Green capital East of the Leitha? The chances and disadvantages of major cities in the Pannonian Basin to win the European Green Capital Award 287Schmeller, D. and Pirisi, G. Hungarian Geographical Bulletin 72 (2023) (3) 287–309.DOI: 10.15201/hungeobull.72.3.5 Hungarian Geographical Bulletin 72 2023 (3) 287–309. Introduction Adapting to climate change and mitigating its potential negative impacts will become an increasingly important task for Euro- pean cities, where nearly 80 percent of the population will be urban by 2050 (Hardi, T. et al. 2014; Clark, G. et al. 2019). The pur- suit of environmental and social resilience and municipal sustainability is becoming increasingly popular among cities (Anders- son, I. 2016; Nzimande, N.P. and Fabula, Sz. 2020; Buzási, A. et al. 2022). This may include, among others, the need to respond to vari- ous external impacts (e.g., natural disasters, extreme weather events), transforming water and waste management at municipal level (e.g., rainwater retention, recycling), reduc- ing air and noise pollution, increasing the number and size of green spaces, or boost- ing the commitment towards sustainability. However, there are differences between the cities of Western and Eastern Europe about the perception and evaluation of the chal- langes of sustainability and climate change. They are reflected by differences in goals, priorities, and structures that appear in European urban development. In former state-socialist countries, territorial and ur- ban development was determined by the state, resulting in limited autonomy for local stakeholders. Urban planning and develop- ment were centrally directed and controlled (‘top-down’), as noted by Kovács, Z. (1999), 1 Doctoral School of Earth Sciences, University of Pécs. Ifjúság útja 6. H-7624 Pécs, Hungary. E-mail: dalma.schmeller@gmail.com 2 Department of Human Geography and Urban Studies, University of Pécs. Ifjúság útja 6. H-7624 Pécs, Hungary. E-mail: pirisig@gamma.ttk.pte.hu Green capital East of the Leitha? The chances and disadvantages of major cities in the Pannonian Basin to win the European Green Capital Award Dalma SCHMELLER 1 and Gábor PIRISI 2 Abstract This study focuses on the chances of major cities (over 100,000 inhabitants) in the Pannonian Basin to win the European Green Capital Award. The 28 cities covered by the analysis can be divided into two groups: eleven cities that have already applied (one of them, Ljubljana was a previous winner) and seventeen cities that have not yet applied for the award. During the research, we divided the cities according to these two groups. In the study we applied various statistical and spatial analysis methods to capture similarities and differences in their environmental indicators. The results show that there are no significant differences in environmental indices between these two groups, and the values of the 2016 winner city (Ljubljana) are most similar to Austrian, Slovenian, and Croatian cities. Furthermore, based on the results of the similarity search, it can be stated that the further east we go, the less similar the examined cities are to Ljubljana. We also examined the probability of reaching the finals, indicating that cities that have not yet applied have a low likelihood of winning the award. Keywords: European Green Capital Award, green cities, environmental indicators, sustainable urban devel- opment, Pannonian Basin Received May 2023, accepted September 2023. Schmeller, D. and Pirisi, G. Hungarian Geographical Bulletin 72 (2023) (3) 287–309.288 Sailer-Fliege, U. (1999), Szirmai, V. (2004), and Konecka-Szydłowska, B. et al. (2018). In contrast, Western Europe saw the emergence of new urban functions in former industrial areas after deindustrialisation, with a sig- nificant focus on brownfield rehabilitation (Dannert, É. 2016). In Western European cit- ies local communities play a crucial role in the urban development process, partly due to varying levels of co-financing and a limit- ed role of the central state (Barta, Gy. 2009; Puczkó, L. and Jószai, A. 2015). Following the transition to democracy, many post-so- cialist cities struggled with the shift to a ‘bottom-up’ planning approach, a transition they had to go through (Hervainé Szabó, Gy. 2008; Hirt, S. and Stanilov, K. 2009). In the new system, funding became primarily available from external sources, requiring local governments’ activity, embeddedness and commitment. Further challenge ap- peared after the Leipzig Charter (European Commission, 2007) with the transtion to an integrated urban development approach, as it posed difficulties for most post-socialist cities in terms of democratising planning and involving local stakeholders (Bajnai, L. 2007). Furthermore, other factors could not be overlooked either, including the economic decline and unemployment stemming from the collapse of industry, the lack of function- ing real estate market until the political trans- formation, the adverse effects of privatization on land use, the neglect of environmental pollution, the growing social inequality and segregation, the lack of capital for local gov- ernments, the absence of an established part- nership system, and the negligible presence of the civil sector (Hervainé Szabó, Gy. 2008; Barta, Gy. 2009; Hirt, S. 2013). To address these challenging issues, post-socialist cities aimed for a secure tran- sition, with governments acting as partners, as seen in the case of Hungary. During this transitional period, while urban develop- ment was under government control with the involvement of supervisory authorities, local governments had the opportunity to apply, plan, and execute independently. According to Pintér, T. “the persistence of the eastern periphery was also necessary for the development of the western countries” (Pintér, T. 2015, 127), meaning that the hand- icap of Eastern European cities inadvertently contributed to the strengthening of Western European cities. In urban development, the role of the European Union became crucial not only in terms of financing but also in introducing policy measures and fostering cooperation (Verdonk, H. 2014), which can stimulate the development of post-socialist cities. Today, one of the most highlighted aspects of EU urban development is the creation of sustain- able and green cities, contributing to miti- gating the negative effects of climate change. To achieve this, the European Commission established the European Green Capital Award (EGCA) in 2008, which encourag- es cities to transition onto a “green path” and promotes long-term development that positively impacts residents’ quality of life (Gudmundsson, H. 2015). The effects of im- plemented developments can be measured through monitoring studies, which can also be considered as performance evaluations, thus, revealing the extent of progress in a given city. The European Union also advo- cates for the monitoring of cities based on various indicators, which also serve as the basis for awarding the EGCA. This study focuses on the major cities (i.e., above 100,000 inhabitants) within the Pannonian Basin in East Central Europe. There have been numerous publications related to sustainability in the region, with the application of various environmental indicators being relatively popular. For in- stance, Bănică, A. et al. (2020) examined several Central and Eastern European cities to explore the connections between green infrastructure, resilience, and adaptability. Similarly, Csete, Á.K. and Gulyás, Á. (2021) investigated the urban green infrastructure network of Szeged, and the role of vegetat- ed surfaces in urban water management. Herbel, I. et al. (2016) studied the urban heat island phenomena in Cluj-Napoca, 289Schmeller, D. and Pirisi, G. Hungarian Geographical Bulletin 72 (2023) (3) 287–309. which are considered “byproducts” of in- creasing urbanization and climate change. Popescu, R-I. and Zamfir, A. (2012) ana- lysed the competitiveness of green cities in the field of “ecological marketing” based on the European Green Capital Award and the Romanian Green City program, finding a close relationship between a city’s ecologi- cal values and its competitiveness. Buzási, A. and Jäger, B.S. (2021) assessed the sustain- ability of Hungarian county capitals using various statistical methods, while Sikos, T.T. and Szendi, D. (2023) examined Hungarian major cities from economic and environ- mental sustainability perspectives based on specific topics related to the UN Sustainable Development Goals. Some publications spe- cifically analyse individual sustainability in- dicators, such as cycling in Osijek (Dimter, S. et al. 2019), the per capita green space in Romanian, Slovenian, and Croatian cities (Badiu, D.I. et al. 2016; Selimović, A. 2022), or energy management in Pécs (Kiss, V.M. 2015). Despite the growing number of stud- ies, a comparative analysis of sustainability indicators of cities in the Pannonian Basin is still missing. The European Green Capital Award The establishment of the European Green Capital Award began in 2006 with an ini- tiative led by Jüri Ratas (Prime Minister of Estonia between 2016 and 2021, and former Mayor of Tallinn from 2005 to 2007). Fifteen European cities joined this initiative, includ- ing Tallinn, Helsinki, Riga, Vilnius, Berlin, Warsaw, Madrid, Ljubljana, Prague, Vienna, Kiel, Kotka, Dartford, Tartu, and Glasgow. The Estonian Cities Association also became associated with the initiative (Sareen, S. and Grandin, J. 2019). The fundamental princi- ples and objectives of the award were out- lined in a declaration known as the Tallinn Memorandum 2006. In this memorandum, the award’s purpose and thematic areas were defined as follows: “Following the initiative of Tallinn, we, representatives of European cities, propose to the European authorities to establish the European Green Capital title. This is to be awarded each year to a city that is an environmental role model for other municipalities, e.g., by having followed a consistent environmental policy, implemented sustainable mobility solutions, including an improved public transport system, expanded the territories of parks and green areas, successfully introduced modern waste management prin- ciples and technologies, or implemented innovative and enterprising solutions to improve the quality of the urban living environment.” (Tallinn Memorandum 2006). The European Commission introduced the award in 2008, creating the first official recognition by the European Union aimed at promoting and supporting the development of green and sustainable cities (Lönegren, L. 2009; Gulsrud, N.M. et al. 2017). The justifica- tion for the existence of the European Green Capital Award is based on the growth of ur- ban populations, which has led to the con- centration of environmental and social issues primarily in these regions. Cities are seen as having to adapt to these challenges (Kahn, M.E. 2006; Beatley, T. 2011; Carter, J.G. 2011; Beretta, I. 2014). The award aims to evaluate how municipalities respond to various en- vironmental challenges, recognizing efforts directed at improving the urban environment and contributing to the creation of more sus- tainable and healthier cities. Additionally, it encourages cities to share their experiences, fostering a collaborative and continuously evolving system (Ruiz del Portal Sanz, A. 2015; Diverde, H. 2016; Cömertler, S. 2017; Nurse, A. and North, P. 2020). Cities with a population of over 100,000 can apply for the award, provided that their country is a member of the European Union, a candidate for accession, or located within the European Economic Area or Switzerland. If the city with the highest population in the country does not meet this threshold, the city with the highest population is allowed to apply. For cities interested in applying, an an- nual workshop is organized to explain the application process and allow participants to share experiences and ideas. The first step in the application is registration, which is Schmeller, D. and Pirisi, G. Hungarian Geographical Bulletin 72 (2023) (3) 287–309.290 entirely non-binding. In other words, cities are not obliged to compete later on, but this registration provides insight into the details and processes of the application. If the city leadership decides to proceed with the ap- plication, the application documents must be submitted through an online platform, which needs to be signed by the mayor or the highest-ranking city representative (Gudmundsson, H. 2015). Cities applying for the award must meet various criteria (Meijering, J.V. et al. 2014), including pre- senting their current state, developments carried out in the past five to ten years, and future goals in various thematic areas. It is also important to showcase commitments, agreements, partnerships, and the role of the community in these developments (European Commission, 2021). At the time of the launch of the award, cit- ies competed based on ten criteria, which have undergone multiple revisions since then (Figure 1). This study examines cities based on the thematic areas specified in the 2022 competition announcement. The reason for this is that starting from the 2023 round, the “sustainable land use and soil” criterion is challenging to quantify with data (e.g., soil sealing). Furthermore, this new criterion did not apply to cities that had already applied for the award, and their application materials do not provide information on this aspect. The submitted applications are evaluated by international experts who create rankings of cities based on the points they have earned. The decision regarding which cities advance to the finals is made by the European Commission based on expert opinions (Gudmundsson, H. Fig. 1. The change of the EGCA-criteria over time. Source: Authors’ own elaboration based on the documents of the European Commission. 291Schmeller, D. and Pirisi, G. Hungarian Geographical Bulletin 72 (2023) (3) 287–309. 2015). In the final circle, cities are required to present their results and explain why they could serve as examples to other cities. By focusing on the identified areas of im- provement in the examination of thematic are- as, cities can effectively manage their financial and temporal resources. They can prioritize areas of development that are crucial for sus- tainability, thereby increasing their chances of success in the competition and enhancing the overall sustainability of their city. The results of this study can contribute to the develop- ment of sustainable, resilient, and green cities, serve as a model for city governments, and be used to enhance the chances of successful participation in the award competition. Financial background of the award The European Green Capital Award does not have its own budget, so it cannot provide di- rect financial support to the applying cities. Cities must seek other European Union fund- ing opportunities to finance their urban de- velopment activities. However, the winning city is entitled to a cash prize introduced since 2019. In 2022, this prize amounted to 350,000 EUR, while the 2023 winner received 600,000 EUR. This prize is funded from the budget of the LIFE program. Cities whose countries do not participate in this program are not eligible for the financial reward (Eu- ropean Commission, 2021). Benefits after winning the award Winning the award can come with several benefits. The winning city can gain inter- national recognition and media coverage, which can positively impact tourism and promote the green city brand. New collabo- rations may be established within the city or with other cities. A notable example is the European Green Capital Network (since 2014)3, through which winning and finalist 3 Available at https://environment.ec.europa.eu/ cities can share their ideas and experiences, represent European cities in the field of en- vironmental protection and sustainability, encourage other cities to engage in sustaina- ble urban planning, and collaborate with the European Commission. Environmental pro- jects can receive greater emphasis, strength- ening the commitment to sustainability. The documentation generated through the award process can help in measuring and analysing the city’s development, highlighting weak- nesses and problems, and providing com- parable data for other cities. Involving city residents in development through public opinion research, informational campaigns, and forums can enhance their commitment to their city, enabling them to contribute to creating a more livable, healthier, and attrac- tive city, ultimately improving their quality of life. Since 2019, the cash prize awarded to cities can be spent on sustainable urban development investments (European Com- mission, 2021). Review of the literature on research focusing on the European Green Capital Award The European Green Capital Award has been of interest to the European Commission since 2006, but it only gained significant recogni- tion in public discourse after the announce- ment of the first winning city in 2010. Conse- quently, the research on this topic dates back to around that time. Since the inception of the award, the European Commission has annu- ally published official evaluation documents, and the publications of the winning cities are also made available on the European Union’s document repository online4. The scholarly literature on the award includes five-year retrospective reports and final publications issued by the municipalities of the winning cities, as well as reports following the evalua- topics/urban-environment/european-green-capital- award/about-awards_en#eu-green-capital-network 4 Available at https://circabc.europa.eu/ui/group/ c6e126de-5b8c -4cd7-8d36-a1978a2a63de/ library/017bb562-fdd8-4adeb1ff-d1ac296c79b7 https://circabc.europa.eu/ui/group/c6e126de-5b8c-4cd7-8d36-a1978a2a63de/library/017bb562-fdd8-4adeb1ff-d1ac296c79b7 https://circabc.europa.eu/ui/group/c6e126de-5b8c-4cd7-8d36-a1978a2a63de/library/017bb562-fdd8-4adeb1ff-d1ac296c79b7 https://circabc.europa.eu/ui/group/c6e126de-5b8c-4cd7-8d36-a1978a2a63de/library/017bb562-fdd8-4adeb1ff-d1ac296c79b7 Schmeller, D. and Pirisi, G. Hungarian Geographical Bulletin 72 (2023) (3) 287–309.292 tion of the applications (accessible from 2010 to 2019). One of the earliest publicly avail- able studies on the European Green Capital Award was conducted by Lovisa Lönegren, who wrote her thesis in 2009 titled “The Eu- ropean Green Capital Award – Towards a sustainable Europe?”. In her research, she sought to answer whether the European Green Capital Award is a suitable method for addressing environmental challenges in the European Union. She approached the topic from the perspective of environmental protection and ecological modernization, us- ing the example of Stockholm. The most im- portant publications related to the European Green Capital Award are listed in Table 1. Table 1. Research topics and references connected with EGCA Approaches Topics References Analysing the 12 EGCA criteria Sustainable land use Hårsman, B. and Wijkmark, B. (2013); Ruiz del Portal Sanz, A. (2015) Local transportation Müller, M. and Reutter, O. (2020) Green space features and green infra- structure networks Cömertler, S. (2017); Kerr, L. (2017) Climate protection Müller, M. and Reutter, O. (2020) Every criteria Ratas, J. and Mäeltsemees, S. (2013); Pantić, M. and Milijić, S. (2021) Evaluation process of the applications Focusing ont he topic of local trans- portation Gudmundsson, H. (2015) Political background, environmental policies Analysis of winning cities Ozcan, N.S. (2015); Polato, E. (2017) The EGCA as a political tool in munic- ipal sustainability Diverde, H. (2016); Gulsrud, N.M. et al. (2017); Kurstjens, N. (2017); Manca, L.R. (2020) Urban governance Ersoy, A. and Hall, S. (2020) Responsibility and accountability Sareen, S. and Grandin, J. (2019) Entrepreneurial spirit and increased economic competitiveness after winning the award, as well as its significance for city management Nurse, A. and North, P. (2020) City branding and marketing Place branding through green spaces and the concept of a green city Gulsrud, N.M. et al. (2013); Andersson, I. (2016) Marketing activities of green cities Demaziere, C. (2020) The impact of social media on inter-or- ganizational collaborations Korpela, T. (2021) Environmental indicators Measurement of environmental sus- tainability Meijering, J.V. et al. (2014); Zoeteman, B. et al. (2014, 2015) Examination of city monitoring Sarubbi, M.P. and Schmidt Bueno de Moraes, C. (2016) Comparison of urban environmental indexes Georgi, B. (2016); Feleki, E. et al. (2018) Analysing the cities applied Based on completed developments Biscossa, F. et al. (2017); Maior, J-C. (2019) Revitalization of city centres and renew- al of public spaces Poljak Istenič, S. (2016); Svirčić Gotovac, A. and Kerbler, B. (2019) The role of civil organizations and grassroots initiatives Ersoy, A. and Larner, W. (2019) Source: Authors’s own elaboration. 293Schmeller, D. and Pirisi, G. Hungarian Geographical Bulletin 72 (2023) (3) 287–309. The cities that have won and applied so far Between the 2010 and the 2024 round of the EGCA, 110 cities have applied for the award, ten of which are located in the study area of the Pannonian Basin (Figure 2). Among the winners, we primarily find cities from West- ern and Northern Europe. Germany, France, and Spain have each had two winner cities from the inception of the award up to 2024. There is an ”axis of winners” to be observed in the map from Lisbon to Lahti, and also, there is a spatial concentration of the final- ist cities in the Northwest of Europe. Among the post-socialist cities, there are only two succesfull candidates: Ljubljana (2016) and Lahti (2023) were able to win the award after many years of continous applications. Over time more and more post-socialist cities have applied to the award, altough most of them have not even reached the final round before the decision. Research questions and methodology Up until the 2024 round of the EGCA, a to- tal of 110 cities have applied for the award. Among them, ten are located within the Pan- nonian Basin, although none of them became finalists or winners. In this study, the cities geographically closest to the cities under ex- amination include Ljubljana (2016), whose environmental values serve as a reference point in some of the analyses. When selecting the reference city, we considered (relatively) similar geographical conditions and urban development paths, as the majority of cities Fig. 2. Cities that applied for the award (2010–2024). Source: Authors’ own elaboration. Winning cities Shortlisted cities Applicant cities Schmeller, D. and Pirisi, G. Hungarian Geographical Bulletin 72 (2023) (3) 287–309.294 in the Pannonian Basin belonged to the East- ern Bloc, i.e., the state-socialist bloc (Hirt, S. et al. 2017). The primary question in the examination of cities in the Pannonian Basin with a popu- lation of over 100,000 was whether the envi- ronmental values of Hungarian cities differ from those of the reference city? If so, which indicators and to what extent do they differ? Another question that arose was whether the two ‘Western’ cities in the study are posi- tioned higher in the similarity ranking or if their environmental values are more similar to those of post-socialist cities? Among the 27 cities examined in this re- search (excluding Ljubljana), 17 have not yet applied for the award (Figure 3). Therefore, we considered these as ‘potential applicants’ and sought to determine if there was a variable in which their values were worse than those of the cities that had already applied. Furthermore, aside from Ljubljana, can it be concluded that among the examined cit- ies, those that have not applied for the award have any chance of making it to the final round? To explore the similarities and differenc- es in environmental values, we used inde- pendent samples t-test (Student’s t), Mann- Whitney U-test, Chi-square test of independ- ence, random forest and a geospatial tool, the similarity search. It is important to empha- size that this research is conceived as an ex- ploratory analysis (EDA), i.e., we do not aim to prove or disprove specific hypotheses, as EDA uses different statistical methods to test the strength of the relationship, not to prove hypotheses (Velleman, P.F. and Hoaglin, D.C. 2012). Tukey, J.W. (1977) described EDA as detective work, the aim of which is to un- cover patterns. The purpose of a discovery analysis is to detect some pattern, difference or similarity in the values of the items un- der investigation (Fife, D.A. and Rodgers, J.L. 2022). Although controversial, it appears that the p-value has at least some relevance in exploratory studies (Rubin, M. 2017), and Fig. 3. Cities covered by the analysis. Source: Authors’ own elaboration. 295Schmeller, D. and Pirisi, G. Hungarian Geographical Bulletin 72 (2023) (3) 287–309. therefore these values are included in the results along with the effect size, generally recommended in the literature (Fife, D.A. and Rodgers, J.L. 2022). Different methods were found to be ap- propriate for comparing cities that have and have not yet applied for the EGCA, due to the characteristics of the variables under study (Table 2). For the normally distributed variables, the independent samples t-test was used, while for variables with a non-normal distribution, the Mann-Whitney U-test was applied. The relationship between binary variables and the fact of applying was ana- lysed using Chi-square test. The chances of cities in the Pannonian Basin to reach the final round were calculat- ed using the random forest method. This first required the creation of a database to deter- mine which sustainability indicators would determine the outcome of the EGCA applica- tion. In the database, the values of 1005 cities that applied for the EGCA were collected according to the indicators identified above. These 100 cities already include the ten appli- cant cities in the Pannonian Basin. The cities were divided into two groups: the finalists (including the winners) and the non-finalists who didn’t make it to the finals. This binary division served as the dependent variable in the binary logistic regression6. The independ- ent variables consisted of the applied indica- tors, totaling 33, which were determined for each city based on the 2019 or 2020 values7, primarily sourced from pan-European da- tabases and documents and plans issued by local governments. This uniform definition raises two prob- lems which are seen as limitations for this research. Firstly, the EGCA application pro- 5 A total of 110 cities applied to the EGCA, but in ten cas- es there were missing data for most of the indicators. 6 If a city applied multiple times, the most recent result was used as the dependent variable. 7 If these were not available, the data closest in time was used. The difficulty of collecting pan-European sustainability indicators at a single point in time was also identified as a problem in the study by Zoete- man, B. et al. (2015). cess takes into account not only the current ecological values of cities, but also recent changes and future plans. Second, by defin- ing a single point in time, there is a risk that a city that applied for the EGCA at an early round may have improved significantly (or, on the contrary, stagnated8). It may not have been a finalist at the time of application due to its poor scores, but due to improvements since then, the model would incorrectly mark it as a finalist. The estimation does not take into account which cities applied in a given year, how strong the competition was, but it is relative to the total sample of 100 cit- ies. This is justified because we do not know the competitors of a potential candidate city, which would apply in the future, so it is ap- propriate to compare them with the full sam- ple of applicant cities. Also, the values of the 100 applicant cit- ies were used for the similarity search. As a first step, a rank scale transformation was performed based on all the scale variables of the 100 applicants and the 15 potential can- didate cities. Then, as a dimension reduction approach, we run a Multiple Factor Analysis (Pagès, J. 2002). Seven dimensions were cre- ated above an eigenvalue of 1, explaining 60.2 percent of the total variance. The reason for using the MFA procedure is that the 33 in- dicators are unevenly distributed across the EGCA themes, and if all of them had been included with equal weight, some categories could have biased the analysis. The reason for including 100 cities was to get a clearer picture of the relationship between the 33 variables and to avoid the bias due to the small number of elements and the limited geographical loca- tion that would have occurred if we had only created dimensions based on the values of the cities located in the Pannonian Basin. The random forest machine learning meth- od was used to determine the chances of the cities (except Ljubljana) to reach the final round. This is an ensemble method based on decision trees, the results of which are sum- 8 On the problem of green city indices without tem- poral monitoring, see Pace, R. et al. (2016). Schmeller, D. and Pirisi, G. Hungarian Geographical Bulletin 72 (2023) (3) 287–309.296 Table 2. Indicators and data sources used for the analysis of cities in the Pannonian Basin, as well as descriptive statistics for the indicators* Variable Mean Standard deviation Minimum Maximum N Data source(s) CO2 emissions, t/person/ year (1) 3.98 2.25 1.19 11.35 27 Eurostat, city documents (Climate Strategy, SECAP, SEAP), Covenant of Mayors website CO2 emissions, t/person/year – percentage of the national average (1) 77.62 39.92 31.33 222.63 27 Own calculation based on Eurostat data Length of cycle paths, m/person (3) 0.37 0.31 0.01 1.01 28 City documents, local media, national statistical offices Number of cars per 1,000 inhabitants (3) 361.29 67.96 190.00 526.00 28 Documents from Eurostat, na- tional statistical offices, national offices Number of cars per 1,000 inhabitants – percentage of the national average (3) 97.32 23.55 57.57 183.27 28 Own calculation based on Eurostat data Percentage of inhabitants travelling to work by car, % (3) 40.44 11.70 23.00 71.00 27 Eurostat, city documents, Sustainable Urban Transport Plan (SUMP), CIVITAS, European Platform on Mobility Management – Modal Split Tool Percentage of inhabitants travelling to work by public transport, % (3) 28.89 11.05 13.00 49.00 27 Eurostat, city documents, Sustainable Urban Transport Plan (SUMP), CIVITAS, European Platform on Mobility Management – Modal Split Tool Percentage of inhabitants walking to work, % (3) 23.54 10.25 1,60 42.00 27 Eurostat, city documents, Sustainable Urban Transport Plan (SUMP), CIVITAS, European Platform on Mobility Management – Modal Split Tool Percentage of inhabitants cycling to work, % (3) 6.68 6.34 0.00 26.70 27 Eurostat, city documents, Sustainable Urban Transport Plan (SUMP), CIVITAS, European Platform on Mobility Management – Modal Split Tool Size of green areas, m2/person (4) 15.30 10.13 3.78 43.77 28 Eurostat, Urban Documents, Joint Research Centre – The future of cities (Urban Data Platform) Population density, inhabit- ant/km2 (4) 1,584.14 1,120.84 343.52 4,335.00 28 Eurostat, city documents Proportion of Natura 2000 sites in relation to the area of the municipality, % (5) 10.66 11.47 0.00 44.90 28 Natura 2000 Network Viewer NO2 annual average, µg/m3 (6) 26.91 7.90 11.20 48.03 28 Eurostat, city documents, European Environment Agency – Air Quality Statistics PM10 annual average, µg/m3 (6) 25.77 5.31 18.47 39.20 28 Eurostat, city documents, European Environment Agency – Air Quality Statistics PM2.5 annual average, µg/m3 (6) 16.49 3.03 11.28 23.00 25 Eurostat, city documents, European Environment Agency – Air Quality Statistics Proportion of people living in > 65 dB noise pollution, %; along roads (7) 15.25 11.10 3.90 54.02 25 European Environment Agency (The Noise Observation and Information Service for Europe), city documents, regional, national environmental documents 297Schmeller, D. and Pirisi, G. Hungarian Geographical Bulletin 72 (2023) (3) 287–309. Table 2. Continued* Variable Mean Standard deviation Minimum Maximum N Data source(s) Median** Mode*** Proportion of people living in > 55 dB noise pollution, %; along roads (7) 17.95 13.57 2.07 65.21 25 European Environment Agency (The Noise Observation and Information Service for Europe), city documents, regional, national environmental documents Amount of waste, kg/person/ year (8) 349.23 92.65 228.71 566.00 28 Eurostat, Assessment of separate collection schemes in the 28 capitals of the EU (European Commission, Final Report 2015), city documents, local media Amount of waste, kg/person/ year – percentage of the national average (8) 97.66 26.08 51.33 162.71 28 Own calculation based on Eurostat data Recycling rate, % (8) 24.67 18.03 2.00 69.00 28 Eurostat, Assessment of separate collection schemes in the 28 capitals of the EU (European Commission, Final Report 2015), city documents, local media Recycling rate, % – percentage of the national average (8) 90.62 63.65 13.33 278.57 28 Own calculation based on Eurostat data Drinking water consumption, l/person/day (9) 121.04 26.94 77.30 180.00 28 Eurostat, city documents Drinking water consumption, l/person/day – percentage of the national average (9) 117.52 25.41 70.58 158.75 28 Own calculation based on Eurostat data Volume of waste water, population.equivalent – p.e. (9) 497,523.3 659,589.8 106,497 2,867,796 26 Urban Waste Water Treatment Directive, Urban Waste Water Treatment Viewer 2018 Number of electric car charging stations per 1,000 inhabitants (10) 0.08 0.07 0.01 0.31 28 Chargemap, Electro Maps, city documents Energy consumption, MWh/ person/year (11) 13.70 6.04 4.38 28.06 28 Eurostat, City documents, Covenant of Mayors website, Energy Cities, European Energy Research Alliance Energy consumption, MWh/ capita – percentage of the national average (11) 301.18 128.44 100.55 701.58 28 Own calculation based on International Energy Agency and Statista data Existence of a climate strategy (2) 1** 1*** – – 28 Municipalities’ websites Existence of Sustainable Energy Action Plan (SEAP) / Sustainable Energy and Climate Action Plan (SECAP) (11) 1** 1*** – – 28 Municipalities’ websites Covenant of Mayors membership (12) 1** 1*** – – 28 Covenant of Mayors website Aalborg Charter signatories (12) 0** 0*** – – 28 Sustainable Cities Platform Circular Economy Declaration signatories (12) 0** 0*** – – 28 Circular Cities Declaration website ICLEI - International Council for Local Environmental Initiatives membership (12) 0** 0*** – – 28 ICLEI website *First column: The numbers in brackets indicate the related EGCA theme, showcased in the introduction section. Source: Authors’ own calculations. Schmeller, D. and Pirisi, G. Hungarian Geographical Bulletin 72 (2023) (3) 287–309.298 marized in the final model (Ho, T.K. 1995). The advantage of random forest is that it is not sensitive to multicollinearity (Triscowati, D.W. et al. 2020), so it is not necessary to drop correlated variables. It has excellent high-di- mensionality, so it does not require a dimen- sionality reduction procedure, thus, avoid- ing the risk that reduced dimensions carry information that is not suitable for estimation (Cutler, A. et al. 2012). Thus, for variables, only centering and scaling preprocessing pro- cedures were performed. The random forest model was fine-tuned to produce the following settings. For each de- composition of the decision tree, 20 random variables were included (mtry), the criteria for the partitioning of the nodes were defined by the extra-tree algorithm (Geurts, P. et al. 2006), and the minimum number of obser- vations in each node was set to one. These parameters were selected by grid search dur- ing cross-validation. Cross-validation was performed using k-fold cross-validation. Although there is no default recommended value for k, most studies use 5 (Zhou, J. et al. 2019), so we adopted it. Since the number of finalists and non-finalists was dispropor- tionately distributed across the 100 cities, care was taken to ensure that each break- down preserved the proportions of these two groups. The k-fold cross-validation was repeated three times. As the final model, we chose the one with the highest specificity because this model is the best at correctly categorizing non-fi- nalists, meaning it has the lowest chance of misleadingly giving a city false hopes of be- ing a finalist. The reason for this is that our estimator model aims to provide a realistic presentation for cities. As no other analysed city apart from Ljubljana has yet made it to the final, and as overall Central and Eastern European cities do not excel in the compe- tition, it is advisable to exercise caution in the estimation. The model with the highest specificity is the best at correctly classifying non-finalists, so in this case the chances of falsely misleading a city with finalist hopes are the lowest. Research results The analysis shows differences in some vari- ables, but we cannot say that applicant cities are clearly more environmentally oriented (Table 3). An independent samples t-test and the associated effect sizes show that for two variables the effect size is medium, so an ob- servable difference has been found. The values for NO2 annual mean and energy consumption are more favourable in the case of the poten- tial candidate cities. If the data table of the 100 cities that have applied for the EGCA is ana- lysed together with the cities in the Pannonian Basin have not applied yet, it can be seen that five potential applicants (Subotica, Szeged, Satu Mare, Baia Mare, Debrecen) are among the top 25 cities with the lowest NO2 emis- sions even in this sample. While Brasov and Cluj-Napoca are among the bottom five cities overall, Budapest and Zagreb are also in the bottom third of the list. These highlighted cities also show that even within countries there can be significant dif- ferences, especially in Hungary and Romania (Constantin, D.E. et al. 2013), which are linked to the city’s role in the countrywide transport and industrial network. In Cluj- Napoca, for example, the overall proportion of people travelling by car or public transport is 63 percent, which increases NO2 emissions, and the fact that the city has a high number of windless days, which means that air pol- lutants are not being emitted from the city, further worsens the situation (Chereches, I.A. et al. 2023). Furthermore, NO2 emissions are also closely related to the population size of the settlement (Lamsal, L.N. et al. 2013). Energy consumption is also strongly deter- mined, as differences in the political, cultural, economic and climatic conditions of differ- ent countries can affect spatial disparities in energy use (Borozan, D. 2018). If the energy use of individual cities is compared with the national average, only small effect size level is associated with a more favourable value for the cities have not applied yet. There is no clear difference between those who have already applied for the award and 299Schmeller, D. and Pirisi, G. Hungarian Geographical Bulletin 72 (2023) (3) 287–309. those who have not applied yet, as confirmed by the Mann-Whitney U-test (Table 4). The results show that there is only a notable dif- ference between the two groups in the pro- portion of people cycling to work and using public transport and recycling (the latter also compared to the national average), as well as in the number of cars per 1,000 inhabit- ants compared to the national average and in population density. All of those variables have an effect size above the small level. Of the variables, the proportion of peo- ple who cycle to work is the only one that shows a result opposite to the expected pat- tern, i.e., more people cycle in cities that are potential candidates than in applicant cities. Of the potential candidate cities, Bratislava, Graz and Szeged have rates that are among the highest of all European cities that have already applied for the EGCA. The differ- ence is also somewhat explained by the geo- graphical location: the inhabitants of Košice, Pécs and Brasov, which are partly located on hill slopes and have already applied for the EGCA, rarely use bicycles. However, there is no longer a big difference in the extent of the cycle path network, and in fact the applicant cities have somewhat higher values. The difference in cycling is also explained by the fact that public transport is much more popular in the applicant cities. Cities that have the worst values in terms of bicy- cle use (e.g., Pécs and Košice) are among the leaders in terms of public transport usage. Public transport is a priority in all the capital cities surveyed except Ljubljana. In relation to the EGCA criterion “sustainable urban transport”, the inhabitants of the applicant cities have fewer cars than the national aver- age, but the difference in terms of travelling by car to work is smaller. The considerable difference in population density values is influenced by the fact that the potential candidate cities with the low- est population density are located mainly in the lowlands (e.g., Kecskemét, Nyíregyháza, Debrecen), where there was no geographi- cal limit to the dispersion of settlements. However, it is important to note that the population density value does not really tell us much about the compactness of the settle- ments (which would indeed be a significant Table 3. Results of the independent samples t-tests Variable Mean (cities have not applied yet) (n = 17) Mean (cities already applied) (n = 11) t Cohen’s d Effect size NO2 annual average 24.543 30.567 -2.088* -0.808 medium PM10 annual average 25.716 25.865 -0.071 -0.027 – PM2.5 annual average 16.919 15.846 0.861 0.351 small Number of cars per 1,000 inhabitants 35.882 369.661 -0.516 -0.199 – Percentage of inhabitants travelling to work by car 41.406 39.045 0.507 0.198 – Percentage of inhabitants walking to work 23.268 23.954 -0.167 -0.065 – Amount of waste – percentage of the national average 99.062 95.511 0.345 0.133 – Drinking water consumption 121.574 120.220 0.127 0.049 – Drinking water consumption – percentage of the national average 120.778 112.494 0.837 0.324 small Energy consumption 12.375 15.747 -1.471 -0.569 medium Energy consumption – percentage of the national average 285.470 325.470 -0.799 -0.309 small *p < 0.05. Source: Authors’ own calculations. Schmeller, D. and Pirisi, G. Hungarian Geographical Bulletin 72 (2023) (3) 287–309.300 factor for sustainability), as it would require a ratio of the population to the actual built- up area rather than to the total administra- tive area. There is a considerable difference be- tween the two groups in the value of recy- cling. This difference remains even when compared to the national average. The data show an interesting pattern, as the Romanian applicant cities have outstanding values at European level compared to the national value, while the Hungarian cities that are potential candidates are mostly in the bottom of the list. Among the binary variables, the Circular Economy Declaration shows the largest dif- ference between applicant cities and those that are potential candidates (Table 5). Among those already applied, there are three signa- tories (Ljubljana, Maribor, Budapest), while among the potential candidates, none has signed the declaration. ICLEI membership is also characterised by medium effect size. A total of five cities are ICLEI members, three of which have already applied for the award. All this suggests that EGCA is more popular among cities that are members or signatories of these two organisations. Table 4. Results of the Mann-Whitney U-tests Variable Mean (cities have not applied yet) Mean (cities already applied) Mann- Whitney U Biserial rank correlation Effect size CO2 emissions 4.066 3.878 83 -0.056 – CO2 emissions – percentage of the national average 81.80 71.45 95 0.079 – Number of cars per 1,000 inhabitants – percentage of the national average 99.014 94.705 127 0.358 medium Percentage of inhabitants cycling to work 8.843 3.545 134* 0.522 large Percentage of inhabitants travelling to work by public transport 25.756 33.454 51.5** -0.414 medium Length of cycle paths 0.301 0.480 69 -0.262 small Percentage of people living in > 65 dB noise pollution 14.834 15.890 87 0.160 small Percentage of people living in > 55 dB noise pollution 18.098 17.741 96 0.280 small Size of green areas 15.405 15.152 92 -0.016 – Proportion of Natura 2000 sites in relation to the area of the municipality 9.032 13.198 69 -0.262 small Population density 1,140.366 2,269.975 35* -0.625 large Amount of waste 339.326 364.551 84 -0.101 – Recycling rate 19.120 33.254 45* -0.518 large Recycling rate – percentage of the national average 71.258 120.558 55.5** -0.406 medium Volume of waste water 296,493.687 819,170.881 64 -0.200 small Number of electric car charging stations per 1,000 inhabitants 0.069 0.111 79 -0.155 small *p < 0.05, **p < 0.1. Source: Authors’ own calculations. 301Schmeller, D. and Pirisi, G. Hungarian Geographical Bulletin 72 (2023) (3) 287–309. Results of the similarity search In the similarity search analysis, 24 of the 28 cities were compared on the basis of the seven dimensions created by the MFA pro- cedure (the Serbian cities had missing data and Ljubljana was the benchmark). Based on the analysis, the cities most similar to the winner of round 2016 in terms of their eco- logical values are: 1. Bratislava, 2. Zagreb, 3. Maribor, 4. Vienna, 5. Graz; the least similar are: 21. Debrecen, 22. Cluj-Napoca, 23. Košice, 24. Oradea. The similarity search also reveals some geographical differences: the western cities are more similar to Ljubljana, while the cities marked in red and orange are all locat- ed east of the Danube (Figure 4). The top five cities are very similar or identical in terms of location, culture, history, language use, leg- islation, and so it can be assumed that they are making decisions and implement sus- tainable developments according to similar guidelines. Bratislava, which closely resem- bles Ljubljana, is on track to meet the SDG criteria like no other capital city in Central and Eastern Europe (apart from Ljubljana)9. The top five most silimar cities also include Graz, which in Egri and Paraszt ‘s study was placed in a joint cluster with Ljubljana, called “Innovative Green Cities and Urban Areas”. (Egri, Z. and Paraszt, M. 2013). The least sim- ilar cities to Ljubljana are mainly those that are major transport hubs (Oradea, Debrecen) or have an industrial past or are currently in- dustrialised (Košice, Cluj-Napoca). Among the cities most similar to Ljubljana, Bratislava and Graz have not yet applied for the award. 9 Available at https://euro-cities.sdgindex.org/#/ Each of the cities in the study scored worse than Ljubljana on only two variables: the length of cycle paths per capita and the amount of waste compared to the national average. In terms of CO2 emissions per capi- ta, only Budapest, Győr and Kecskemét were slightly worse than the winning city. Târgu Mureș has the lowest number of cars per 1,000 inhabitants (while Graz has the highest value) and also the highest share of pedestri- ans, while Bratislava has the highest share of cyclists. In terms of green spaces per capita, the Hungarian cities (except Pécs) are in the lead, while Baia Mare has the worst green space coverage. For Natura 2000 sites, the winning city is ranked fourth in our database, and Ljubljana has lower air pollution scores than most cities. Ljubljana ranks in the mid- dle of the pack in terms of night and daytime noise pollution and drinking water consump- tion, Nyíregyháza has the lowest waste gen- eration (Ljubljana is the fourth). There is no major difference in the amount of waste water treated, but Ljubljana scores poorly in terms of annual energy consumption (per capita). Regarding population density, the Hungarian (except Budapest) and some Romanian cit- ies have values below 1,000 inhabitants/km2, while the other cities have higher figures. The position of the Hungarian cities The ranking of Hungarian cities is as follows: Pécs 6th, Győr 8th, Miskolc 9th, Szeged 12th, Nyíregyháza 13th, Budapest 14th, Kecskemét 19th, and Debrecen 21st. Pécs excelled in the percentage of commuters using public trans- portation, the representation of Natura 2000 Table 5. Results of the Chi-square tests Variable Chi square Cramer’s V Effect size SEAP/SECAP Covenant of Mayors membership (12) Aalborg Charter signatories Circular Economy Declaration signatories ICLEI membership Existence of a climate strategy 1.000 0.226 0.671 0.050* 0.0617** 1.000 0.042 0.294 0.138 0.430 0.3880 0.073 small medium small medium medium small *p < 0.05, **p < 0.1. Source: Authors’ own calculations. Schmeller, D. and Pirisi, G. Hungarian Geographical Bulletin 72 (2023) (3) 287–309.302 areas within the city, per capita CO2 emis- sions, and daily drinking water consump- tion compared to the national average. These factors placed it among the top three cities. However, its performance in other indica- tors was somewhat poorer, falling more into the middle range. Pécs benefits from a high proportion of Natura 2000 areas within its city limits due to the presence of the Mec- sek Mountains, many of which are located within the administrative boundaries of Pécs and are under various protection statuses. Győr did not rank among the top three in any environmental indicators. In fact, it falls into the bottom three cities regarding per capita CO2 emissions and the percentage of pedes- trians in the city. On the positive side, Győr has the third highest per capita green area in the ranking, with 29.8 m2 per person. It is surpassed only by Szeged (34.7 m2/person) and Kecskemét (36.4 m2/person). Miskolc ex- cels in terms of Natura 2000 areas, where it holds the first position when considering its city size (44.9%). However, it ranks second in terms of PM10 and PM2.5 levels and third in terms of energy consumption compared to the national average. In other variables, Miskolc falls within the middle range. In Sze- ged, the lowest percentage of people com- mute by car to work (23%), while 17 percent of the population cycles to work (ranking third best), and the annual average for ni- trogen dioxide is the lowest here at 15.3 µg/ m3. Nyíregyháza ranks third highest in terms of PM10 annual average levels (31.9 µg/m3). However, it generates the least municipal waste per capita annually (228.7 kg), making it the second lowest compared to the national average. Nyíregyháza also ranks third best in recycling with a 47 percent recycling rate. Budapest ranks third highest in terms of per capita annual CO2 emissions but only slightly exceeds the national average. It takes the first place in the percentage of commuters using public transportation (45%). However, in terms of daily drinking Fig. 4. Result of the similarity search analysis. Source: Authors’ own elaboration. 303Schmeller, D. and Pirisi, G. Hungarian Geographical Bulletin 72 (2023) (3) 287–309. water consumption (and its value compared to the national average), Budapest does not fare well. Budapest residents use 148 liters of water daily, making it the second highest- consuming city (Debrecen shares the same values in water consumption). Budapest also produces the highest amount of wastewater, which is also influenced by its population size, as it is the second most populous city in the sample. Additionally, Budapest’s energy consumption per capita exceeds the national average, ranking it second highest. Kecskemét and Debrecen show a signifi- cant contrast in per capita CO2 emissions, with Debrecen emitting the second lowest amount while Kecskemét emits the most among all cities in the sample. Kecskemét also stands out for having the second high- est difference in the number of cars per 1,000 people compared to the national average (116.9%). Debrecen ranks third best in terms of municipal waste generated per capita (237 kg/person/year), but this does not correspond to a high recycling rate (10%). Kecskemét consumes more energy annually than any other city, including the national average. Regarding population density, Budapest is the most densely populated city, Győr is of average density, and the other Hungarian cit- ies have relatively low population density. Results of the random forest classification The AUC of the random forest model run on previously applied 100 cities is 0.74, with a sensitivity of 81.4 percent and a specific- ity of 40.4 percent. Based on the model, the ten most influential variables are the exist- ence of a climate strategy, the length of cycle paths per capita, the proportion of people using public transport, ICLEI membership, the number of electric car charging stations per population, the exictence of the Aalborg Charter signatory, the proportion of people commuting to work by public transport, population density, the annual average PM10 value and recycling. If these variables are examined for the raw data of the 100 ap- plicant cities, it can be seen that the finalists do indeed have better sustainability scores (the only exception being the proportion of people using public transport, where the av- erage for non-finalists is higher). If, therefore, the cities in the Pannonian Basin have good environmental values for these indicators in particular, their chances of reaching the final round of the competition could be increased in a possible bidding process. From the ran- dom forest model estimation for 27 cities, the finalists’chances for each city are shown in Table 6. Table 6. The chances of the investigated cities to reach the final round in the EGCA competition Potential candidates Probability of reaching the final round, % Applicant cities Probability of reaching the final round, % Bratislava Târgu Mureș Graz Miskolc Győr Timișoara Kecskemét Osijek Szeged Sibiu Satu Mare Debrecen Baia Mare Nyíregyháza Oradea 43.8 32.8 26.0 18.0 17.2 14.4 12.4 11.2 11.2 10.6 9.2 8.6 8.6 8.2 5.4 Vienna Maribor Budapest Zagreb Brașov Arad Pécs Cluj-Napoca Košice – – – – – – 67.0 32.6 31.4 30.6 14.6 9.8 9.6 9.2 6.6 – – – – – – Source: Authors’ own calculations. Schmeller, D. and Pirisi, G. Hungarian Geographical Bulletin 72 (2023) (3) 287–309.304 Compared to the results of the similarity search presented above, the random forest gives a more accurate estimate, since in the latter case the values of the cities are not com- pared to a single winning city, but to all win- ner or finalist cities. In addition, the random forest did not estimate the ranking based on dimensions, created by dimension reduction, but on the values of all indicators, and also took into account which indicators have the most influence on the chances of the outcome of the application. The top ranking based on estimated odds is consistent with the results of the similarity search. Bratislava, Zagreb, Maribor and Vienna all have scores above 30 percent. Vienna’s chances are particularly promising, the last time the city applied for the award was in 2014, but failed to make it to the final round. Târgu Mureș has shown a signifi- cant improvement compared to its similarity search result, mainly thanks to its favourable population density and air pollution indica- tors. Oradea is the least likely to make it to the final according to the random forest, which is in line with the result of the similarity search. Discussion The study focuses on the examination of cities in the Pannonian Basin with popula- tions exceeding 100,000 based on the EGCA criteria system, for which there are no other existing scholarly examples. Therefore, it can be said that the presented results are novel. The findings of this study gave evidence that there is no significant difference between the two groups of cities in the Pannonian Ba- sin, those that have already applied for the award and those that have not, based on the 33 environmental indicators. However, as Schmeller, D. and Sümeghy, D. (2023) gave evidence, Eastern European cities have less favourable environmental indicators com- pared to Western European cities. The most significant differences are observed in air pollution, transportation, waste manage- ment, population density indicators, as well as the presence or absence of various documents. It is important to highlight that not all variables are worse for Eastern European cities. For in- stance, the percentage of commuters using pub- lic transport, which is favourable for sustain- able urban transportation, is higher in Eastern European cities. However, the number of cy- clists and the length of cycling paths per capita are much lower compared to Western European cities. Furthermore, Eastern European cities have lower population density values, which are unfavourable in terms of sustainable land use. The presence of documents related to local governance and climate change is more com- mon in Western European cities than in the East. Therefore, the degree of lagging behind of Eastern European cities, specifically those in the Pannonian Basin, can be reduced through the development of the aforementioned topics, along with changes in political views, goals, and the attitude of local residents. The chances of cities making it to the final round of the award competition can be influ- enced by decisions made by city administra- tions. According to the study by Sümeghy, D. and Schmeller, D. (2023), the intentions of city administrations and the proportion of green-oriented representatives in local councils are correlated with submitting ap- plications. Left-leaning city municipality and a higher proportion of green-oriented repre- sentatives in local councils have a positive ef- fect on the chances of application, increasing the intention to apply. However, the studied cities are characterized by predominantly right-leaning city administrations and a low proportion of green-oriented representatives (Sümeghy, D. and Schmeller, D. 2023). The cited literature also reveals that political fac- tors can also be associated with reaching the final round. Making it to the finals is posi- tively influenced by a higher proportion of green-oriented representatives, experience with the award (how many times the city has applied), and a lower environmental index of the local city administration. In the case of Eastern European cities, multiple appli- cations do not guarantee reaching the finals since they perform poorly in other politi- cal variables: they have a low proportion of 305Schmeller, D. and Pirisi, G. Hungarian Geographical Bulletin 72 (2023) (3) 287–309. green-oriented representatives in the local council, and due to right-wing party ideolo- gies, economic interests take precedence over environmental concerns. In general, Eastern European cities have a high environmental index, which is unfavourable (Sümeghy, D. and Schmeller, D. 2023). Based on these findings, the question arises as to whether Eastern European cities apply for the award because they genuinely seek change and as- pire to become sustainable and green cities in the long term, or if the applications are merely driven by trends and greenwashing. Obtaining the award is not just about cam- paigning for sustainable and green cities during elections; it requires long-term com- mitment and continuous engagement and education of the population. It is worth not- ing that a city can still be sustainable, green, or resilient even if it does not apply for the award. Amsterdam and Vienna are good ex- amples of this. They applied for the award initially but have not done so since, yet they are considered among the world’s most liva- ble cities according to various indices and are leaders in various sustainability initiatives. The results can provide a solid foundation for the potential success of future applications by cities in the Pannonian Basin. However, there is also the possibility that based on the results, a city that has not applied yet might believe it has no chance of making it to the finals, leading the city administration not to submit an application to the European Green Capital Award. It is essential to consider the limitation that the analysis only examined each city based on data from a single year and did not take into account the strength of the competition in a given year. Considering the trend that the gravi- tational centre of cities applying for the European Green Capital Award is shifting towards the south and east, prospective cit- ies in the Pannonian Basin may not need to compete directly with cities like Stockholm or Copenhagen, which have outstanding sus- tainability indicators. Instead, they would be competing with other cities more similar to them. Thus, despite the relatively low per- centage shown in the chance estimation com- pared to all previous applicant cities, if the field of applicants continues to evolve as per current trends, the chances of making it to the finals will inevitably increase. To illustrate this, even though Graz had a chance estima- tion of only 26 percent, it had a higher chance than any other city that applied for the 2025 round and did indeed make it to the finals. Furthermore, the model only estimates the likelihood of making it to the finals for the first application (when cities typically do not make it to the finals), and it does not account for the positive impact that can emerge based on experiences from previous applications. In the case of a city reapplying, the real chance of success would likely be even higher than the estimated value. Cities can undoubtedly be sustainable and green without the European Green Capital Award, but the criteria and in- dicator set of the award can be valuable for achieving sustainability goals and measuring the political, environmental, and livability “performance” of cities across Europe. Conclusions The results show that cities that have already applied for EGCA have indeed performed better regarding some environmental indica- tors, but when looking at Europe as a whole and the 100 EGCA applicant cities, the vast majority of the applicant cities from the Pan- nonian Basin region are in the bottom third of the ranking. Ljubljana’s chances of winning were significantly boosted not only by its con- tinuously improving environmental indicators but also by the fact that the city administration submitted their application to the competition five times. This determination to apply for the award was supported by the estimation made using binary logistic regression. Both the random forest and the similarity search results show a certain geographical pattern, where the further east we go, the less likely the cities are to be finalists and the less similar they are to Ljubljana (the exception in the case of the random forest is Târgu Mureș). Schmeller, D. and Pirisi, G. Hungarian Geographical Bulletin 72 (2023) (3) 287–309.306 It can be observed that the similarity among the examined Hungarian cities is closer to the successful Western cities than to the previ- ously unsuccessful Eastern ones, indicating that they are making progress towards achiev- ing the appropriate environmental values. However, it is important to emphasize that compared to the Western or Northern winning cities, Hungarian cities tend to fall more in the middle or even towards the lower end of the ranking. In the cases of Pécs and Miskolc, the high percentage of Natura 2000 areas within the city boundaries positively influenced their rankings in the similarity search. The analysis also identified areas where ur- ban policies should focus locally if the goal is to join the elite club of green capitals. In the cases analysed, the average discrepancies in the individual indicators are generally not striking, but the estimates of the probability of being a finalist provided by the similarity analysis can be quite sobering, as in 33 percent of the cities analysed it is less than 10 percent. Some of the existing differences can be attribut- ed to geographical factors or to local conditions created by path dependency, which cannot be changed in any meaningful way. Examples in- clude population density, topography, which has a strong influence on the use of bicycles, and some energy economy issues, which are partly the result of the national energy mix and partly the result of local economic conditions. These factors are very difficult to adjust locally and in the foreseeable future. However, it is also possible to identify the elements on which a green-capital focused urban development policy should focus: the shortcomings can be addressed with the least investment and in the shortest time in terms of strategic planning and international conventions, organisations. It is also possible to expand the network of cycle paths or electric charging stations with low in- vestment compared to other areas. However, specific analyses focusing on the specificities of the cities concerned are needed to explore the potential effectiveness and investment re- quired for an urban policy that puts the recog- nition of green capital status at the heart of the local green transition. REFERENCES Andersson, I. 2016. ‘Green cities’ going greener? Local environmental policy-making and place branding in the ‘Greenest City in Europe’. European Planning Studies 24. (6): 1197–1215. Badiu, D.L., Iojă, C.I., Pătroescu, M., Breuste, J., Artmann, M., Niță, M.R., ... and Onose, D.A. 2016. Is urban green space per capita a valuable target to achieve cities’ sustainability goals? Romania as a case study. Ecological Indicators 70. 53–66. Bajnai, L. 2007. Városfejlesztés (Urban development). Budapest, Scolar. Bănică, A., Istrate, M. and Muntele, I. 2020. Towards green resilient cities in Eastern European countries. Journal of Urban and Regional Analysis 12. (1): 53–73. Barta, Gy. 2009. Integrált Városfejlesztési Stratégia: A városfejlesztés megújítása (Integrated Urban Development Strategy: Renewal of the urban de- velopment). Tér és Társadalom 23. (3): 1–12. Beatley, T. 2011. Biophilic Cities: Integrating Nature into Urban Design and Planning. Washington, D.C., Island Press. Beretta, I. 2014. Becoming a European Green Capital: A way towards sustainability? In From Sustainable to Resilient Cities: Global Concerns and Urban Efforts. Ed.: Hol, G.W., Bingley, Emerald Publishing Ltd. 315–338. Biscossa, F., Botti, M., Cappochin, G., Furlan, G., Lironi, S., Negri, G. and Selmin, T. 2017. Capitali Verdi d’Europa ed EcoCités. Strategie e metodi per la rigenerazione delle città / European Green Capital and EcoCities. Strategies and methods for urban regenearation. In European Green Capitals – Esperienze di Rigenerazione Urbana Sostenibile / Experiences of Sustainable Urban Regeneration. Eds.: Cappochin, G., Botti, M., Furlan, G. and Lironi, S., Siracusa, Lettera Ventidue, 15–39. Borozan, D. 2018. Decomposing the changes in European final energy consumption. Energy Strategy Reviews 22. 26–36. Buzási, A. and Jäger, B.S. 2021. Hazai megyeszékhe- lyek városi fenntarthatóságának statisztikai alapú elemzése (Statistical analysis of urban sustainability in Hungarian county seats). Statisztikai Szemle 99. (8): 731–758. Buzási, A., Jäger, B.S. and Hortay, O. 2022. Analysing and mapping heatwave vulnerability and urban sustainability. The case of largest Hungarian cities. In SUPTM 2022 Conference Proceedings Sciforum-050260. Available at https://doi.org/ 10.31428/10317/10480 Carter, J.G. 2011. Climate change adaptation in European cities. Current Opinion in Environmental Sustainability 3. (3): 193–198. Available at https:// doi.org/10.1016/j.cosust.2010.12.015 Chereches, I.A., Arion, I.D., Muresan, I.C. and Gaspar, F. 2023. Study of the effects of the https://doi.org/10.1016/j.cosust.2010.12.015 https://doi.org/10.1016/j.cosust.2010.12.015 307Schmeller, D. and Pirisi, G. Hungarian Geographical Bulletin 72 (2023) (3) 287–309. COVID-19 pandemic on air quality: A case study in Cluj-Napoca, Romania. Sustainability 15. (3): 2549. Clark, G., Moonen, T. and Nunley, J. 2019. The Story of Your City. Europe and its Urban Development, 1970 to 2020. Luxembourg, European Investment Bank. Constantin, D.E., Voiculescu, M. and Georgescu, L. 2013. Satellite observations of NO2 trend over Romania. The Scientific World Journal 2013: 261634. Doi: 10.1155/2013/261634 Cömertler, S. 2017. Greens of the European Green Capitals. IOP Conference Series: Materials Science and Engineering 245. (5): 52–64. Csete, Á.K. and Gulyás, Á. 2021. Green infrastructure- based hydrological modelling, a comparison between different urban districts, through the case of Szeged, Hungary. Hungarian Geographical Bulletin 70. (4): 353–368. Cutler, A., Cutler, D.R. and Stevens, J.R. 2012. Random forests. In Ensemble Machine Learning: Methods and Applications. Eds.: Zhang, C. and Ma, Y., New York, Springer, 157–175. Dannert, É. 2016. Terra incognita. Barnamezők és kezelésük Európában, valamint Magyarországon. (Terra incogni- ta. Brownfields and their handling in Europe and Hungary). PhD thesis, Pécs, University of Pécs, TTK. Demaziere, C. 2020. Green city branding or achieving sustainable urban development? Reflections of two winning cities of the European Green Capital Award: Stockholm and Hamburg. Town Planning Review 91. (4): 373–395. Dimter, S., Stober, D. and Zagvozda, M. 2019. Strategic planning of cycling infrastructure towards sustainable city mobility: Case study Osijek, Croatia. IOP Conference Series: Materials Science and Engineering 471. (2019) 092022. Diverde, H. 2016. The European Green Capital Award as a tool for the environmental work in Umeå. MSc thesis, Linköping, University of Linköping. Available at https://www.diva-portal.org/smash/ get/diva2:971647/FULLTEXT01.pdf Egri, Z. and Paraszt, M. 2013. Urbanizáció Kelet-Közép- Európában: A várostipológia kísérletei (Urbanisation in East Central Europe: Experiments of the urban typology). In Új hangsúlyok a területi fejlődésben. Eds.: Lukovics, M. and Savanya, P., Szeged, JATE Press, 79–98. Ersoy, A. and Larner, W. 2019. Rethinking urban entre- preneurialism: Bristol Green Capital – in it for good? European Planning Studies 28. (4): 790–808. Ersoy, A. and Hall, S. 2020. The Bristol Green Capital Partnership: an exemplar of reflexive governance for sustainable urban development? Town Planning Review 91. (4): 397–413. Available at https://doi. org/10.3828/tpr.2020.23 European Commission 2007. Leipzig Charter on Sustainable European Cities. Available at https:// city2030.org.ua/sites/default/files/documents/ DL_LeipzigCharta.pdf European Commission 2021. European Green Capital Award 2024 and European Green Capital Award 2024. Rules of Contest. Available at https://eurocid.mne. gov.pt/sites/default/files/repo-sitory/paragraph/ documents/9601/regulamento.pdf Feleki, E., Vlachokostas, C. and Moussiopoulos, N. 2018. Characterisation of sustainability in ur- ban areas: An analysis of assessment tools with emphasis on European cities. Sustainable Cities and Society 43. 563–577. Fife, D.A. and Rodgers, J.L. 2022. Understanding the exploratory/confirmatory data analysis continuum: Moving beyond the “replication crisis”. American Psychologist 77. (3): 453–466. Georgi, B. 2016. Assessing the urban environment: The European Green Capital Award and other urban assessments. In Sustainable Cities: Assessing the Performance and Practice of Urban Environments. Eds.: Laconte, P. and Gossop, C., London, I. B. Tauris, 50–67. Geurts, P., Ernst, D. and Wehenkel, L. 2006. Extremely randomized trees. Machine Learning 63. 3–42. Gudmundsson, H. 2015. The European Green Capital Award. Its role, evaluation criteria and policy implications. Toshi Keikaku 64. (2): 22–27. Gulsrud, N.M., Ostoić, S.K., Faehnle, M., Maric, B., Paloniemi, R., Pearlmutter, D. and Simson, A.J. 2017. Challenges to governing urban green infrastructure in Europe: The case of the European Green Capital Award. In The Urban Forest. Eds.: Pearlmutter, D. et al., Cham, Springer, 235–258. Hardi, T., Baráth, G., Csizmadia, Zs. and Uszkai, A. 2014. A városnövekedés területi eltérései Európában, különös tekintettel a járműipari város- okra (Spatial disparities of urban growth in Europe with special regard to locations of automotive industry). Tér és Társadalom 28. (2): 45–66. Hårsman, B. and Wijkmark, B. 2013. From ugly duckling to Europe’s first green capital: A historical perspective on the development of Stockholm’s urban environment. In Sustainable Stockholm. Eds.: Rader Olsson, A. and Metzger, J., Milton Park, Routledge, 10–50. Herbel, I., Croitoru, A.E., Rus, I., Harpa, G.V. and Ciupertea, A.F. 2016. Detection of atmospheric urban heat island through direct measurements in Cluj-Napoca city, Romania. Hungarian Geographical Bulletin 65. (2): 117–128. Hervainé Szabó, Gy. 2008. Az integratív várospolitika tapasztalatai a hazai várostérségekben (Experiences of integrative urban policy in domestic urban areas). Tér és Társadalom 22. (1): 77–91. Hirt, S. 2013. Whatever happened to the (post)social- ist city? Cities 32. 29–38. Hirt, S. and Stanilov, K. 2009. Twenty Years of Tansition. Human Settlements Global Dialogue Series, No. 5. Nairobi, UN-Habitat. https://doi.org/10.1155%2F2013%2F261634 https://www.diva-portal.org/smash/get/diva2:971647/FULLTEXT01.pdf https://www.diva-portal.org/smash/get/diva2:971647/FULLTEXT01.pdf https://doi.org/10.3828/tpr.2020.23 https://doi.org/10.3828/tpr.2020.23 https://city2030.org.ua/sites/default/files/documents/DL_LeipzigCharta.pdf https://city2030.org.ua/sites/default/files/documents/DL_LeipzigCharta.pdf https://city2030.org.ua/sites/default/files/documents/DL_LeipzigCharta.pdf https://eurocid.mne.gov.pt/sites/default/files/repository/paragraph/documents/9601/regulamento.pdf https://eurocid.mne.gov.pt/sites/default/files/repository/paragraph/documents/9601/regulamento.pdf https://eurocid.mne.gov.pt/sites/default/files/repository/paragraph/documents/9601/regulamento.pdf Schmeller, D. and Pirisi, G. Hungarian Geographical Bulletin 72 (2023) (3) 287–309.308 Hirt, S., Ferenčuhová, S. and Tuvikene, T. 2017. Conceptual forum: The “post-socialist” city. Eurasian Geography and Economics 57. (4–5): 497–520. Ho, T.K. 1995. Random decision forests. In Proceedings of 3rd International Conference on Document Analysis and Recognition 1. Montreal, Canada, IEEE Publication, 278–282. Doi: 10.1109/ICDAR.1995.598994 IPCC 2022. Climate Change 2022. Mitigation of Climate Change. Intergovernmental Panel on Climate Change. WMO UN. Available at https://report. ipcc.ch/ar6/wg2/IPCC_AR6_WGII_FullReport.pdf Kahn, M.E. 2006. Green Cities – Urban Growth and the Environment. Washington, D.C., Brookings Institution Press. Kerr, L. 2017. A tale of two green cities. Exploring the role of visions in the development of green infrastructure in two European Green Capital Cities. MSc thesis, Nijmegen, Radboud University. Kiss, V.M. 2015. Modelling the energy system of Pécs – The first step towards a sustainable city. Energy 80. (1): 373–387. Konecka-Szydłowska, B., Trócsányi, A. and Pirisi, G. 2018. Urbanisation in a formal way? The different characteristics of the ‘newest towns’ in Poland and Hungary. Regional Statistics 8. (2): 135–153. Korpela, T. 2021. Social media logic in interorgani- zational boundary spanning: The case of European Green Capital Award 2021. BSc thesis, Groningen, University of Groningen. Available at https://frw. studenttheses.ub.rug.nl/3550/ Kovács, Z. 1999. Cities from state-socialism to global capitalism: an introduction. GeoJournal 49. (1): 1–6. Kurstjens, N. 2017. De duurzaamste stad van Europa. Een onderzoek naar stedelijke duurzaamheid en de rol van het beleidsinstrument ”European Green Capital Award”. MSc thesis, Nijmegen, Radboud University. Lamsal, L.N., Martin, R.V., Parrish, D.D. and Krotkov, N.A. 2013. Scaling relationship for NO2 pollution and urban population size: A satellite perspective. Environmental Science and Technology 47. (14): 7855–7861. Lönegren, L. 2009. The European Green Capital Award – Towards a sustainable Europe? BSc thesis. Malmö, Malmö University. Available at https:// www.diva-portal.org/smash/get/diva2:1483880/ FULLTEXT01.pdf Maior, J-C. 2019. Ljubljana – The Green Capital of EU in 2016. Study case – What has been changed in order to award the title? 2005–2015. Journal of Innovations in Natural Sciences 1. (1): 50–56. Manca, L.R. 2020. Green Capitals “in the Hearts and Minds of the People”. A qualitative enquiry into the perception of the influence of the European Green Capital Award among municipal officials. MSc thesis, Maastricht, Maastricht University. Available at https://www.researchgate.net/publi- cation/349238896_Green_Capitals_in_the_Hearts_ and_Minds_of_the_People_A_qualitative_enqui- ry_into_the_perception_of_the_influence_of_the_ European_Green_Capital_Award_among_munici- pal_officials Meijering, J.V., Kern, K. and Tobi, H. 2014. Identifying the methodological characteristics of European green city rankings. Ecological Indicators 43. 132–142. Available at https://doi.org/10.1016/j.ecolind.2014.02.026 Müller, M. and Reutter, O. 2020. Benchmark: Climate and environmentally friendly urban passenger trans- port – the concepts of the European Green Capitals 2010–2020. World Transport Policy and Practice 26. (2): 21–43. Nurse, A. and North, P. 2020. European green capital: Environmental urbanism, or an addition to the entrepreneurial toolbox? Town Planning Review 91. (4): 357–372. Nzimande, N.P. and Fabula, Sz. 2020. Socially sustainable urban renewal in emerging economies: A comparison of Magdolna Quarter, Budapest, Hungary and Albert Park, Durban, South Africa. Hungarian Geographical Bulletin 69. (4): 383–400. Ozcan, N.S. 2015. An opportunity for the sustainable ecological renewal: European Green Capitals. In Digital Proceeding of ICOCEE – CAPPADOCIA 2015. 20–23. 05.2015. Nevsehir, Turkey. Pace, R., Churkina, G. and Rivera, M. 2016. How Green is a “Green City”? A Review of Existing Indicators and Approaches. Potsdam, Institute for Advanced Sustainability Studies (IASS). Pagès, J. 2002. Analyse factorielle multiple appliquée aux variables qualitatives et aux données mixtes. Revue Statistique Appliquee 50. (4): 5–37. Pantić, M. and Milijić, S. 2021. The European Green Capital Award – Is it a dream or reality for Belgrade (Serbia)? Sustainability 13. (11): 6182. Available at https://doi.org/10.3390/su13116182 Pintér, T. 2015. Integrált városfejlesztés az Európai Unió keleti és nyugati tagállamaiban: Románia és Németország esete (Integrated urban development in the eastern and western member states of the European Union: The case of Romania and Germany). Journal of Central European Green Innovation 3. (1063- 201686207): 123–136. Polato, E. 2017. Le Capitali Verdi Europee / European Green Capitals. BSc thesis, Padova, University of Padova. Available at https://core.ac.uk/reader/89389670 Poljak Istenič, S. 2016. Reviving public spaces through cycling and gardening. Ljubljana – European Green Capital 2016. Etnološka Tribina: Godišnjak Hrvatskog Etnološkog Društva 46. (39): 157–175. Popescu, R-I. and Zamfir, A. 2012. Ecological marketing and competitive cities – Best practices for sustainable development of green cities. International Journal of Arts and Sciences 5. (1): 411–419. Puczkó, L. and Jószai, A. 2015. Települési tervezés (Sett lement planning). Budapest , Nemzeti Közszolgálati Egyetem. https://doi.org/10.1109/ICDAR.1995.598994 https://report.ipcc.ch/ar6/wg2/IPCC_AR6_WGII_FullReport.pdf https://report.ipcc.ch/ar6/wg2/IPCC_AR6_WGII_FullReport.pdf https://frw.studenttheses.ub.rug.nl/3550/ https://frw.studenttheses.ub.rug.nl/3550/ https://www.diva-portal.org/smash/get/diva2:1156189/FULLTEXT01.pdf https://www.diva-portal.org/smash/get/diva2:1156189/FULLTEXT01.pdf https://www.diva-portal.org/smash/get/diva2:1156189/FULLTEXT01.pdf https://www.researchgate.net/publication/349238896_Green_Capitals_in_the_Hearts_and_Minds_of_the_People_A_qualitative_enquiry_into_the_perception_of_the_influence_of_the_European_Green_Capital_Award_among_municipal_officials https://www.researchgate.net/publication/349238896_Green_Capitals_in_the_Hearts_and_Minds_of_the_People_A_qualitative_enquiry_into_the_perception_of_the_influence_of_the_European_Green_Capital_Award_among_municipal_officials https://www.researchgate.net/publication/349238896_Green_Capitals_in_the_Hearts_and_Minds_of_the_People_A_qualitative_enquiry_into_the_perception_of_the_influence_of_the_European_Green_Capital_Award_among_municipal_officials https://www.researchgate.net/publication/349238896_Green_Capitals_in_the_Hearts_and_Minds_of_the_People_A_qualitative_enquiry_into_the_perception_of_the_influence_of_the_European_Green_Capital_Award_among_municipal_officials https://www.researchgate.net/publication/349238896_Green_Capitals_in_the_Hearts_and_Minds_of_the_People_A_qualitative_enquiry_into_the_perception_of_the_influence_of_the_European_Green_Capital_Award_among_municipal_officials https://www.researchgate.net/publication/349238896_Green_Capitals_in_the_Hearts_and_Minds_of_the_People_A_qualitative_enquiry_into_the_perception_of_the_influence_of_the_European_Green_Capital_Award_among_municipal_officials https://doi.org/10.1016/j.ecolind.2014.02.026 https://doi.org/10.3390/su13116182 https://core.ac.uk/reader/89389670 309Schmeller, D. and Pirisi, G. Hungarian Geographical Bulletin 72 (2023) (3) 287–309. Ratas, J. and Mäeltsemees, S. 2013. Role of environment in strengthening competitiveness of cities by example of European Green Capitals and Tallinn. Estonian Discussions on Economic Policy 21. (2). Available at http://dx.doi.org/10.2139/ssrn.2383286 Rubin, M. 2017. Do p values lose their meaning in exploratory analyses? It depends how you define the familywise error rate. Review of General Psychology 21. (3): 269–275. Ruiz del Portal Sanz, A. 2015. Is the European Green Capital Award showcasing appropriate models of best practice for transition? The land use indicator. In 52nd International Making Cities Livable Conference on Achieving Green, Healthy Cities. Bristol, 29th June – 3rd July. 2015. Available at https://orca.cardiff.ac.uk/ id/eprint/85626/1/Angela%20Ruiz%20del%20 Portal_paper_.pdf Sailer-Fliege, U. 1999. Characteristics of post-social- ist urban transformation in East Central Europe. GeoJournal 49. (1): 7–16. Sareen, S. and Grandin, J. 2019. European green capitals: branding, spatial dislocation or ca-talysts for change? Geografiska Annaler: Series B, Human Geography 102. (1): 101–117. Available at https://doi. org/10.1080/04353684.2019.1667258 Sarubbi, M.P. and Schmidt Bueno de Moraes, C. 2016. Avaliação comparativa de metodologias de indi- cadores para a sustentabilidade urbana. Cadernos Zygmunt Bauman 8. (18): 211–231. Schmeller, D. and Sümeghy, D. 2023. Is the rival city always greener? – An analysis of the indicators for European Green Capital Award shortlisted and ap- plicant cities. Regional Statistics (forthcoming). Selimović, A. 2022. Važnost urbane zelene infrastrukture na primjeru grada. MSc thesis. Zagreb, University of Zagreb. Sikos, T.T. and Szendi, D. 2023. A hazai megyei jogú városok gazdasági és környezeti fenntarthatóságának mérése, 2020–2021 (Measuring the economic and environmental sustainability of cities with county rank, 2020–2021). Területi Statisztika 63. (1): 88–124. Sümeghy, D. and Schmeller, D. 2023. Giving the green light to sustainability: Key political factors behind the European Green Capital Award applications. Journal of Urban Affairs September 2023. Available at https:// doi.org/10.1080/07352166.2023.2247504 Svirčić Gotovac, A. and Kerbler, B. 2019. From post-socialist to sustainable: The city of Ljubljana. Sustainability 11. (24): 7126. Available at https://doi. org/10.3390/su11247126 Szirmai, V. 2004. Globalizáció és a nagyvárosi tér tár- sadalmi szerkezete (Globalisation and the social struc- ture of large urban spaces). Szociológiai Szemle 4. 3–24. Tallinn Memorandum 2006. Memorandum on the European Green Capital title. Available at https://ec.europa.eu/ environment/europeangreencapital/wp-content/ uploads/2011/06/Tallin-Memorandum.pdf Triscowati, D.W., Sartono, B., Kurnia, A., Dirgahayu, D. and Wijayanto, A.W. 2020. Classification of rice-plant growth phase using supervised random forest method based on landsat-8 multitemporal data. International Journal of Remote Sensing and Earth Sciences 16. (2): 187–196. Tukey, J.W. 1977. Exploratory Data Analysis. Reading, MA, Addison-Wesley. Velleman, P.F. and Hoaglin, D.C. 2012. Exploratory data analysis. In APA Handbook of Research Methods in Psychology. Eds.: Cooper, H., Camic, P.M., Long, D.L., Panter, A.T., Rindskopf, D. and Sher, K.J., Washington, D.C., American Psychological Association, 51–70. Verdonk, H. 2014. Urban policies in Europe. In Cities As Engines of Sustainable Competitiveness: European Urban Policy in Practice. Eds.: van den Berg, L., van der Meer, J. and Carvalho, L., Farnham, Ashgate Publishing, 11–83. Zhou, J., Li, E., Wei, H., Li, C., Qiao, Q. and Armaghani, D.J. 2019. Random forests and cubist algorithms for predicting shear strengths of rockfill materials. Applied Sciences 9. (8): 1621. Available at https://doi.org/10.3390/app9081621 Zoeteman, B., Slabbekoorn, J., Mommaas, H. and Dagevos, J. 2014. Sustainability Monitoring of European Cities. A Scoping Study Prepared in Collaboration with DG Environment for European Green Capital Award applicants. Telos Project, Tilburg, Tilburg University. Available at https:// pure.uvt.nl/ws/portalfiles/portal/29823642/14112_ Sustainability_Monitoring_EGCA_cities_8_9.pdf Zoeteman, B., van der Zande, M. and Smeets, R. 2015. Integrated Sustainability Monitoring of 58 EU- Cities. Draft report of Telos Project, Tilburg, Tilburg University. http://dx.doi.org/10.2139/ssrn.2383286 https://orca.cardiff.ac.uk/id/eprint/85626/1/Angela%20Ruiz%20del%20Portal_paper_.pdf https://orca.cardiff.ac.uk/id/eprint/85626/1/Angela%20Ruiz%20del%20Portal_paper_.pdf https://orca.cardiff.ac.uk/id/eprint/85626/1/Angela%20Ruiz%20del%20Portal_paper_.pdf https://doi.org/10.1080/04353684.2019.1667258 https://doi.org/10.1080/04353684.2019.1667258 https://doi.org/10.1080/07352166.2023.2247504 https://doi.org/10.1080/07352166.2023.2247504 https://doi.org/10.3390/su11247126 https://doi.org/10.3390/su11247126 https://environment.ec.europa.eu/system/files/2022-02/European%20Green%20Capital%20-%20Memorandum%20of%20understanding.pdf https://environment.ec.europa.eu/system/files/2022-02/European%20Green%20Capital%20-%20Memorandum%20of%20understanding.pdf https://environment.ec.europa.eu/system/files/2022-02/European%20Green%20Capital%20-%20Memorandum%20of%20understanding.pdf https://doi.org/10.3390/app9081621 https://pure.uvt.nl/ws/portalfiles/portal/29823642/14112_Sustainability_Monitoring_EGCA_cities_8_9.pdf https://pure.uvt.nl/ws/portalfiles/portal/29823642/14112_Sustainability_Monitoring_EGCA_cities_8_9.pdf https://pure.uvt.nl/ws/portalfiles/portal/29823642/14112_Sustainability_Monitoring_EGCA_cities_8_9.pdf Schmeller, D. and Pirisi, G. Hungarian Geographical Bulletin 72 (2023) (3) 287–309.310