 1040 km² between August 1998 and August 2001, verified by TOPEX/Poseidon satellite data. The top 10 list in Table 2 concludes with Valvo, Murray, and Ashton (2006), who received 199 citations for their study titled “How Does Underlying Geology Affect Coastline Change?” This study developed a numerical model to investigate the effect of underlying geology on shoreline change. The results showed that although finer-grained materials erode more rapidly, long-term shoreline retreat tends to become more uniform over time. Consequently, the articles listed in the Table 2 represent key contributions to understanding shoreline changes from different perspectives, such as remote sensing technology, error analysis in mapping, and geological factors affecting shoreline evolution. The number of citations reflects the impact and the relevance of these studies in the broader field of coastal research.

Table 2.Top 10 most cited publications.

View Fullscreen

Highly Cited Publications

The relationship between publication age and total citation count is presented in Figure 4a. The Pearson correlation coefficient is r = 0.35, indicating a moderate positive correlation between the two variables. The p value obtained from the analysis is 0.00038, which indicates that the relationship is statistically significant (p < 0.001). This situation shows that as the publication age increases, the total number of citations also increases; in other words, older publications continue to maintain their impact in the field by receiving more citations over time. Figure 4b shows the relationship between publication age and citation density (i.e. the average annual number of citations). The Pearson correlation coefficient has been calculated as r = −0.6, which indicates a strong negative relationship between the two variables. In addition, the p value of p = 6.4e − 11 indicates that the relationship is statistically highly significant (p << 0.001). This result shows that as the publication age increases, the annual citation rate decreases significantly. In the field of shoreline change, newly published papers receive more citations in a shorter period, which makes these studies more visible and influential in the current literature. The findings generally indicate that older publications reach high total citation counts over time, making a long-term impact, whereas newer publications create a quicker impact with high citation density in a short period. This trend can be attributed not only to the factor of time but also to the technological transformation in research methods. In recent years, the widespread use of advanced analysis tools such as GIS, remote sensing technologies, and DSAS in shoreline change research has brought both methodological innovation and high accuracy to the studies. These techniques allow faster and more detailed analysis of spatial and temporal changes, increasing the scientific value and practical use of studies. This, in turn, boosts interest in and citations of research that uses modern methods.

View Figure

• Download as Powerpoint
• Download Figure

Evolving Citation Trends

Table 3 shows a comparison of the number of citations and citation density across three periods (1991–2001, 2002–12, and 2013–22) for the 100 most cited articles. The analysis reveals a notable trend in the citation patterns of academic articles over time. Although the average number of citations per article has decreased from 159.3 in the 1991–2001 period to 86.76 in the 2013–22 period, representing a substantial drop of approximately 46%, this difference is not statistically significant. This suggests that although newer articles have had less time to gather citations, overall citation accumulation has not dramatically changed. More significantly, the citation density has increased substantially. The citation density rose significantly, from 5.37 citations during the 1991–2001 period to 12.61 citations in the 2013–22 period, highlighting that more recent research is being cited at a faster rate. This increase in citation density is statistically significant, highlighting a meaningful shift in how quickly recent articles are gaining recognition. This shift may be attributed to factors such as the widespread accessibility to research through digital platforms, faster dissemination of information, and the growing number of researchers in various scientific fields. In conclusion, although older articles naturally accumulate more citations over time, newer research is experiencing faster recognition and impact, driven by advancements in technology and increased scholarly activity.

Table 3.Number of citations and citation density of the 100 most cited articles.

View Fullscreen

Journal Contributions

Figure 5 shows the distribution of research articles across scientific journals within the field of coastal studies. The Journal of Coastal Research stands out with the highest number of articles (13), indicating its prominence as a leading journal for research related to shoreline dynamics. Among the key factors that reinforce its position is not only the journal’s focus on current themes such as shoreline change, erosion, sea-level rise, and integrated coastal management but also its adoption of a publication policy that is open to multidisciplinary studies. This approach, which encompasses disciplines such as geology, geography, climate sciences, engineering, and remote sensing, provides a strong foundation for academic interaction in the field of coastal sciences. In addition, the Journal of Coastal Research is indexed in reputable databases such as WoS and Scopus, allows thematic diversity through special issues published at regular intervals, and reaches a wide audience of researchers through its hybrid publishing model. These features make the journal an ideal publication venue for both fundamental academic studies and applied coastal research. Coastal Engineering follows with 10 articles, reflecting significant focus on the engineering aspects of coastal systems. The journal publishes applied and theoretical studies in coastal engineering, with a focus on topics such as numerical modeling, wave–current interactions, and technical design of coastal structures. Coastal Engineering, published by Elsevier, is indexed in both WoS and Scopus; with its high impact factor and hybrid publishing model, it appeals to a broad academic audience. These qualities support the journal’s position as one of the leading publication sources technically focused on shoreline change and prediction research. Marine Geology ranks next with seven articles, emphasizing the importance of geological processes in understanding shoreline changes. The journal prioritizes hypothesis-driven and interdisciplinary studies that cover topics such as sediment dynamics, paleoclimate reconstructions, and coastal morphodynamics. The journal publishes research on observational data, modeling approaches, and sedimentary archive analyses, as well as emerging research areas such as human-influenced coastal and marine geology. Marine Geology, published by Elsevier, is indexed in major databases like WoS and Scopus and increases its presence in the literature through a hybrid publishing model. These features contribute to the journal’s status as one of the preferred publication venues for studies examining the long-term evolution of coastal systems from a geological standpoint. Journals such as the International Journal of Remote Sensing, Estuarine Coastal and Shelf Science, and Geomorphology also play notable roles, each contributing multiple articles, which displays the interdisciplinary nature of the field. In addition, the presence of publications in the journals Remote Sensing of Environment and Environmental Monitoring and Assessment highlights the growing reliance on technological tools and environmental monitoring in coastal research. In conclusion, Figure 5 indicates that shoreline change and future prediction studies are concentrated in various scientific disciplines, including environmental sciences, engineering, geology, remote sensing, and geomorphology. This diversity reflects the development of multidimensional scientific approaches aimed at understanding the complex nature of coastal systems.

View Figure

• Download as Powerpoint
• Download Figure

Interconnections among Key Terms, Leading Authors, and Technological Advances

The three-field plot graph in Figure 6 illustrates the interconnected relationships among key terms, leading authors, and research descriptors in coastal studies. The most prominent terms in research titles include coastal, shoreline, response, analysis, and change, reflecting a strong focus on coastal dynamics, particularly in relation to shoreline changes and environmental responses. Terms like beach, mapping, prediction, and variability further emphasize the use of mapping and analytical methods to predict and understand coastal evolution. Key authors such as I.L. Turner, N. Chandrasekar, A.K. Bhattacharya, and H. Fath are heavily linked to these research areas, demonstrating their significant contributions. The descriptors highlight important topics like coastal erosion, shoreline change, and Landsat, showing the central role of erosion studies and satellite-based shoreline detection in coastal research. Technological tools, particularly remote sensing and DSAS, are frequently associated with this work, reflecting their growing use in measuring and predicting shoreline changes. The graph underscores that coastal research is an interdisciplinary field focused on understanding shoreline variability and erosion through advanced predictive models and technological methods. As a result, Figure 6 displays the significant contributions of key researchers and the importance of evolving technologies in advancing the study of coastal processes.

View Figure

• Download as Powerpoint
• Download Figure

Leading Contributors: Insights from Author Contribution Frequency

Figure 7 presents the contribution frequency of various authors in shoreline studies. I.L. Turner leads with the highest contribution, represented by a value of six, indicating a significant impact in the field. Prominent contributors M.A. Davidson, S.P. Leatherman, R.A. Morton, and K.D. Splinter each have a value of four, reflecting substantial contributions to shoreline change and future prediction research. Authors P.L. Barnard, N. Chandrasekar, M. Crowell, M.D. Harley, and N.G. Plant have a slightly lower value for three, showing that their work is also influential but may cover slightly narrower aspects. As a result, Figure 7 highlights key contributors in the field of shoreline research, with Turner standing out as the most influential, followed by a group of authors whose work has also had a notable impact. This contribution frequency helps to identify leading researchers and their prominence in the study of shoreline dynamics.

View Figure

• Download as Powerpoint
• Download Figure

Publication Trends and Citation Impact

Figure 8 presents the publication trends and citation impact of key authors in shoreline research, highlighting their contributions over time. I.L. Turner stands out as a particularly influential figure, maintaining a consistent output of publications with a significant rise in citation impact in recent years. His increasing influence is illustrated by larger citation counts in the later years of his career. Similarly, M.A. Davidson has demonstrated steady research productivity, although with a relatively lower citation impact compared with Turner. S.P. Leatherman was highly active in the 1990s, contributing several influential works that continue to be cited. However, his recent impact has diminished, indicating the lasting influence of his earlier research. R.A. Morton follows a different pattern also characterized by early productivity. Recent contributors K.D. Splinter, N. Chandrasekar, and P.L. Barnard are also gaining prominence, with Splinter showing a particularly high citation impact in recent years. M. Crowell has had moderate publication activity, with Crowell’s earlier works continuing to accumulate citations. In addition, M.D. Harley and N.G. Plant are emerging as significant contributors, indicating high relevance and influence in recent research. As a result, Figure 8 illustrates the evolving landscape of research influence in shoreline change and future prediction studies, with both long-standing contributors like Leatherman and newer researchers like Turner, Harley and Plant playing crucial roles in advancing the field.

View Figure

• Download as Powerpoint
• Download Figure

Local Impact of Journals: H Index Analysis

The Hirsch index (H index), introduced by J.E. Hirsch, assesses academic performance by accounting for both the number of publications and the number of citations, indicating how many papers have been cited at least an equivalent number of times (Hirsch, 2005). Figure 9 presents the local impact of various academic journals in shoreline research, measured by their H index. The Journal of Coastal Research has the highest local impact, with an H index of 13, indicating its prominent role in publishing influential papers in the field. Coastal Engineering follows with an H index of 10, underscoring its significance in engineering-related shoreline studies. Marine Geology ranks third, with an H index of 7, demonstrating its influence in geology-related shoreline research. Other journals such as International Journal of Remote Sensing; Estuarine Coastal and Shelf Science; Geomorphology; Journal of Geophysical Research: Earth Surface, Ocean & Coastal Management; Remote Sensing of Environment; and Environmental Monitoring and Assessment have lower H indices (ranging from 3 to 5), reflecting their importance in the interdisciplinary aspects of shoreline research. As a result, several journals, such as the Journal of Coastal Research and Coastal Engineering, have achieved high H indices in the field of shoreline research. This can be attributed to their long-standing presence, consistent publication of influential studies, and specialization in key areas such as coastal processes, remote sensing, and environmental management. Their inclusion in major citation databases, interdisciplinary relevance, and broad accessibility have enhanced their visibility and citation frequency, contributing to their strong academic impact over time.

View Figure

• Download as Powerpoint
• Download Figure

Word Cloud

Index terms are generated by a computer algorithm based on frequently used terms in document titles, reference lists, and keywords (Yildirim, Rahman, and Singh, 2022). Figure 10 presents a word cloud that visualizes the most frequently used terms in research related to shoreline studies, highlighting key themes and areas of focus. The most prominent terms, such as remote sensing, shoreline change, and coastal erosion, indicate a central role in the contemporary research. This issue demonstrates that remote sensing techniques are widely used to analyze shoreline change and coastal erosion. For example, Chu et al. (2006) analyzes the erosion and accretion patterns of the Yellow River Delta using remote sensing data from 1976 to 2000.

View Figure

• Download as Powerpoint
• Download Figure

The terms erosion, DSAS, Landsat, and accretion also appear prominently in the word cloud, reflecting emphasis on shoreline monitoring techniques and coastal change detection methodologies. In recent years, various studies have been conducted using the DSAS tool and Landsat images to determine shoreline accretion and erosion rates. For instance, Bera and Maiti (2019) analyzed shoreline erosion and accretion rates in the Sundarbans from 1975 to 2017 using Landsat images and the DSAS tool.

Other significant terms include coastal management, sea-level rise, and GIS, underscoring the interdisciplinary nature of studies that combine geospatial analysis with coastal dynamics. For example, Rao et al. (2009) evaluated the vulnerability of the Andhra Pradesh coast to eustatic sea-level rise by analyzing five physical variables and developing a coastal vulnerability index using the ArcGIS program. The word cloud also highlights terms like shoreline variability, beach nourishment, shoreline prediction, and sediment transport, which point to the practical applications of these studies in managing and mitigating coastal hazards. For instance, Benedet et al. (2004) linked beach morphology with coastal processes by analyzing long-term wave statistics, aerial photography, and sediment data from Florida’s Atlantic and Gulf coasts. Less frequent but still relevant terms such as photogrammetry, linear regression, Google Earth Engine, and applications illustrate the range of methods employed in shoreline research. As a result, the word cloud indicates a strong focus on shoreline change, remote sensing, and coastal erosion as the primary themes in this body of research.

Thematic Map of Density and Centrality

Figure 11 represents the intellectual structure and development of research themes in a specific scientific field through coword analysis. The map is divided into four quadrants based on two axes: centrality (horizontal axis) and density (vertical axis). Centrality indicates how important or relevant a theme is to the overall field, whereas density reflects how well developed or cohesive a theme is internally. In the upper-right quadrant are the motor themes, which are both highly relevant to the field and well developed. These themes, such as “erosion, GIS, and accretion,” are considered the driving forces of the research domain. In the upper-left quadrant are the niche themes, such as “forecasting and shoreline prediction.” These are also well developed but are more specialized and less connected to the broader field. In contrat, the lower-left quadrant contains emerging or declining themes, like “wave climate and coastal management,” which are either gaining initial interest or losing prominence and development. Finally, in the lower-right quadrant are the basic themes, including frequently used but still underdeveloped concepts such as “remote sensing, DSAS, shoreline change, and Google Earth Engine.” These themes are central to the field’s foundation but require further academic development. Each colored bubble on the map represents a thematic cluster of related keywords, with the bubble size indicating the frequency or impact of that theme in the literature. The map as a whole provides a strategic overview of the research landscape, helping scholars identify key areas of focus, recognize emerging trends, and uncover gaps that may warrant future investigation.

View Figure

• Download as Powerpoint
• Download Figure

Network Map

Figure 12 presents a keyword co-occurrence network map that visually illustrates the relationships and thematic structures within the literature on shoreline studies. Each node in the figure represents a keyword, with the size of the node indicating the frequency of the term’s appearance across the analyzed publications. Prominent terms such as remote sensing, coastal erosion, and shoreline change appear as the largest nodes, suggesting they are central and frequently used concepts in the field. The map is divided into color-coded clusters, each representing a group of closely related keywords. For instance, the red cluster centers around terms such as coastal erosion, shoreline change rates, DSAS, and sea-level rise, highlighting a thematic focus on erosion processes and long-term environmental changes. The green cluster includes terms like remote sensing, photogrammetry, and shoreline, indicating a strong methodological emphasis on geospatial tools for monitoring coastal dynamics. The orange cluster relates to coastal management and includes keywords such as accretion, GIS, and beach nourishment, reflecting applied aspects of shoreline stabilization and planning. Smaller clusters, such as the purple one containing shoreline change rate, shoreline prediction and India, point to region-specific or emerging research areas. A separate brown cluster featuring regression and linear suggests statistical modeling as a supporting analytical approach. The pink cluster highlights a thematic focus on satellite-based coastal monitoring and the use of water indices, featuring keywords such as Landsat and MNDWI, the acronym for the Modified Normalized Difference Water Index. As a result, the figure highlights the interdisciplinary nature of shoreline research, combining environmental science, geospatial technology, and coastal management themes.

View Figure

• Download as Powerpoint
• Download Figure

Time Period Analysis

Figure 13 displays the evolution of key themes in shoreline change and future prediction research across three periods: 1991–2001, 2002–12, and 2013–22. The figure highlights the shifting focus of research topics over time, with increasing emphasis on technological approaches. During the earliest period (1991–2001), the main themes were coastal erosion and erosion, suggesting that early research primarily focused on understanding and documenting these physical processes. This foundational work laid the groundwork for subsequent studies. In the 2002–12 period, there is a notable expansion of research themes, with the introduction of shoreline change and remote sensing and continued focus on coastal erosion and erosion. The rise of remote sensing during this decade indicates the growing importance of technological methods in shoreline research. It reflects a shift toward more data-driven approaches in tracking and analyzing shoreline changes and erosion patterns. The most recent period (2013–22) shows continued dominance of remote sensing as a central research theme, alongside the emergence of new technologies such as GIS, Landsat, and satellite imagery. These themes reflect increased reliance on geospatial tools and satellite data for monitoring shoreline changes and predicting future shoreline position. Erosion remains a significant topic, but its centrality is complemented by these newer technologies, indicating an integrated approach to understanding and managing coastal environments. As a result, this timeline demonstrates a clear trend toward the adoption of advanced remote sensing and GIS tools in shoreline change and future prediction research, highlighting the technological evolution of the field over the past three decades.

View Figure

• Download as Powerpoint
• Download Figure

Factorial Analysis

Figure 14 presents a thematic map based on the clustering and spatial distribution of keywords, illustrating the conceptual structure of research in the field of shoreline change and future prediction studies. Each cluster is color coded, with its positioning on the two-dimensional plane representing the relationship and thematic proximity between keywords. The red cluster, located near the center, encompasses core research terms such as shoreline change, remote sensing, coastal evolution, Landsat, and GIS, indicating that this group represents the central and most developed theme in the field. The green cluster, found in the upper-left quadrant, includes terms like shoreline model, prediction, and India, highlighting a research focus on modeling and regional applications of shoreline change analysis. The blue cluster on the far right features terms such as beach nourishment, accretion, coastal zone management, and hazards, suggesting this theme is more specialized and policy oriented, with applications in coastal planning and hazard mitigation. Meanwhile, the purple cluster in the lower-left quadrant contains keywords like coastline change, remote, and change detection, reflecting a more technical and foundational aspect of coastal monitoring using remote sensing tools. In conclusion, this figure reveals the multidimensional nature of the research landscape, with central themes clustered around technological methods and broader applications branching into regional, managerial, and predictive domains.

View Figure

• Download as Powerpoint
• Download Figure