# Visualising the Relevance of Climate Change for Spatial Planning by the Example of Serbia
## 2 Data and Methods
### Research Design  
Visualisation methods have been part of extensive research because their application \"clarifies the complexity of the models [and]... creates an overview and transparency\" ([62] p. 1). Some researchers chose visualisation to increase the expressiveness and attractiveness of overall environmental issues [63; 64], urban planning, and carbon emissions [65], etc. In urban and spatial planning, visualisation has gone beyond its role as a tool for researchers and experts and has become a requirement in decision-making processes when addressing citizens and other stakeholders [31; 66] Therefore, the research design presented in this paper can have relevant applicability beyond this paper and the example of Serbia. For content analysis, the focus of this research dictated that one of the concepts and keywords to look for was \"climate change\". Based on this, we selected 38 keywords that were traced and observed in the context of climate change, i.e., in the form of a measure proclaimed by the analysed planning document. The keywords were selected based on climate change measures and concepts recognized in the previously conducted study by [PERSON] et al. [61]. In that study, citizens were asked to enumerate all the climate change measures they were familiar with. Since the nature of some enumerated measures does not pertain to the field of spatial planning (e.g., the selection of crop type, changes of field work schedules), we chose not to consider those measures in the selection of keywords and concepts. The list of 38 keywords (measures) is presented in Figure 1. To trace the selected keywords in the documents, we used the command \"find\" in digital versions of the analysed planning documents (Word or PDF files) and subsequently checked the context in which the keyword was used. If the context referred to climate change and represented a proclaimed measure, we considered it a positive result and used it in the next step of the analysis. In the next step, we used binary analysis and frequency grading. A matrix was created where spatial-planning documents intersect keywords. If the keyword was used in the document in the context of climate change measures, this was indicated with a \"1\"; if the keyword was not found, this was indicated with a \"0\". In our document analysis, the keywords we sought served as indicators, guiding us to specific sections within the documents. After identifying each keyword, we meticulously examined the context in which it was employed, assessing whether it pertained to climate change measures. This process not only allowed us to confirm climate-change-related content but also to scrutinize different sections of the text and potentially identify new keywords that enriched our analytical framework. Part of the matrix is shown in Table 2 as an example. Table 2 also illustrates that \"TOTAL\" represents the frequency of keywords throughout the analysed documents, not in terms of the frequency of occurrence in individual documents but the number of documents in which they appear. Figure 1 is the outcome and the first visual representation in the analysis. It shows the relevance of certain measures to spatial planningin Serbia in four categories, based on the number/percentage of plans in which measures occur in the climate change context. The next task was to simplify represent the results. To achieve that, we distributed the 38 keywords into categories, with each corresponding to a different climate change effect. The climate change effects we selected based on the relevant literature review e.g., [31; 67; 68; 69; 70; 71], typical for the territory of Serbia, are the following: drought, floods, hail/storms, heat waves, landslides, and premature snow melting. The distribution of keywords, hence, measures, is displayed in Table 3. Some keywords/measures were considered in several categories (e.g., 2--afforestation, 11--establishing new protection areas) since they influence multiple aspects, i.e., climate change effects.