Assessment of Climate Vulnerability Indices for Coastal Tourism Destinations

Abstract

Coastal ecosystems are crucial for territorial development but they face increasing pressure from population growth and climate change. These factors threaten ecosystems, communities, and tourism infrastructure. It is essential to assess vulnerability to achieve adaptation and indices are widely used for this purpose due to their simplicity. However, inconsistencies persist in definitions, methodologies, dimensions, and variable selection. This systematic review of 43 second-generation studies analyzes the evolution of conceptual approaches, identifies the most common indicators, and examines index methodologies. The results reveal that, although the IPCC has updated its definition of vulnerability, many publications still use previous conceptual frameworks. While temperature is relevant to tourism, most studies focus on increasing sea level and its effects. In some cases, social and economic dimensions are treated jointly whereas in other studies they are considered separately. Variable selection remains case-specific and a robust, standardized framework is still lacking, especially for social aspects. Despite the undoubted importance of tourism, specific research on this sector is scarce. This review underscores the need for standardized indices tailored to coastal tourism management under climate change. Future research directions are also proposed.

1. Introduction

Coastal ecosystems play a key role in the global economy as they support tourism, maritime transport, fisheries, and aquaculture [1]. Migration to coastal areas, which is driven by better living conditions and economic opportunities, has led to continuous growth, especially in emerging countries [2,3,4,5]. Currently, around 40% of the global population lives within 100 km of the coast and this is projected to increase to 50% by 2030 [4,6]. This growth highlights the importance of coastal zones [1], but uncontrolled urbanization increases greenhouse gas emissions and overuses ecosystem services [7]. Intensive human development reduces coastal ecosystem resilience and increases vulnerability to climate impacts [1,8].

The close link between climate and tourism underscores the need for accurate climate forecasts to guide decisions aimed at mitigating negative impacts. Rising sea levels, extreme tides, storm surges, wave setup, strong winds, floods, and droughts all threaten ecosystems, livelihoods, and infrastructure [4,9,10]. Within 50 years, up to 30% of infrastructure within 200 m of the coastline may be damaged by erosion [11]. Climate vulnerability assessments are essential for spatial planning and for developing adaptation and mitigation policies [12,13]. In spite of extensive research on coastal risks and vulnerabilities [14,15,16], standardized methods remain unavailable due to definitional and methodological disagreements [17].

Index-based approaches are popular due to their simplicity and efficiency. However, these methods vary significantly in terms of names and the variables used. Early indices focused on physical variables [18,19], whereas newer ones include socioeconomic factors to provide a more holistic view. Indices have been applied at national and regional scales [20,21,22,23]. However, many authors suggest that such indices are more effective locally, where systems can be tailored to specific cases [24,25]. Despite the numerous research on urban coastal vulnerability, standardization in management tools remains elusive and better indicator selection is required.

The evolving vulnerability concept in IPCC reports adds complexity [26]. This concept was first used for coastal areas in the 1970s and interest grew rapidly from 1990 [27]. Publications have shifted away from external system characteristics (hazards) to internal ones (sensitivity and adaptive capacity), thus reflecting a move from impact-based to vulnerability-based approaches [26,28]. Füssel and Klein [29] classified impact-focused studies as first-generation and those in which internal factors are integrated as second-generation. Defining key factors prior to carrying out an analysis is essential for robust assessments.

A unified conceptual framework for indicator selection does not exist as yet, particularly for socioeconomic indicators, which often depend on data availability. This lack of consistency is a key challenge, as it limits comparisons across regions [25] and leads to an incomplete, variable approach to vulnerability assessment. Many research address only selected impacts and often exclude tourism-related aspects. A holistic approach is therefore needed to identify not only hazardous areas but also community-level vulnerability [30]. Future research should focus on using consistent, tourism-relevant indicators to inform the design of effective climate policies [31]. In spite of rapid growth in this field, inconsistencies in definitions, methods, dimensions, and indicators persist. Systematic reviews are crucial to synthesize findings, identify gaps, and guide research.

In this review a total of 43 second-generation studies were systematically selected that integrate sensitivity and adaptive capacity using coastal vulnerability indices. The aim of this review is to bridge science and coastal policy-making and to provide a clear overview of indices that are comprehensive yet practical. Specific objectives include:

• Analyzing the evolution of the vulnerability concept in IPCC reports.
• Identifying countries and years with the most publications to highlight global trends.
• Classifying studies by main focus (drivers, effects, or both) to reveal thematic trends.
• Identifying the most widely used indices and their terminology.
• Analyzing how IPCC dimensions (sensitivity, adaptive capacity, exposure) are addressed.
• Identifying the most widely used indicators in each dimension.
• Identifying main assessment techniques for coastal vulnerability indices.
• Assessing the inclusion of tourism in vulnerability assessments of coastal destinations.
• Evaluating analysis scales and data availability, with an emphasis on local open data access.

2. Materials and Methods

This systematic review (Figure 1) is structured according to the PRISMA 2020 guidelines (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) [32]. These guidelines ensure transparency in documenting the publications included in the review and in the subsequent meta-analysis (Figure 2).

Prior to carrying out the review we formulated a PICO research question (Population, Intervention, Comparison, Outcome), from which the search keywords were derived. The PICO question was: In coastal tourism destinations (P), which climate change vulnerability indices (I) have been used, developed, or compared (C) in the literature, and what are the most effective variables, techniques, and outcomes (O) for assessing vulnerability and guiding tourism planning?

The search was conducted in Web of Science, Scopus, Google Scholar and Dialnet databases to ensure the inclusion of a broader range of academic works, including book chapters, and to identify relevant non-English-language literature. Keywords were combined using Boolean operators (AND, OR, NOT), truncations (“*”, “?”) and quotation marks depending on each database. For example, the following combination was used in June 2024 on:

• Web of Science: coast* AND tour* AND(destination OR area OR zone) AND vulnerab* AND(climate OR index OR assessment OR evaluation) AND (method* OR design OR measure OR comparison OR analysis OR framework OR approach OR assessment OR develop*) AND(variable OR indicator OR “best practice” OR effective OR implement*) and Article or Review Article or Book Chapters (Document Types) and English or Spanish or Portuguese (Languages) and Environmental Sciences Ecology or Geology or Oceanography or Meteorology Atmospheric Sciences or Engineering or Social Sciences Other Topics or Biodiversity Conservation or Physical Geography or Business Economics or Geography or Public Environmental Occupational Health or International Relations or Development Studies or Public Administration or Sociology (Research Areas). With these keywords and delimitations by document type, language, and research area, the database yielded a total of 190 publications, from which we identified 179 as appropriate for inclusion in the selection process.
• Scopus: coast* AND tour* AND(destination OR area OR zone) AND vulnerab* AND(climate OR index OR assessment OR evaluation) AND (method* OR design OR measure OR comparison OR analysis OR framework OR approach OR assessment OR develop*) AND(variable OR indicator OR “best practice” OR effective OR implement*) and Article or Review Article or Book Chapters (Document Types) and English or Spanish or Portuguese (Languages) and Environmental Sciences or Earth and Planetary Sciences or Social Sciences or Engineering or Business, Management and Accounting or Multidisciplinary or Economics, Econometrics and Finance or Decision Sciences (Research Areas). In this case, the database returned a total of 180 studies, and we identified 150 as suitable for this study.
• Google Scholar: coast* AND tour* AND destination AND “climate change” AND “vulnerability index” AND methodology AND (variable* OR indicator) AND “best practice” and with a temporal interval between 2016 and 2024. This filter was particularly useful in Google Scholar because, unlike other databases, this search engine indexes the full text of documents, which could generate a large number of less precise results if not delimited. Google Scholar give us 64 studies and we found 20 as appropriate for inclusion in the selection process.
• Dialnet: coast tour* (destination OR zone OR area) “climate change” vulnerability (index OR evaluation OR analysis) (methodology OR design OR development) (variable? OR indicator) with the full-text delimitation, the database yielded 23 publications, and we identified 8 as suitable for this research paper.

Based on the search, 357 potentially relevant research were initially identified by title (Figure 2). The results were incorporated into a database and 39 duplicates were removed. Inclusion and exclusion criteria were then applied in a first screening process based on titles, abstracts, and keywords to exclude 199 studies that clearly did not meet the established criteria and to reduce the dataset to a more manageable size.

In this first stage, and in an effort to address the specific focus on climate change vulnerability in coastal tourism destinations, only articles that explicitly address “vulnerability”, geographically focused on coastal areas, centered on climate change drivers or effects, and published from 2016 onward were included (119) (Figure 2). The aim of applying this publication cutoff was to consider only publications carried out under updated frameworks and methodologies for climate vulnerability assessment. The selection of 2016 as the cutoff reflects key milestones in international climate governance. The IPCC Fifth Assessment Report, published in 2014, marked a conceptual shift in understanding vulnerability. Additionally, the Paris Agreement [6], adopted at COP21 and effective since 4 November 2016, set concrete goals to limit global warming and strengthen adaptive capacity to adverse effects. These events significantly influenced how vulnerability is conceived, assessed, and managed, especially in coastal contexts.

In the second stage, full texts selected in the first screening were analyzed and additional exclusion criteria were applied (Figure 2) to ensure only publications that meet all requirements were included. 10 review articles were excluded since the focus was on practical studies in which indices are developed or applied. 18 studies that assessed vulnerability using non-index-based approaches were not retained, in order to identify and determine the most commonly used types of indices. Finally, in order to align the analysis with the most recent and robust conceptual frameworks, 43 studies that did not fully integrate a comprehensive set of vulnerability dimensions were excluded. The review focused on recent definitions from the IPCC (AR5/AR6) [34,35] and contributions from other researchers [36,37,38,39], which state that vulnerability is part of the risk framework and consists solely of sensitivity and adaptive capacity. Physical and geomorphological dimensions were also considered, as they are directly related to exposure and hazards, and publications referring to physical, social, and economic dimensions as indicators of the three key components of vulnerability (exposure, sensitivity, and adaptive capacity) were included. It is essential to include the economic dimension due to the central role that tourism plays in coastal systems. Moreover, 5 studies focusing on specific vulnerabilities (e.g., the vulnerability of seaports or the ecology of mangroves) were omitted to ensure a broad and holistic perspective on vulnerability that encompasses territory, infrastructure, ecosystems, communities, society, livelihoods, and tourism activities.

Finally, after completing the selection process, 76 full-text studies were excluded and 43 were included in the review (Supplementary Materials Annex 1). A detailed reading of the selected studies was then carried out. During this coding phase, relevant data were extracted and recorded in an Excel database. Information was organized under the following variables: index name, sub-indices (if applicable), method, equation and its methodological basis, weighting type, tools or techniques used, number and name of indicators, data sources, scales, geographic context, and tourism relevance.

Indicator nomenclature was standardized and grouped into broader categories in order to facilitate cross-study comparison. For physical indicators the following categories were identified: geomorphology and physical characteristics, hydrology and climate, natural hazards and climate change, land use and ecosystems, and infrastructure and society. Variables that appeared only once across all research were excluded to simplify the results. A greater diversity was observed for social indicators and nine categories were identified: demographics and population structure, socioeconomic conditions, knowledge and education, health and well-being, housing conditions, environment and coastal resilience, infrastructure and service access, economic activities and livelihoods, and vulnerability, governance, and risk adaptation. Finally, a critical analysis was conducted to integrate the findings, identify patterns, and detect gaps in the literature.

To ensure the reliability and relevance of the included studies, a critical assessment was performed, focusing on the conceptual and methodological aspects of each publication. This analysis was based on the following key criteria, with each criterion contributing to a final score that determined the suitability of each study for the review:

• Focus on specific climatic effects. To avoid generic analysis and to ensure thematic specificity, publications centered on direct climatic effects such as heatwaves, drought, erosion, and floods were prioritized. These studies provide a more robust foundation for developing a practical index compared to those that only focus on general impacts or drivers. (1 point).
• Clear methodology and tool specification. The clarity of the methodology was evaluated, giving attention to the following aspects: (a) The use of differentiated weighting to assign relative importance to indicators (2 points) was valued more highly than the use of equal weighting (1 point). (b) Multi-criteria decision-making methods were prioritized for their practical applicability in management work (1 point). (c) A well-specified and transparent methodology was required (1 point). (d) AHP and PCA analyses were given special consideration, as they are common tools in management decision-making (1 point).
• Appropriate scale of analysis. Studies were given credit for using a municipal scale of analysis, which is considered the most appropriate for this type of work (1 point).
• Use of open-access data. The use of open-access data is a more practical way to bridge the gap between research and management or policy. Equal value to publications that exclusively use open-access data and to those that combine it with In Situ data was assigned (1 point).
• Inclusion of tourism. Studies that integrate tourism into their analysis were considered particularly relevant (1 point).

3. Results

3.1. Historical Evolution of the Concept of Vulnerability

In 1990 the IPCC [40] developed a common methodology for assessing vulnerability, primarily focusing on the impacts associated with the rise in sea level (Figure 3). The Second Assessment Report (SAR) [41] defined vulnerability based on internal system factors, such as sensitivity and adaptive capacity, and highlighted that the most vulnerable systems are those with a higher sensitivity to climate change and a lower adaptive capacity. It was also emphasized that developing countries exhibit greater vulnerability due to economic constraints that hinder the implementation of adaptation plans. The Third Assessment Report (TAR) [42] introduced exposure as an external factor of vulnerability. The Fourth Assessment Report (AR4) [43] reaffirmed and formalized this definition, clarifying that adaptation can reduce sensitivity to climate change while mitigation can decrease exposure, particularly its rate and extent.

A new risk framework was introduced in more recent reports [34,44], in which exposure (previously part of vulnerability in AR4 [43] shifted to the set of concepts that define risk, and vulnerability was redefined to focus on sensitivity and adaptive capacity [17]. The term “hazard” was introduced in AR5 [34] and risk was defined as the result of interactions between hazard, exposure, and vulnerability. The definitions in both AR4 [43] and AR5 [34] reveal that vulnerability and risk include both external and internal dimensions. In AR4 [43], exposure represented the external dimension, while sensitivity and adaptive capacity comprised the internal. In AR5 [34], hazard and exposure represent the external dimension, and vulnerability the internal [44]. Furthermore, AR6 [35] emphasized that vulnerability is not uniform and it disproportionately affects certain communities and regions that have historically contributed less to the problem, thus underlining the importance of considering it within the context of sustainable development and equity.

3.2. Geographical Distribution of Scientific Production

The historical evolution of publications provides an overview of how scientific and technical production has changed over time. There is a clear upward trend in the number of studies published during the analyzed period, with a notable increase in 2021 and 2022 that coincides with the release of the latest IPCC report. Regarding the geographical distribution (Figure 4), the publications selected for this review were carried out in Algeria, Brazil, China, Ecuador, Egypt, The United States, Kuwait, Ghana, Greece, Grenada, India, Iran, Italy, Malaysia, Mexico, Mozambique, Nigeria, Thailand, and Vietnam. Among these, India and China stand out as the countries with the highest level of production in recent years and these are followed by Italy, Egypt, Malaysia, and Vietnam.

3.3. Thematic Distribution by Climate Change Drivers and Impacts

Figure 5 illustrates how the reviewed studies address climate change drivers and their effects on coastal vulnerability. Studies were grouped into three analytical categories based on their focus: those analyzing climate change drivers, those analyzing manifested effects, and those that consider both factors integratively.

Among the analyzed studies, 15 focused specifically on vulnerability to drivers such as sea level rise, increased frequency and intensity of extreme storms, rising temperatures, and ocean surface warming. Sea level rise was the most prominent driver and this was prioritized in 10 studies. The most represented category concerns research that focus on climate change effects, with a total of 21. Within this category, flooding and coastal erosion were the most frequently analyzed effects, either individually or in combination. There is a clear tendency to assess vulnerability to flooding while other effects, such as drought, have hardly been considered, with only one study specifically addressing this aspect. This finding is noteworthy because in coastal tourism contexts both temperature increases and drought can significantly impact economic activity and local quality of life. Lastly, a third category includes seven studies that address vulnerability by simultaneously considering both drivers and the effects of climate change. Major differences in the analyzed variables were not observed within this group, although two publications did stand out as they combined vulnerability to extreme storms (driver), flooding (effect), and temperature rise (driver).

3.4. Terms Used in Vulnerability Indices and Their Frequency of Use

A detailed analysis of the types of indices used in the reviewed publications is provided in Figure 6 and this shows the frequency of each type of index. The methodological references on which their construction is based are shown in Figure 7 and a relationship can be established between the most cited authors and the indices derived from their methodologies.

Various types of indices are identified in Figure 6. The most used index is the CVI (Coastal Vulnerability Index), which was applied in 15 studies. CVI was originally proposed by Gornitz [19] and it has been widely adopted in the literature. While commonly referring to the “Coastal Vulnerability Index,” in some cases the CVI initialism has also been used for Cumulative Vulnerability Index or Integrated Coastal Vulnerability Index, depending on the author’s approach. The next most common index after the CVI is the Vulnerability Index (V), which appears in five studies and also has variations in its denomination. The CCVI (Climate Change Vulnerability Index) and ICVI (Integrated Coastal Vulnerability Index) each appear in three publications. Other indices, such as CoRI, FVI, SEVICA, HVI, and SoVI, amongst others, appear only once—an observation that reflects a high terminological diversity.

Based on this analysis, five main categories of indices were defined: CVI, CCVI, ICVI, V, and Others. To simplify the analysis, indices used only once were grouped under “Others.” Most of these indices are composite, i.e., they consist of several sub-indices ranging from relatively simple (e.g., CoRI, FVI, SEVICA) to more complex (e.g., CCVA, CFV, CVI, HVI, ICVI, SoVI), thus reflecting the evolution and customization level of the employed methodologies.

The authors used methodological references for the construction of indices and the frequency with which they were cited are represented in Figure 7. Based on the index categories defined in Figure 6, a correspondence was established between each author and the type of index developed based on their approaches.

The results of this analysis highlight the most influential theoretical frameworks in designing coastal vulnerability indices. Gornitz and Kanciruk [18], Gornitz [19], and Gornitz et al. [92] stand out as they were cited nine times for the development of CVI and once for CCVI. Thieler and Hammar-Klose [112] were also frequently used as a basis for constructing CCVI, CVI, and ICVI. Moreover, the 2007 and 2014 IPCC reports [34,43] were identified as methodological sources in three publications in which CCVI, V, and Other indexes were applied. The remaining authors appeared less frequently and were only cited once or twice. This analysis underscores not only the diversity of index types used but also the most influential theoretical and methodological sources in developing coastal vulnerability assessments.

3.5. Dimensions of Vulnerability

The studies on climate vulnerability included in this review mainly address three dimensions: physical, social, and economic. However, differences exist in how each dimension is treated.

The proportion of studies that subdivide the physical dimension into geomorphological and physical-dynamic subcategories is provided in Figure 8, along with the percentages of the research that address social and economic dimensions jointly or separately. This classification helps to identify methodological patterns and approaches in assessing coastal vulnerability to climate change.

The physical dimension is addressed collectively in most studies (74.4%). However, in 25.6% of the studies this aspect was divided into two subcategories: geomorphological and physical-dynamic. This classification can be linked to the exposure and hazard components defined in the IPCC conceptual frameworks, especially from AR5 [34] onwards, which distinguishes between internal factors (such as exposure) and external factors (such as hazards or climate threats). Although one might expect that this distinction would influence publications post-AR5, a clear trend indicating a generalized adoption of this classification in the physical dimension was not observed.

Regarding social and economic dimensions, significant differences were not found in their treatment: in 51.2% of the publications these were addressed jointly under the “socioeconomic” category, while in 48.8% they were considered separately. This variation relates to the methodological approaches adopted and the availability of specific data for each dimension.

In some research [45,49,54,58] the analysis was structured using the IPCC methodological framework components—exposure, sensitivity, and adaptive capacity—distributed among physical, social, and economic factors. In other publications [46,47,53,79] social and economic factors were grouped into a single socioeconomic dimension. Additionally, some authors [61] clearly differentiated physical factors into geomorphological categories (linked to exposure) and physical-dynamic categories (related to climate hazard).

3.6. Key Variables in Coastal Vulnerability Assessment: Categorization and Frequency of Use

The lack of standardization in the use of variables is one of the most evident aspects in an initial analysis. There is considerable variability in both the number of variables used in each study and their naming, particularly in the case of socioeconomic variables. This situation makes it complicated to establish a common baseline or make direct comparisons among publications.

In contrast to the above, physical variables show greater homogeneity in both number and naming. As previously mentioned, in some articles these variables are grouped under a single category, while in others they are divided into “geomorphological” and “physical-dynamic” categories. The most representative categories of physical variables or indicators are Geomorphology and physical characteristics, Hydrology, and Climate. The most common indicators (Figure 9) include slope, coastal geomorphology, elevation, distance from the shoreline, sea level rise, tidal range, significant wave height, storm frequency, shoreline change rate, and erosion. It is particularly interesting that many of these indicators were already present in early research, such as Gornitz [19], and have continued to be used with minimal modifications to the present day.

Regarding social variables (Figure 10), the most representative categories are Economic activities and livelihoods, Demography and population structure, and Socioeconomic conditions. The most commonly used variables in this dimension include population density, land use, road connectivity, educational level, and income level.

3.7. Weighting Methods and Tools for Data Processing and Visualization

The ways in which the weighting of variables or indicators used in climate vulnerability indices in the literature included in this review are shown in Figure 11a. In 41.9% of publications, differentiated weights were assigned and these give different relative importances to each variable depending on its relevance. In 32.6% of the studies uniform weighting was chosen, which assigns the same weight to all indicators. In 14% of the studies both approaches were combined, while in 11.6% weighting was not specified in the methodology.

Two of the tools used for weighting (Figure 11b) stand out: the Analytical Hierarchy Process (AHP), within the framework of multicriteria decision-making (MCDA) methods, and Principal Component Analysis (PCA) as a statistical technique. AHP is based on expert participation, where the importance of each variable is compared and evaluated through surveys or participatory meetings. PCA allows the identification of variables, explains the greatest variance and reduces the number of indicators to a more representative subset.

Publications in which AHP was applied commonly used surveys and sessions with key stakeholders or local experts to determine weights. While it is true that these tools can lead to differentiated weighting, in some cases they were also used to assign equal weights depending on the design of the study.

Geographic Information Systems (GIS) represent a cross-cutting tool used in the studies in this review. With one exception, GIS was used in all publications to visualize vulnerability spatially and locate the most exposed or sensitive areas. In some studies, this visualization was complemented with numerical models to dynamically represent certain components or with satellite imagery, which was especially used to measure indicators such as shoreline change. However, these latter tools are considered complementary since their use was not widespread. It is noteworthy that in nine publications classified as MCDA there was no clear indication as to which methodological tool was used for weighting variables and these were therefore not included in this detailed analysis.

3.8. Analysis of the Level of Integration of the Tourism Sector in Coastal Climate Vulnerability Assessments

The analysis reveals that in only five studies (11.6%) were the climate vulnerability assessments specifically focused on the tourism sector (Figure 12a), a finding that indicates low representation of this sector when compared to other areas analyzed. Among the physical indicators used in tourism-related publications, those related to coastal features such as slope, coastal geomorphology, elevation, and beach width are prominent. Furthermore, indicators like temperature, significant wave height, sea-level rise, humidity, wind speed, and changes in the coastline are also frequently employed. As for the socioeconomic indicators (Figure 12b), population density, the construction of coastal defenses, land use, tourist density, and tourist income are particularly notable, among others. These variables reflect key aspects of tourism activity.

3.9. Analysis of Study Scale and Its Relationship with Data Sources Used

Climate vulnerability indices can be applied at various geographic scales, from sub-municipal to global levels. A distinction is made in Figure 13a between the study scope—the general scale of the analyzed territory—and the unit of analysis, which refers to the specific spatial level where the index calculations are performed. Regarding scope, the most localized publications, such as sub-municipal, were scarce (5). Municipal-scale investigations represented the majority (16), followed by regional (14) and national (7). The continental scale was the least explored, with only one study identified.

However, when considering the unit of analysis, sub-municipal scales clearly predominate with 20 studies. This is followed by the municipal level (18 studies) and, to a lesser extent, regional (5). This indicates that there is a preference for conducting analyses at more detailed scales, even when the study scope covers larger territories. For example, in regional publications (14 in total), municipal-level (6) and sub-municipal-level (8) analyses were conducted. Similarly, in municipal-scope publications (16) the unit of analysis was both municipal (11) and sub-municipal (5).

This analysis cannot be dissociated from the types of data source used to construct and validate the indices (Figure 13b). In most cases (14 studies) a combination of open-access data and field data was used and this facilitates research alignment with management policies. In contrast, the exclusive use of internal data (1) or field data (1) may limit replicability and usefulness for public managers. Analysis of the relationship between analysis scale and data sources revealed the following: publications in which only open-access data (8) were used mainly applied the analyses at the sub-municipal level (6); those that combined open-access and field data (14) worked at both municipal (6) and sub-municipal (8) levels; studies in which a mix of open-access and internal data (10) was used focused primarily on municipal analysis (6); and, finally, the studies that incorporated open-access, internal, and field data (9) achieved greater detail, mostly by conducting sub-municipal analyses (5).

4. Discussion

The results outlined above show a significant evolution in the concept of vulnerability in IPCC reports, with a shift from an initial focus on physical impacts such as sea level rise [40] to a more complex definition that incorporates internal system factors like sensitivity and adaptive capacity, as well as external components like exposure [42,43] and hazard in the risk frameworks introduced in AR5 [34] and AR6 [35]. Nevertheless, a clear unified approach to this concept was not observed among the different publications. Authors such as Cutter and Finch [15] highlight the importance of focusing on internal characteristics that make certain groups more prone to impacts, especially in the contexts of inequality and uneven development. This perspective is consistent with the IPCC’s conceptual evolution, which emphasizes that vulnerability is not uniform and affects communities with lower adaptive capacity more intensely, many of which have contributed little to climate change.

While it’s recommended to adopt more recent frameworks on risk, where vulnerability is component, it’s pertinent to explore complementary approaches to enrich the analysis. A notable example is the one proposed by Balsas [115] in his study on fishing communities, where vulnerability is defined as a property of resilience. This approach doesn’t contradict IPCC definition; rather, it offers a more practical perspective. Instead of viewing vulnerability solely as a passive weakness that contributes to risk, this approach actively links it to a system’s capacity to resist change and recover from threats. In this way, it promotes a focus not only on identifying weaknesses (vulnerability) but also on the immediate formulation of recovery and transformation strategies (resilience). The work of Balsas [115] exemplifies this duality by identifying vulnerabilities in multiples dimensions, such as a dependence of a single economic sector, and, in turn, proposing specific resilience strategies like economic diversification.

In order to understand better the landscape of coastal vulnerability assessments, the geographical and temporal distributions of the literature were analyzed. A progressive increase in scientific production was observed, with a notable peak in 2021 and 2022, possibly linked to the publication of IPCC AR6 [35]. Geographically, study concentration is striking, with India and China emerging as main production centers, followed by Italy, Egypt, Malaysia, and Vietnam. However, the absence of studies from Spain is notable. Despite its extensive coastal zones and significant vulnerability to climate change, very few Spanish publications were found to focus strictly on coastal vulnerability assessment through indices. After applying inclusion and exclusion criteria there was no Spanish study that met the requirements to be included. This finding suggests either a possible gap in the literature or a different methodological approach in local research on this specific topic.

Regarding the main climate change approaches in the analyzed publications, thematic trends in vulnerability assessment were identified (drivers, effects, or both). Studies that were focused on effects predominate and these particularly address flooding and coastal erosion. However, it is noteworthy that effects such as drought have scarcely been considered, with only one study covering this topic in spite of its relevance in tourism contexts. As Olcina and Vera [116] note, reduced precipitation and the loss of climate comfort in southern and eastern Spain due to rising temperatures are key effects of global warming. This gap may indicate a need for more research on drought vulnerability in coastal tourism.

One of the challenges in assessing coastal vulnerability lies in the diversity of proposed index names and selected variables. One of the aims of this review was to identify patterns in index typology and terminology. While it is true that the Coastal Vulnerability Index (CVI) stands out as the most widely used (15 studies), this apparent predominance is nuanced by the notable terminological diversity observed. This indicates significant heterogeneity in index names and complexity, which can either be simple or composed of multiple sub-indices. This diversity aligns with the situation pointed out by several authors, who emphasized both the usefulness of these indices for decision-making [117] and the need to incorporate socioeconomic dimensions to achieve a more comprehensive view of coastal vulnerability [118,119,120].

Regarding the fundamental dimensions of climate vulnerability addressed in the literature (exposure, sensitivity, and adaptive capacity), the results reveal that although included, there is generally an absence of methodological consensus on their treatment. This lack of uniformity concerns authors like Kasthala et al. [26], who warn that omitting a dimension can lead to incomplete assessments and counterproductive decisions. For example, prioritizing infrastructure in socially vulnerable but environmentally valuable areas could result in inadequate policies that promote infrastructure development and, consequently, environmental degradation. Similarly, Preston and Jones [121] emphasize the need for a holistic approach in which different vulnerability dimensions are integrated into a single index or a limited set of indices to avoid partial perspectives and promote more balanced adaptation policies.

The analysis of indicators used in coastal vulnerability assessments reveals a clear lack of standardization and this makes it difficult to make comparisons between studies. This difference is particularly pronounced in the socioeconomic dimension, where the lack of consistency in variable selection and naming is considerable and compromises result homogeneity [30,111]. In contrast, physical indicators show greater homogeneity, with variables such as slope, geomorphology, elevation, sea level rise, tidal range, and shoreline change rate standing out. Such variables were already present in early works like Gornitz [19] and they are frequently used in CVI formulations [105]. Nevertheless, despite recent conceptualizations in which sensitivity and adaptive capacity are integrated, there is still no consensus on suitable indicators. As pointed out by Nguyen et al. [1], the applicability and choice of descriptors related to adaptive capacity remain less developed compared to exposure and sensitivity. This dispersion highlights the need for stronger frameworks for identifying and applying key variables in future analyses [28].

The analysis of tools and techniques used in vulnerability assessments reinforce the assertion of Nguyen et al. [1] that there is still no standardized methodological framework to quantify and compare vulnerability. The diversity of approaches is remarkable and they include multicriteria decision-making methods, numerical models, and spatial models with remote sensing. This diversity aligns with Nguyen et al. [1], who identified participatory and simulation-based approaches. Among these, multicriteria decision-making techniques stand out, with AHP and PCA as the main tools employed. Regarding weighting, there is a clear preference for differentiated weighting (41.9%), which suggests an effort to reflect more accurately the individual influence of each variable. Finally, the use of GIS was nearly unanimous, consistent with Charalampos and Vassilios [30], and this highlights its fundamental role in spatially visualizing vulnerability and integrating exposure, sensitivity, and adaptive capacity indicators. As stated by Malone and Engle [122], it is crucial to recognize that GIS variable aggregation can mask inherent uncertainties.

The limited incorporation of tourism in assessments (only 11.6%) contrasts markedly with the high concentration of tourist destinations in coastal areas. These destinations are increasingly threatened by climate change impacts despite the economic relevance of tourism in these regions. This highlights a clear opportunity for improvement in future research, especially in contexts where tourism is a central economic pillar.

The preference for conducting climate vulnerability analyses at sub-municipal scales responds to the need to more accurately capture territorial particularities and support more specific management decisions, as recommended by the IPCC [34] and various authors such as Kasthala et al. [26]. At these scales, applied indices achieve greater precision and effectiveness in reflecting territorial particularities and facilitating decision-making. While the ability to conduct assessments at local scales is closely tied to data availability, more detailed publications often combine open-access data with field-collected data to improve spatial resolution. In summary, to achieve a more comprehensive and detailed vulnerability analysis, combining these data types is ideal; however, as Kasthala et al. [26] and Rocha et al. [123] highlight, access to local data remains a key challenge for developing more accurate and useful assessments for adaptive planning.

In summary, this study represents an indirect analysis of the absence of an integrated and standardized index to assess climate change vulnerability in coastal areas. Despite the growing number of publications in this field, significant challenges and limitations persist in how climate vulnerability is conceptualized and measured. Assessing this vulnerability is crucial for the design of effective adaptation strategies, and indices have become widely used tools due to their apparent simplicity and ease of interpretation. This systematic review of 43 studies, all characterized by integrating internal factors such as sensitivity and adaptive capacity in their assessments, allowed us to examine the evolution of the vulnerability concept, the geographical distribution of productions, and the climate change factors of most concern to the scientific community. Moreover, inconsistencies were revealed in defining index terminology, considered dimensions (physical, social, economic), selection of variables or indicators, and the application of specific methodologies. The number of studies in which the tourism sector is considered was also evaluated, along with the most used scales and data sources. These divergences limit the possibility of comparing studies standardizing frameworks, and they also hinder the practical application of results in coastal management and decision-making. Ultimately, as Lima and Bonetti [124] point out, publications in which coastal population vulnerability was analyzed not only contribute scientific knowledge but can play a key role in formulating prevention and mitigation strategies. By guiding a manager’s decisions, these studies directly contribute to reducing social and economic risks in increasingly climate-threatened contexts.

5. Conclusions

In the context of territorial development, coastal ecosystems play an essential role but face increasing pressure from population growth, infrastructure expansion, and climate change impacts. Although these areas offer opportunities for tourism, well-established management plans to mitigate climate effects on these destinations do not exist. Despite the increase in the literature in which indices are used to assess coastal vulnerability in recent years, a lack of methodological standardization persists, and this limits result comparability and applicability for decision-makers.

In this review, a total of 43 studies were analyzed with the aim of assessing the evolution of conceptual approaches, identifying main thematic trends, most used indices, dimensions, and indicators, as well as the most common methodologies and scales. It was observed that, although the IPCC has updated its definition of vulnerability and includes it as a contribution to risk along with exposure and hazard, in many publications the earlier conceptual frameworks for vulnerability are still used. This finding highlights the need to move towards risk-centered approaches. Additionally, scientific production was especially concentrated in 2021 and 2022, with China and India being the most active countries. While temperature is relevant to tourism, studies are predominantly focused on climate change effects such as erosion and flooding, primarily using the Coastal Vulnerability Index (CVI). However, there is great variability in terminology and treatment of physical, social, and economic dimensions.

A lack of standardization in indicator selection was identified, and this particularly affects socioeconomic variables. In addition, there was a clear preference for differentiated weighting, with techniques such as AHP and PCA applied. GIS was widely used to represent vulnerability spatially. The low presence of the tourism sector in the analyzed studies is striking due to its economic importance in coastal areas. Only 11.6% of publications incorporated tourism-related variables and this clearly represents a research opportunity. Furthermore, it was confirmed that more detailed analysis scales, such as municipal and sub-municipal, allow a better understanding of territorial particularities, especially when open-access data are combined with field-collected information.

In conclusion, and following Lima and Bonetti [124], these studies can guide effective mitigation and prevention strategies and reduce social and economic risks. Therefore, it is proposed to develop a municipal-scale climate vulnerability index to serve as an intermediate tool between technical knowledge and decision-making, with tourism incorporated as a key axis to strengthen coastal resilience.