A Methodological Tool to Integrate Theoretical Concepts in Climate Change Adaptation to Spatial Planning

Abstract

Climate change adaptation has become an important policy domain, as it has the potential to substantially reduce many of the adverse impacts of climate change. Several scientific terms and general concepts have been used to comprehend adaptation, including vulnerability, exposure, sensitivity, adaptability, and resilience. However, most of these concepts are often used in inconsistent ways and their relationship is to a large extent unclear. As a result, there is a lack of clear understanding of adaptation and its practical implementation in fields such as spatial planning, whose role in tackling climate change, especially through ecosystem approaches, is critical. This paper attempts to investigate the practical integration of adaptation in the context of spatial planning, specifically through Green Infrastructure (GI) planning. Applying a thematic analysis to 91 scientific and major policy documents, the main determinants of the critical concepts that relate to adaptation were identified, classified, and intertwined with key determinants of GI planning and design. The analysis led to the development of a methodological tool, named REAd GrIn. This model can be used to prepare and evaluate spatial plans and policies, which integrate the concepts of resilience, vulnerability, and adaptability to achieve adaptation through spatial planning.

1. Introduction

The pursuit of sustainability implies that cities should plan for a range of interdependent challenges (economic, social and environmental) which are increasingly complex and uncertain. Thus, cities have to address/adjust to adapt to many types of stresses and shocks, with climate change being one of them [1,2]. From an environmental point of view, the very nature of cities complicates and exacerbates this effort. This is due to the fact that existing development patterns, along with human activities and behaviors, are considered to be the main culprits of climate change. At the same time, cities themselves (both as natural and anthropogenic environments) are highly vulnerable to the effects of climate change and also drivers of innovation, which can help them withstand shocks and stresses. The realization that climate will continue to change and become less predictable, combined with the acceleration and inevitability, of climate change due to human activity, including urbanization, highlights the need to take measures to reduce risks and uncertainties. Thus, adaptation to climate change has become, alongside mitigation, an important policy domain, as well as a necessary strategy and measure of action (and often the only option) at all levels/scales of governance, up to the individual level [3,4,5,6,7,8,9,10,11,12,13].

From a spatial perspective, climate change has a range of spatial impacts that can influence future land use, and at the same time, spatial configurations contribute and are vulnerable to climate change. These observed vicious circles alter the context of spatial planning and also challenge our responses, policies and planning and thus our ability to maintain human well-being and healthy ecosystems [4,7,14,15,16,17,18]. The need for targeted policy interventions to address climate change (mitigation and adaptation), triggers the debate about improved institutions, regulatory mechanisms, governance reforms and/or reorganization of institutional frameworks that affect the patterns of the use of the various forms of capital [19,20]. However, this does not necessarily entail the shaping of an entirely new set of planning and decision-making tools. Considerations for these issues can be incorporated into existing planning systems and their tools [6]. It could be argued that the pursuit of climate change adaptation creates an opportunity and a motivation to challenge and re-examine ideas, policies, actions and dominant development paradigms at multiple levels of governance. By improving existing policies on climate variability, it is possible to meet current needs while at the same time addressing future problems/vulnerabilities, which are directly related to the goals of sustainable development [21,22,23].

Adaptation can incorporate a range of responses from short-term adjustments to long-term, deeper transformation [24,25]. Moreover, adaptation comes in a huge variety of forms and types, depending on various characteristics/attributes at multiple and interacting scales, which also determine the process of adaptation [22,26,27,28,29,30]. A set of factors (social, economic, environmental, technological, information, governance and management structures, etc.), influence the ability to undertake successful adaptations [6,13,16,20,22,27,28,29,31,32]. It is thus understood that there are no universally applicable adaptation policies or actions, since societies and cities differ, as well as the hazards they face and their urban form and structure. This also means that they face different challenges [4,22,27].

The observed complexity of different aspects, as they emerge from the review of the relevant literature, demonstrate that adaptation is a rather contested term for which there are different perceptions and interpretations, depending on the scientific discipline and the type of study/research. As a result, the lack of clear understanding of the concept is further intensified. The various definitions of adaptation are mainly variations on a common theme, with the concept of adjustment playing a major role [16,25,27,33,34]. It could be argued that adaptation is an on-going process and a continuous stream of activities, actions and decisions [6,28,29].

Several scientific terms and concepts have been used in order to understand adaptation to climate change, such as vulnerability, exposure, sensitivity, adaptability (or adaptive capacity), stability, robustness, resilience and flexibility [6]. For all these concepts many, often overlapped, definitions are used in various ways in many different scientific fields. While interrelated, the relationship among these concepts remains unclear, despite the wide recognition they have gained in recent years. The conceptual fuzziness, emerging from the inherent ambiguity of the terms, causes problems in their use, measurement and implementation. More importantly, this fuzziness complicates their integration in decision-making and planning, and their translation as functional and practical terms for cities governance [1,2,6,9,25,30,35,36,37,38,39,40].

Following the approach of a previous work of ours [41], in this paper adaptation is considered as an umbrella concept that encompasses the concepts of vulnerability, resilience and adaptability (which functions as a connecting link to the latter two), with sustainability being the ultimate goal.

Table 1. Definitions of the concept’s vulnerability, resilience, adaptability, and adaptation [41].

Concept	Definition
vulnerability	the degree to which a system is susceptible to, or unable to cope with, adverse effects of climate change; it has an external (exposure) and internal (sensitivity and adaptability) dimension
resilience	the ability of complex SES to change, adapt and transform in response to hazards including those associated with climate change; it is considered to be closely related with adaptability
adaptability	the ability or capacity of a system to adjust to climate change, to moderate potential damages, to take advantage of opportunities, or to cope with the consequences, by modifying/changing its characteristics or behaviour so as to cope better with existing or anticipated hazards; it is considered as requirement that enables adaptation and sustainability and serves as the link between vulnerability and resilience
adaptation	a process, action or outcome in a system in order to better cope with, manage or adjust to actual or expected changing conditions (stresses, hazards, risks), to moderate harm or exploit beneficial opportunities and so attain a desirable configuration and sustainability

provides the definitions of these concepts. Essentially, these concepts are perceived as distinct but connected to each other. Therefore, adaptation to climate change of a system (natural, human, social, economic, and socioecological) incorporates:

• the reduction of its vulnerability to real or expected effects of climate change,
• the maintenance and improvement/increase of its adaptability,
• the reduction of its exposure and sensitivity, combined to the above two objectives,
• the enhancement of its resilience to future uncertainties and potential risks,
• the enhancement of transformability, where and when necessary.

A large body of literature agrees that spatial planning and especially land use planning has a vital role to play in addressing climate change and particularly in achieving adaptation. Spatial planning can contribute to adaptation through its physical and organizational aspects. The physical aspect represents the material object of planning, focusing on space/land and it is shaped by natural and anthropogenic processes and relations. The organizational aspect reflects the cross-sectoral coordination of actors and actions/policies and the address and reconciliation of different needs, demands and interests of all stakeholders in a balanced manner [5,7,8,10,11,16,17,18,42,43]. Thus, planning tools can be used to reduce the exposure and vulnerability as well as to increase the resilience of cities at a range of climate change hazards and impacts [3,4,7,13,16,41,43,44,45].

In recent years, there has been a shift in spatial planning to more ecosystem-based approaches, integrating social-ecological interactions. The concept of Green Infrastructure (GI) has emerged as one of the most efficient and effective planning tools for adaptation to (and mitigation of) climate change. It has been also stated that GI enhances cities’ resilience and reduces their vulnerability to the effects of climate change, and overall enables adaptation to climate change and sustainability. The provision of the full range of GI benefits, in a cost-efficient way, requires an integrated planning and management approach, concerning both the physical and the organizational aspect of spatial planning [10,11,44,45,46,47,48].

The multiplicity of the concepts related to adaptation, along with their often ambiguous and elusive definition, supplements the already fuzzy nature of spatial planning. While their meaning may be politically accepted but their translation into practice is difficult remaining an open question. Thus, tools are needed in order to address differences in understanding, evaluate existing policies and also translate these notions/concepts into practice. The present paper attempts to clarify the relation between adaptation to climate change and its constituent concepts (vulnerability, resilience and adaptability), with spatial planning (through planning and design of GI). In doing so we identify the basic determinants of these concepts (Section 3). Based on this analysis, a methodological tool is formed (REAd GrIn) that can address the subjective nature of these fuzzy notions and concepts in planning. A pilot example is also presented to showcase the application of the tool in different spatial planning levels (Section 4). This tool aims to provide a framework for planners and decision-makers in order to use these fuzzy concepts in planning practice in a more consistent way.

2. Methodology

The main objective of the paper is to understand the relationship among the four key concepts, namely adaptation, resilience, vulnerability, adaptability (considered here as the link between vulnerability and resilience) and GI, by identifying their main common determinants within the relevant literature, essentially the broader patterns (themes) within a dataset. For this reason, a qualitative analysis of the dataset was chosen, and particularly the method of thematic analysis. The process was based on an abductive analysis, meaning that, even though the broader themes of the analysis were conceived to some extent, different codes were also allowed to emerge directly from the data and transform the themes, instead of forcing codes to fit in preexisting themes [49].

The thematic analysis was conducted based on the six-phased process proposed by Braun and Clarke [50], in a general dataset of 91 documents (scientific articles, books, reports and strategies) covering the period 2000–2020 (

Table 2. Dataset per type of document.

Type of Document	Number	References
Academic papers	59	[1,7,9,12,14,15,16,19,26,27,29,30,32,33,35,37,39,40,44,45,47,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88]
Academic books/Collective volumes	7	[13,20,89,90,91,92,93]
Reports	10	[22,28,31,42,94,95,96,97,98,99]
Strategies/Planning guides/Framework	15	[100,101,102,103,104,105,106,107,108,109,110,111,112,113]
Total	91

). The aim was to study a wide range of different documents (theoretical and practical), over a period of time, in order to explore the various aspects and understandings/interpretations of the key concepts as fully as possible. For each of the four key concepts, a thematic analysis was performed on a subset of 91 documents, focusing on the determinants, attributes and principles of each one.

Regarding the overall process of the analysis, first an extensive literature review was conducted where documents (dataset for each concept) were read and re-read and initial thoughts were noted down (phase 1). Due to the diversity of terms used to refer to the key concepts keyword-search analysis was not preferred, instead documents were read and analyzed by both the researchers/authors (researcher triangulation). Emphasis was given to the coding process and the formation of a coding framework, which led to the formation of initial overarching themes (phase 2 and 3). After regular meetings and debriefings, codes were finalized, and themes were reviewed and named (phase 4 and 5). The final phase involves the final analysis and write-up of a concise presentation and interpretation of the results.

In order to manage the large data sets, Excel spreadsheets and the Atlas program were used. This analysis led to the preparation of a wide variety of tables with codes and themes. This process facilitated the reviewing of data, references and codes/themes, while it clearly showed how each code/theme derived from the data (audit trail), enhancing, thus, the adequacy of the analysis. Some passages were coded more than once, depending on their meaning. Data ‘deviating’ from the theory were not ignored. Instead, they were coded to highlight inconsistencies of the theory as well as the ambiguity and complexity that characterize the key concepts and their relationships. Researcher triangulation and meetings ensured the credibility and reliability of the study. In the following section a detailed description of the codes and themes is presented followed by the analysis of the proposed methodological tool REAd GrIn (Resilience-vulnErability-Adaptability Green Infrastrusture), mainly with tables (along with the relevant references) and figures, so that transferability, along with trustworthiness and credibility, of the research can be enhanced [50,114].

It is worth noting that the aim of this analysis is to identify the determinants (the themes of the analysis) of each concept and then compare them. The relationships between the determinants were considered equivalent without being examined in greater detail. The aim of this thematic analysis was to highlight and compare the common determinants of the individual concepts, which lead to the objectives to reduce vulnerability and enhance resilience and adaptability of a system by better planning and designing GI. For example, the “participation” code was categorized under both the ‘social capital’ and ‘governance and planning system’ themes, depending on the context in which it is used. While it is evident that there is a correlation between the two codes, this was not analyzed. Furthermore, our purpose was not to confirm the theory (which was anticipated to some degree) but to elucidate the relationship between the key concepts by identifying their common determinants, which are either not obvious or not included (clearly) in the theory.

For each key concept its determinants (as they derive from the literature review), are listed in tables along with the relevant references. The set of themes and their relevant codes (which represent the determinants/principles), for each concept was divided into two domains, the main and the cross-cutting domain. The main domain includes the determinants that define the capacity of the system itself, its composition and components. The cross-cutting domain includes the set of determinants that affect the ones of the main domain and vary among the concepts. Finally, a comparison among the determinants was made, which, along with their identification, helped to address the problem/barrier of fuzziness and formulate a conceptual framework to understand their meaning and relationships.

3. Results: Classification of the Key Concepts Determinants

The findings of the thematic analysis for the key concepts are presented below.

3.1. Determinants of Vulnerability

To investigate the basic determinants of vulnerability 29 documents (dataset) covering the period from 2000 to 2018 were studied.

Table 3. Determinants of vulnerability (themes and main codes where necessary).

Determinants	References
main domain
economic capital [economic capital; income; economic growth; economic resources, assets, endowments; wealth; investment; insurance; debts; poverty; economic & income inequality; economic marginalization; financial instruments; GDP per capita; availability of economic capital; market dependency; food securities & entitlements; costs; funds; education & health expenditure; housing tenure; economic factors, drivers, forces, characteristics]	[7,12,13,16,20,22,26,27,28,30,31,33,51,52,53,54,55,56,57,89,94,100]
human capital [availability of human capital; knowledge; skills; education; experience; information; health; physical, mental, cognitive capacities; well-being; demography (demographic factors & drivers (age, gender, minority populations, migration status, racial and ethnic status)]	[7,12,16,20,22,26,28,30,31,52,55,56,57,58,59,60,89,94,95,100]
natural capital [availability, distribution of natural capital; natural resource; ecosystem conversion; sustaining natural capital; ecosystem damage, degradation; elimination of natural vegetation cover, deforestation; capacity of natural capital to provide multiple ecosystem services; biophysical drivers, indicators]	[20,22,26,28,37,55,56,57,58,89]
physical/built capital	[22,26,31,55]
social capital [social capital; availability, distribution of social capital; social resources; leadership; social networks; social relations; social institutions; bottom-up participatory approaches; collective/collaborative actions and processes, community engagement, partnerships; equity; inequality; marginalization; social factors, forces, drivers, characteristics; societal capacities; social support systems; societal capacities; cultural characteristics, factors, forces, dimension]	[7,12,16,20,22,26,27,28,30,31,33,37,51,55,56,57,59,61,89,94,95]
governance & planning system [governance systems; institutions; political power; access, participation to decision making, partnerships; integration; inclusivity; collaborative management; stakeholders engagement; communication; community planning; policies, legal frameworks; planning initiatives; land use planning; building regulations; political factors, forces, drivers, characteristics]	[7,20,22,27,28,30,31,33,37,51,55,56,57,60,61,94,95]
technology	[12,22,27,33,55,56,89,94]
cross-cutting domain
accessibility [to services, resources, capitals]	[7,12,22,31,55,89]
adaptability	[7,12,20,22,26,27,29,30,31,33,37,53,55,56,57,59,60,89,94,95]
diversity	[20,22,54,55,56,94]
exposure	[7,12,16,20,22,26,27,28,29,30,31,33,37,51,53,54,55,56,57,59,60,89,94,95]
geography/space-specific	[12,13,22,27,30,31,37,53,54,55,57,89,94,100]
hazard specific	[12,20,22,26,27,31,51,55,56,57,60,95]
resilience	[20,27,54,89]
sensitivity	[7,12,16,20,22,26,27,29,30,31,33,37,51,53,54,55,56,57,59,60,89,94,95]
slow variables	[20]
susceptibility	[7,12,16,22,29,30,31,56,60,94,95]

summarizes these determinants (themes and codes), which essentially represent characteristics and factors that constitute and/or affect vulnerability. In these specific concept terms, such as determinants, generic features, sources, factors, dimensions, and characteristics, were all considered to indicate the determinants affecting vulnerability and therefore were all classified as determinants by our study.

The determinants derived from the thematic analysis confirm the theoretical framework regarding the nature of vulnerability. As can be seen, the determinants concern both social vulnerability, i.e., factors related to the internal state and conditions/elements of the system (internal aspect of the concept, social or intrinsic), as well as dependence on climate changes, specific hazards and system’s exposure (external aspect, physical or biophysics).

The analysis reveals that vulnerability of a system depends on all forms of capital, with particular emphasis, compared to the other concepts, on economic capital. Regarding natural capital, it is stress that sustaining it (and providing multiple ecosystem services) helps to reduce vulnerability to hazards. It is worth mentioning that participation and collaboration (codes in the thematic analysis), belongs to social capital when they are a result of society’s actions (bottom-up initiatives), otherwise they are integrated in governance and planning system (while there are cases that are part of both determinants).

Regarding the cross-cutting domain, it is emphasized that vulnerability is a dynamic concept that changes over time and depends on the location and the hazard. Interestingly, some authors consider resilience as a determinant of vulnerability. This finding reinforces the conclusion that there is ambiguity in the relevance of the concepts and that their interpretation largely depends on the authors’ scientific background as well as the type and purpose of each study (subjective factors).

3.2. Determinants of Resilience

The dataset regarding resilience consisted of 35 documents, mainly articles in scientific journals and books, from 2002 to 2018. It is worth noting that, in comparison with the other concepts, there was more and much easier accessible material for resilience. This is, to some extent, indicative of the increasing popularity of the concept and the attention it receives. Several determinants that influence a systems’ resilience are listed in the relevant literature. The most important and documented ones are outlined in

Table 4. Determinants of resilience (themes and main codes where necessary).

Determinants/Attributes	References
main domain
economic capital [economic capital; economic activities; economic novelty; income equality, levels, stability, distribution; economic drivers, dynamics]	[20,58,62,63,90,91,94]
human capital [human capital; education; knowledge; learning; experimentation; information; creativity, innovation, novelty; research; awareness; memory; willingness to change; demographic change]	[1,13,20,32,35,39,40,45,58,62,63,64,65,66,67,68,69,90,91,92,93,94,96,101]
natural capital [natural capital; natural systems, assets; resource reserves; ecosystem services; ecosystem protection; biophysical legacies; ecological memory; spatial heterogeneity; ecological connectivity; environmental, ecological drivers and dynamics]	[9,13,20,62,63,64,68,69,91,92,96,101]
physical/built capital	[9,20,62]
social capital [social capital; social/multi-scale networks; trust; leadership; institutions; social organization; equity; cooperation, participation, collaboration, community engagement, partnership, civic involvement; social memory, social legacies; social learning; social cohesion; communication; social roles; social organization; social values; social values; social drivers, dynamics; culture]	[9,13,20,32,39,40,45,58,62,63,64,65,67,68,69,70,71,72,90,91,92,93,94,96,97,101]
governance & planning system [governance systems; institutions; political space for experimentation; stakeholder engagement; participation; partnership; collaboration; transdisciplinary; transparency; decentralization; openness; inclusivity; integration; iterative process; nestedness; cross-scale communication; recognition of complex systems; policies; structured scenarios; active adaptive management; foresight capacity; adaptive planning/design; ongoing, iterative, adaptive, proactive planning; long term plan]	[1,9,13,20,39,40,45,58,63,65,67,68,69,70,71,72,73,74,75,76,90,91,92,93,94,96,97,101]
technology	[58,90]
cross-cutting domain
accessibility [to resource, infrastructure, services, key functions]	[9,13,40,90]
adaptability	[9,13,20,39,40,58,65,70,71,75,90,97]
complex adaptive systems thinking	[20,45,67,69,93]
connectivity [connectivity; structural, functional, ecological; cultural, cross-scale connection; supportive linkages; multiscale networks; interconnections; interdependency; mobility, migration]	[13,20,45,62,63,65,67,69,70,74,75,76,77,90,93,94,96,97]
desirability	[32,39,72,96]
diversity [diversity; biodiversity; ecological, social, physical, economic, functional, cultural, landscape, response; of species, people, institutions, human opportunities, economic options; social, cultural, economic, spatial heterogeneity]	[1,9,13,20,32,40,45,58,62,63,64,65,67,68,69,70,71,74,75,76,77,91,92,93,94,96,97,101]
efficiency	[9,13,40,70,71,77,91]
feedbacks	[9,13,20,63,64,67,68,69,73,92,93,96,101]
flexibility	[1,9,13,39,40,65,66,70,75,90,94,97]
modularity	[13,63,64,65,68,69,74,75,76,77,91,92,96,97,101]
multifunctionality	[13,63,74,75,76,91,97]
persistence	[1,32,35,39,40,58,63,64,71,72,74,90,91,94,96]
recovery [robustness, stabilization, buffering, rapidity, reliability]	[9,13,39,40,70,75,97]
redundancy	[9,13,20,40,62,63,64,65,67,69,70,71,74,75,76,77,90,91,93,97]
self-organisation	[13,20,32,35,37,58,64,65,66,90,94,96]
self-reliance/autonomous	[40,70]
slow variables	[45,58,63,67,69,71,90,92,93,96]
transformability	[13,39,66,72,96]
variability	[65,90,92,96]

. Even though it is not an exhaustive list, it is apparent that a wide variety of determinants exists.

The main domain determinants of resilience consist of all forms of capital, governance and planning system and technology. Emphasis is given to governance and planning a system as well as to social capital. There are few references to physical/built capital as a main determinant of resilience, as it is the case with vulnerability. References to technology, as well as financial capital, are fewer for the concept of resilience, in relation to the concept of vulnerability.

Regarding the cross-cutting domain, the thematic analysis reveals that resilience consists of many different determinants representing its different types (engineering, ecological and evolutionary), which explains the simultaneous existence of seemingly contradictory determinants, such as stability, robustness, persistence and transformability. At a first glance, it could be argued that these contradictions create a chaotic situation, but they actually illustrate the various interpretations and ambiguities surrounding the meaning of the concept and that, in many cases, authors adopt their own approach (as in vulnerability). Even the large number of cross-cutting determinants indicates the dispersal of the concept.

It is also worth noting that some authors (around 10% of the literature examined) mention desirability as a determinant of resilience. Desirability mainly characterizes the concept of adaptability, which is always a positive concept. Its emergence as a determinant of resilience could be attributed to the evolution of the concept, and to the broadening of its definition in order to represent a ubiquitously positive concept. In the relevant literature, resilience can also have a negative aspect and is not always desirable. Therefore, the distinction between the concepts of adaptability and resilience becomes even more difficult [30,60].

3.3. Determinants of Adaptability

In order to identify the main determinants of adaptability, 35 documents (scientific articles and books, official reports) were analyzed, covering the period 2001–2018. The main determinants are outlined in

Table 5. Main determinants (themes and main codes where necessary) of resilience.

Determinants	References
main domain
economic capital [economic, financial capital; economic, financial resources; economic development; income (GDP per capita, insecurity, inequality); wealth economic/material, distribution; economic wellbeing; economic marginalization; financial instruments, insurance; fiscal incentives for risk management; economic ability; economic capacity]	[12,13,15,19,20,22,27,28,29,30,33,37,53,71,72,73,78,89,94,95,102,103]
human capital [human capital; human resources; education (formal, informal); learning; knowledge; information; skills; demography (age, class, gender, health); experience; experimentation; innovation; memory; perceptions; personal traits; personal security]	[12,13,14,15,19,20,22,27,28,29,30,32,33,35,40,42,53,64,66,71,72,73,78,89,90,94,95,102,103]
natural capital [natural capital (amount, diversity, access, control, mobilization); natural resources; ecological memory; environmental capacity; biophysical conditions]	[18,20,28,29,71,73,78,89,102,103]
physical/built capital	[13,15,19,20,22,27,29,30,39,71,72,73,78,89,94,95,102,103]
social capital [social capital; social capacity; networks (social, institutional, kinship, communication); social institutions; leadership; trust; equity; social institutions; social learning; flows (ideas, resources, information and knowledge); collective action; participation; commitment; interactions, negotiations, relationships; equity; class/social status; social memory; bridging organizations; social roles; social, institutional elements; social factors; societal characteristics; socio-cultural ability]	[12,15,19,20,22,27,28,29,30,32,33,37,39,42,53,58,71,72,73,78,89,90,92,94,95,96,102,103]
governance & planning system [governance structures; multi-level governance systems; forward-looking decision-making and governance; institutions; policies; land reforms; participation; cooperation; representation; engagement; interactions, negotiations; democratic decentralization; power structures; political capital, influence, legitimacy, factors, stability, will; entitlements; proactive planning; management capabilities; capacity to govern, to design and implement]	[12,13,15,19,20,22,27,28,29,30,33,39,42,53,58,71,72,78,89,90,94,95,102,103]
technology	[15,19,22,27,29,30,33,53,72,89,94,95,103]
cross-cutting domain
accessibility [to various types of capital; resources; infrastructure; social, institutional networks; information; opportunities; financial instruments; education; health services; supplies]	[13,19,22,27,42,71,89,94,102,103]
desirability	[19,20,30,32,71,72]
diversity [diversity; biological, economic, cultural; capitals; resource base; livelihood diversification]	[20,39,64,89,90,94,103]
efficiency, rapidity	[39]
feedbacks	[73]
flexibility	[35,39,40,72,94,103]
geography/space-specific	[22,27,28,29,53,94,102]
hazard specific	[22,27,29,94,102]
multifunctionality	[75]
persistence	[14,32,40,64,73,96]
redundancy	[75,103]
self-organisation	[20,64,73,90]

.

The thematic analysis demonstrates that adaptability, like vulnerability and resilience, is influenced by all forms of capital (and the mobilization of their resources), governance and planning system, and technology. The latter is mentioned to a much greater extent in the concept of adaptability than the two previously analyzed concepts of vulnerability and resilience. Great emphasis is placed on human and social capital and less on natural.

Regarding the cross-cutting domain, it is worth mentioning the determinants of persistence and desirability. The term persistence does not appear per se in the literature, however as a concept it exists within definitions that link adaptability with the development along a current trajectory or the maintenance of the system’s crucial functions and structure, factors that are directly related to the definitions of engineering and ecological resilience. Desirability represents the ability of a system to exist/move to more desirable states after disturbances, internal or external, either by responding to and absorbing the disturbance and maintaining its general function, structure and characteristics or by transforming it. Thus, desirability integrates both the determinants of persistence (change into a new state or alternative regime within the same stability domain) and transformability. Therefore, for this determinant, all the references directly mentioning the word desirability, as well as those stating that adaptability contribute to either maintain or change the system, were listed/recorded.

The thematic analysis of the concepts of vulnerability and resilience indicated that adaptability is one of their determinants. At the same time, the thematic analysis for the concept of adaptability reveals that all the determinants that influence adaptability are largely identified with either vulnerability, resilience or both concepts. Thus, the analysis confirms the relevant theory, as adaptability is considered the connecting link to vulnerability and resilience and by many it is defined as the ability of the actors of a system to influence and manage resilience [36,71,92].

3.4. Determinants of GI Planning

The thematic analysis for GI was conducted in 27 documents (scientific articles and books, plans, and policies/strategies), which cover the period 2002–2020 and concern various spatial scales and places. In the analysis regarding GI principles, an attempt was made to cover a wide range of sources (spatially and temporally) to highlight the evolution of the concept over time and to include in the analysis the different approaches to the concept and the principles in different areas. It is worth noting that, a large part of the relevant literature concerns the steps and procedures/process in the creation of GI and not so much the planning principles (there was essentially a greater degree of difficulty in finding documents compared to the other concepts), which may derive from the ambiguity of the concept, as various disciplines have adopted it focusing on different GI functions and benefits and so different conceptual meanings exist.

The key principles of GI planning, as they emerged from the analysis of the documents, are outlined in

Table 6. Determinants of GI planning (themes and main codes where necessary).

Determinants	References
main domain
economic capital [primary public investment; investments; funding; creation, maintenance, management; properly resourced; similar position to grey infrastructure investment]	[79,80,98,100,104,105,106,107,115]
human capital [learning; knowledge; information; health; wellbeing]	[45,80,105,107]
natural capital [ecosystems services; natural resources; natural processes; protection; preservation, conservation; affordability; ecosystem-based approach; holistic, comprehensive, integrated approach; GI assets (i.e., habitats, woodlands, waterways, natural/environmental systems, green spaces)]	[44,45,47,79,80,81,82,98,100,104,105,106,107,108,109,110]
physical/built capital [grey/green GI assets (e.g., cycleways, green roofs, sustainable drainage systems); green-grey integration, continuum]	[82,83,106,107,108,111]
social capital [collaboration (inter-& transdisciplinarity); community, diverse stakeholder involvement; end-user participation; social inclusion; equality; partnership; participation; interactions; linkages (between people and people with nature); historic environment]	[44,45,47,79,80,82,98,100,104,105,107,108,109,111,112,115]
governance & planning system [multi-level governance; holistic, comprehensive, integrated, multi-scale, collaborative, proactive, multi-scale, multi-phase, detailed planning; planning; integration; coordination; cross-boundary strategies and cooperation; inter-& transdisciplinarity; multi-scale, participatory, partnership, collaborative, strategic, long-term, evidence-based, sound science approach; community involvement; social inclusion; embed in statutory planning systems]	[44,45,47,79,80,82,83,84,85,86,87,88,98,99,100,104,105,106,107,108,109,110,111,112,113,115,116]
cross-cutting domain
accessibility	[88,105,106,107,108,111,112]
connectivity/multiscale networks [connectivity/connections (spatial, physical, functional, structural, ecological, ecosystem, landscape, administrative, for humans); networks (integrated, ecological, green); linkage; corridors; greenways, waterways; mobility]	[44,45,47,79,80,81,82,83,84,85,86,87,88,98,99,100,104,105,106,107,108,109,110,111,112,113,115,116]
diversity [diversity; biodiversity; multi-object approach]	[44,45,80,82,83,85,87,98,105,106,107,108,110,111,112,113]
flexibility	[113]
identity/local distinctiveness	[80,87,98,105,106,110]
multifunctionality	[44,45,47,80,81,82,83,84,85,86,87,88,98,99,104,105,106,107,108,109,110,111,112,113,116]

. In this way, it is possible to compare the determinants of GI planning with the ones of vulnerability, resilience and adaptability. Essentially, the aim is to identify the common determinants of the four concepts and the way in which GI planning can incorporate the other concepts with a view to achieving climate change adaptation.

As becomes apparent from Table 6, GI planning also depends on and is affected by all forms of capital (and the mobilization of their resources) and the planning and governance system. Regarding physical/built capital (grey infrastructure), references are mostly focused on the urban level and the green-grey integration (natural and more anthropogenic assets), e.g., cycleways and green roofs. Additionally, assets of physical/built capital are related with other planning principles of GI, such as connectivity, mobility, diversity or biodiversity. While technology is not explicitly mentioned in the design principles, it is directly related to the GI since several GI assets, e.g., green roofs, vertical gardens, walking and cycling routes, are directly related to technological developments and are constantly being improved through them.

GI planning principles focus on a small number of cross-cutting determinants, compared to the other concepts, with multifunctionality and connectivity being the most prominent. These two principles/determinants actually represent the basic core of the GI concept. It is worth mentioning that, in many documents, the concept of multifunctionality is interpreted as the provision of multiple benefits. In our study, we consider it as the provision of many functions from the GI assets. Diversity is another key principle/determinant of GI, referring to both biodiversity and a multi-object approach in the sense of incorporating many different types of GI assets.

4. Discussion: Building the REAd GrIn Methodological Tool

The thematic analysis of the four key concepts (vulnerability, resilience, adaptability and GI) revealed the determinants of each of them. This process helps to clarify each concept and the relationship among them. At the same time, it reveals the points of confusion and the overlaps that arise mainly due to the interpretation that each researcher/author attributes to them mainly because of their different perspectives and scientific background. It also enables their comparison, through which their common determinants (that contribute to climate change adaptation) can be identified. The elucidation of the concepts may be more important for theory, but from the perspective of achieving adaptation in practice, it is much more important to identify the determinants that affect the four concepts and essentially contribute to adaptation (Section 4.1). Based on these common determinants and with inputs from the theoretical framework, it is possible to create/build a planning and evaluation tool, the REAd GrIn (Section 4.2). Along with a discussion of the components of the REAd GrIn tool, i.e., the common determinants, we also present a pilot example to showcase the application of the proposed toll in different spatial planning levels. More specifically we discuss how two important documents of the Irish spatial planning system (a mature planning system with emphasis on land use planning) handle the common determinants of the concepts discussed here. The documents we examined are the National Planning Framework (NPF) [117] (national level spatial planning) and the Dublin City Development Plan (DCDP) 2016–2022 [118] (urban level spatial planning).

4.1. Common Determinants

The findings from the comparison of Table 3, Table 4 and Table 5 confirm and enhance, to a large extent, the theoretical framework of vulnerability, resilience and adaptability. The comparison clearly demonstrates that the concepts are interrelated and that adaptability is not only part of vulnerability and resilience but also the link between them, as all of its determinants coincide with either one or both of the other concepts. These results were to a certain degree expected, as the determinants that increase adaptability are considered to be the ones that also increase resilience and reduce vulnerability [29,33,94].

However, the main contribution of the thematic analysis was not to confirm the theory but to reveal the common determinants these concepts share, clarifying in part their relationship. Of course, the results of the comparison also reflect the ambiguity of these concepts, since their definitions and characteristics are in many cases conflated [9,29,33,61,94,103]. Greater confusion and overlap are observed between the concepts of adaptability and resilience, as they have several common determinants that make it difficult to distinguish them and often lead to being used as synonyms. Based on the analysis carried out, it appears that there are mainly three determinants causing confusion, namely persistence, transformability and desirability.

As was mentioned before, persistence does not appear per se in the literature of adaptability, but it emerges through its definitions, which resembles the ones of engineering and ecological resilience. The same applies to transformability, as the literature review shows that adaptability facilitates transformation, but it is not mentioned as its actual determinant. In contrast to resilience, where some authors, especially those relating to socio-ecological or evolutionary resilience, refer to transformability as a key determinant of resilience. Both persistence, to some extent, and transformability, almost entirely, are linked to adaptability through the characteristic of desirability.

The confusion between the two concepts is attributed partly to the evolution of the concept of resilience to become a ubiquitously positive concept as adaptability [24,30], and a process instead of a system’s fixed asset. The latter is mainly the case with the original concept of resilience, namely engineering resilience. Resilience may not be a desirable condition. For this reason, it can be argued that desirability is primarily a determinant of adaptability and not of resilience. In the evolutionary approach (and partly the ecological) to resilience, both resilience and adaptability are considered as a continually evolving/changing process, which increases up to a certain point and then decreases and rebuilds [6,14,30,35,36,65,71,90,94,119,120]. Both concepts are related to the dynamics of a system. Their main difference lies in the fact that resilience indicates a system’s structural characteristics and settings while adaptability the ability of the system to react to changing conditions as well as the ability of a socio-ecological system to influence and manage resilience for the achievement of a desirable outcome [36,60,92,96]. Therefore, adaptability emphasizes the successful response to changes and variations (adjust, address, prepare, restrict, reduce and/or utilize, as referred to in the general definitions of the concept).

A comparison among the four key concepts (Table 3, Table 4, Table 5 and Table 6) reveals that, apart from the determinant “identity/local distinctiveness”, all the documented GI determinants are in line with those that enhance resilience and adaptability while reducing vulnerability (Figure 1). This comparison also highlights that all the concepts are influenced by all forms of capital along with the system of governance and planning, although only in the theory of adaptability are there direct mentions. Regarding the cross-cutting domain, accessibility and diversity emerge as common determinants of all the concepts. Flexibility and multifunctionality in GI planning appears to enhance resilience and adaptability while connectivity is only correlated with resilience and GI planning.

4.2. The REAd GrIn Tool

Based on the findings of the thematic analyses and their comparison, presented above, with inputs from the theoretical framework, we propose a methodological tool that can also serve as an evaluation tool, named REAd GrIn (Figure 2). In essence, REAd GrIn specifies and translates the common determinants into simpler and more practical ones. The tool can be applied to the analysis and evaluation of different spatial planning frameworks (ex. strategies, policies, and plans) regarding the integration of vulnerability, adaptability, resilience and GI planning (i.e., integration of their common determinants) aiming at adaptation to climate change. At the same time, it can contribute to the clarification of the concepts in terms of their practical application, putting emphasis on physical planning, especially for local authorities, decision-makers and planners in order to guide them in the planning process.

REAd GrIn essentially demonstrates the most important determinants of the concepts for spatial planning and what planning can do to achieve adaptation (and ultimately sustainable development) through GI and based on the concepts of vulnerability, resilience and adaptability. In other words, how all these concepts are integrated and applied in planning and mainly with what actions and policies this can be achieved through existing plans and their future revisions or in the drafting of new ones. It outlines, therefore, the determinants that should be included in plans and strategies/policies in order to incorporate the concepts of resilience, vulnerability and adaptability in order to achieve adaptation to climate change through GI.

The concept of vulnerability and specifically its reduction is explored from both its external and internal dimension, through the concepts that compose it, namely exposure, sensitivity and adaptability. The incorporation of the concept of exposure in planning documents can be investigated by whether they recognize hazards and risks related to climate change. For example, regarding urban planning and compact cities, it could be explored if the planning documents acknowledge the primary effects of climate change, which are urban heating (increased temperatures, urban heat island) and floods [due to heavy rainfall (flash floods), rising sea and/or river levels or their combination], as hazards and risks. The analysis of the examined planning documents from the Irish planning system showed that they incorporate the need to address climate change, both in terms of adaptation and mitigation. In both plans, particular emphasis is given to the increased flood risk, due to rising sea levels and more frequent and sustained rainfall events. DCDP also mentions the increased mean annual surface air temperature. More importantly, both plans recognize the spatial planning process as an established means to implement and integrate climate change adaptation.

Sensitivity is considered to be an inherent property of systems that depend on their characteristics and properties [38,60]. At the same time, it is recognized that sensitivity of systems is strongly correlated with natural capital [20,94,121]. Therefore, to assess the extent to which a planning document promotes (directly or indirectly) the reduction of vulnerability of an urban system (including inhabitants), the factor of whether it takes into account the conservation, protection, enhancement, creation and in general the proper management of natural capital, essentially of GI assets, could be explored. The management of GI assets is considered in relation to the risks/hazards, threats and/or effects of climate change. Thus, it could be studied if documents include guidelines and actions for adaptation to climate change through the management of GI assets.

It is worth noting that GI assets can also contribute to the reduction of exposure of (urban) systems to hazards, for example the increase in green spaces may reduce exposure to the effect of urban heat island [121]. However, to avoid any confusion, in this tool it is considered that the management of natural capital, and in particular, of GI assets represents better the concept of sensitivity. GI assets themselves are sensitive to the effects of climate change, which also affects the sensitivity of spatial units and should be taken into account. A typical example is green spaces that can tackle urban heat island in urban areas (the more spaces a city has the less sensitive it is to this phenomenon), but at the same time there is the possibility of increasing the sensitivity of the system to the effects of drought and water scarcity [121].

Taking again the examined plans from the Irish planning system, NPF promotes the protection, preservation, and enhancement of natural capital through, among other things, GI planning. However, the proposed actions and policies are not always associated with climate change, but with other aspects such as economic ones. GI planning is associated with climate change mainly at the local level. Specifically, the creation of green spaces and parks to enable better management of urban micro-climates, is promoted as part of what is called in the plan “green adaptation” (meaning using ecological properties to enhance the resilience of human and natural systems in the face of climate change). Sustainable water management solutions (such as Sustainable Urban Drainage Systems (SUDS) and green roofs) are also supported. In addition, protection and enhancement of GI assets, namely forests, peatlands and permanent grasslands, are promoted as carbon pools.

DCDP refers to the creation, enhancement, and protection of GI and its assets in the context of spatial planning, mainly in relation to the risk of flooding but also mitigation. With the aim of retaining water and reducing surface water runoff (thereby reducing the risk of flooding), it promotes the creation of linear parks/corridors along rivers/canals, the preservation of natural river banks, the protection of the coastline and waterways, the development of pocket parks or areas of public facilities. For the same purpose it encourages the creation and use of SUDS, such as green roofs, swales, detention basins, ponds and wetlands, especially in new developments, but also the combination of the aforementioned assets. The creation and/or enhancement of riparian buffer zones is also recommended to enhance flood management. It becomes obvious that both plans incorporate the determinant of diversity, as they promote the enhancement/protection or creation of different GI assets with the aim of adapting to climate change even if this is not explicitly stated.

Multifunctionality, is assessed through the promotion/enhancement of different functions and activities that the various GI assets host. At the same time, it should be assessed whether the documents refer to multiple benefits, goods and services that GI assets can provide. In our pilot example, both plans recognize the multiple benefits that the various assets of GI can provide, with mitigation and adaptation to climate change among them. However, DCDP incorporates the determinant of multifunctionality in much greater extent. For example, for open spaces it is explicitly stated that it is the Dublin City Council’s policy to enhance the provision of multiple functions, such as biodiversity enhancement, urban drainage, flood management, outdoor recreation, and carbon sequestration. Similarly, the creation and enhancement of riparian buffer zones is promoted, to preserve/create habitats, improve water quality (filter pollutants and sediments from surface runoff), provide recreation and enhance flood management. On the contrary, in NPF, the use of green belts and green spaces for community recreation and amenity purposes is recognized, but without promoting or proposing specific actions, while no correlation with climate change is recorded. In the context of its national policy objective regarding the enhancement of the conservation status and improvement of the management of protected areas, it also proposes that development within Natura 2000 sites should facilitate sustainable activities. Such an objective may intensify the multifunctionality of these GI assets but in this case also no correlation with climate change is recorded.

Accessibility concerns both the easy access to GI assets by all potential users and by all modes and the layout of spaces/assets (streets, pedestrian paths, squares etc.), in relation to climate change. Both examined plans incorporate the specific determinant but there is no direct correlation with the primary effects of climate change. Certain indirect correlations are recorded. For instance, NPF promotes access to trails networks, which should be designed and delivered with a strong emphasis on protection and preservation of fragile environments. Respectively, DCDP proposes the improvement of pedestrian and cycle access routes to strategic level amenities, while ensuring that ecosystem functions are not compromised and existing biodiversity is protected and enhanced. Additionally, it promotes access through walkways, cycleways and other compatible recreational uses, along watercourses, while protecting and improving the latter’s natural character.

Connectivity, which strengthens the resilience of systems and is a key concept of GI, can be examined considering whether the planning documents promote the connection (physical, ecological) of GI assets (e.g., physical connectivity, corridors, paths/walkways, cycleways, and ecological connection) with regard to climate change. Connectivity should be considered at all spatial scales (multi-scale networks), as GI is by definition a connected multi-scale network of assets. DCDP incorporates the determinant of connectivity to a greater extent. Connectivity through GI planning is largely related to flood risk management. For example, in case a proposed development adjoins a river or canal bank, this plan proposes that the area adjacent to the waterway to be retained as a linear park or walkway, with linkages into the wider open space network. In NPF, the correlation between connectivity and climate change is only indirect. For instance, it is stated that development of a strategic national network of greenways, blueways and peatways will support, among others, the protection and promotion of natural assets and biodiversity.

Flexibility concerns both physical planning as well as its governance. From a physical planning aspect, it can be assessed through provisions concerning flexible design and location of GI, particularly within a coherent/compact urban fabric. From the governance aspect, it concerns the openness and flexibility to change of the examined plan, especially in relation to GI and climate change. Flexibility in DCDP is largely related to housing and the use/design of buildings. Among others, it is stated that the city council should continue to revise design criteria for the management of urban run-off to address increasing water levels and weather events. The concept of flexibility is mentioned in NPF but without any correlation with climate change and/or GI.

In addition to the dimension of physical planning, the tool also incorporates the dimension of institutions and governance. Multi-level governance could be examined through provisions regarding vertical and horizontal dimensions of governance. It therefore concerns, whether and to what extent higher and lower levels of stakeholders/partners and agencies contribute to the planning process and the implementation of projects and actions related to GI for adaptation. In the NPF, there is a correlation of the characteristic of multi-level governance, in terms of cooperation and participation, with GI (e.g., cross-border cooperation for the development of blueways and greenways) but not with the primary effects of climate change. DCDP promotes cooperation regarding climate change (e.g., coordinated response and cooperation between public bodies to manage and deal with flood risk) and GI (e.g., participation/consultation in the development of river walks and cycleways), but there is not a correlation between them, i.e., cooperation and participation is not encouraged for adaptation through GI.

The determinant of learning/knowledge could be examined through references to learning from other regions/cities/agencies (e.g., good practices), the integration/use, production, dissemination and transfer of local and scientific knowledge, but also the information, awareness-raising, education of the public, stakeholders and in general those involved. Learning and knowledge in the REAd GrIn tool focus on climate change and GI assets (either in terms of their benefits or their implementation/design), particularly on their correlation and their spatial dimension. NPF incorporates the determinant of learning/knowledge but there is not any correlation with climate change and/or GI. Regarding GI, as one of the ways to protect and improve the management of protected areas, continuous research and monitoring of habitats is proposed, but without correlation with climate change. Respectively, regarding climate change, it incorporates objectives such as improving understanding of flood risk and ensuring best practice for flood risk management without any mention to GI. DCDP incorporates the determinant to a greater extent, but still the mentions are quite general and indirect. For example, one of its policies concerns the promotion of learning and awareness of children and young people through green initiatives and biodiversity projects, which in some cases take place on GI assets.

The last determinant concerns funding of and investments on projects for the conservation, protection, enhancement/creation and general management of GI, in relation to climate change. In our pilot example, both plans incorporate the determinant but there is no mention of funding/investment in GI assets to address climate change.

Figure 3 illustrates the evaluation of the determinants’ integration in the examined plans.

5. Conclusions

The general topic of this paper revolves around the widely, nowadays, used but vague concepts of vulnerability, resilience and adaptability in relation to planning. The main objective is to understand and interpret the fuzzy character of these concepts through the lens of spatial planning, as well as how these concepts can be translated into specific policies and measures.

Given that vulnerability, resilience and adaptability cannot be implemented as such since they rather represent a way of looking at policy-making and spatial planning, a thematic analysis was performed taking into account the different understandings and perceptions of the concepts. The findings demonstrate the complexity and fuzziness of these concepts (which was to some extent expected based on the literature review) and that there are links among them as well as with spatial planning. However, the main goal of the thematic analysis was not to confirm the theory but to clarify and identify these links, namely their determinants, so that they can be translated into planning practice.

The research highlights that the practical integration of adaptation to climate change in spatial planning is not an easy process. Nevertheless, its integration through specific planning tools, such as GI, could be a relatively manageable and potentially a more comprehensible way in planning practice. This was attempted through the creation of a methodological tool, REAd GrIn, which is based on the common determinants of vulnerability, resilience, adaptability and GI planning and design. REAd GrIn provides a way of thinking in order to evaluate and modify strategies/plans, and also to facilitate decision-makers to practically applying these complex, fuzzy concepts (planning and evaluation tool). Moreover, it is structured in such a way that it can be implemented for any strategy/plan, from national to local level, and geographic area as well as adjusted to specific requirements (i.e., exposure to some other climate change related hazard).

The REAd GrIn tool can operate as a guide indicating the necessary individual steps to integrate climate change adaptation through GI into plans and policies. A first step would be to identify, current and future, climate risks/hazards (determinant of exposure). A second step is to identify the GI assets and to propose the creation of new ones to address climate change as well as the maintenance of existing ones (determinant of sensitivity). The next step concerns the measures and directions to be taken for the diversity of GI assets (public and/or private), their interconnection and accessibility and also flexibility of their planning and design. A final step concerns the governance aspects that should be taken into account, such as participation and cooperation, various forms of integration and production of knowledge and learning, and financing. Essentially, the REAd GrIn tool should be considered as a framework of principles for formulating new and/or evaluating/modifying existing spatial plans.

The tool approaches the concept of adaptation from the perspective of institutional practice in spatial planning. Thus, the various determinants were examined in terms of what a spatial strategy or plan can define in order to achieve adaptation. Therefore, in this paper the system of focus to which the proposed tool is applied is the spatial planning system. Besides, spatial planning itself can be understood as a complex system, involving a multitude of different stakeholders and different types of institutions, all interconnected in time and space, in many cases hierarchically. The proposed tool features both specific and more general aspects of the concepts, given the multiple and multidimensional issues managed/affected by a spatial plan, at any scale.

This paper highlighted the need for adaptation theory to be translated into the practice of spatial planning and indicated a way that this can be achieved. The intention was not to define a single, optimal planning approach and feature spatial planning as a panacea for solving climate change adaptation issues. It rather demonstrates the need for specific methodological tools that provide manageable ways on how spatial plans can be prepared and revised. Our attempt in this paper suggests that tools and concepts, however abstract and difficult to integrate into planning may be considered, can contribute to managing and addressing complex, interrelated problems and crises. In this way such methodological tools operate as planning and evaluation tools that can help to reduce uncertainty by providing a proactive as well as a transformative dimension to planning. Thus, the paper essentially contributes to the debate regarding how we can link theory and practice, rather than providing definitive answers to this complex issue.