The undeniable benefits of urban open spaces, such as parks and urban forests, has triggered a steady increase in “natural capital” demands. Nevertheless, the uncertainties surrounding open spaces and ecosystem services jeopardize their consideration in public decision making. Certain of their aspects are not fully translatable in economic terms, primarily due to the absence of proper valuation tools. This results in not only under-provisioning of natural capital, but also unsustainable urban development. Hence, an imperative need to incorporate efficient ecosystem valuation tools emerges. The objective of this research is twofold. Firstly, it aims to prove and quantify the influence of urban open spaces on the surrounding real estate’s market value. Secondly, it investigates which characteristics of these spaces bear the largest impact, with a particular interest in ecosystem services. The methodology employed in the present study is a combination of both quantitative and qualitative methods. The quantitative part, designated as Phase I, includes the establishment of a hedonic pricing model, which quantifies the added value of proximity to the selected clustered open spaces, which are also called “Ecosystem Service Hubs” (ESHs). The qualitative part, addressed as Phase II, swifts the focus from the housing samples to the ESHs. It consists of activities attempting an ecological profiling of the ESHs. Phase I’s Hub Hedonic Pricing model revealed that ESH1 bears the largest influence on surrounding real estate, followed by ESH3 and ESH2. Notably, a 1% increase in distance would lead to approximately 2,7€, 0,8€ and 1,6€ per m2 for each hub respectively. Inserting the distance variable as a dummy variable, instead of a continuous one, displayed a similar behaviour. Thence, each housing sample is divided into categories in order to execute a distance effect sensitivity analysis. It is suggested that “young, large, row houses in greener neighborhoods” exhibit the largest distance decay effect sensitivity. Lastly, the overarching monetary values are roughly estimated. These are 5,81, 1,98 and 3,28 million € for each hub respectively, whereas the average value per m2 per house is 77,44€, 57,68€ and 107,47€ respectively. Concerning Phase II, the ESHs’ core components and characteristics are identified. Then, an association between the economic benefits and the core characteristics is attempted, through qualitative correlations. These are summed up in the following statement: “Ecosystem Service Hubs generate higher economic benefits when they are larger and more diverse, in terms of both composition and ecosystem services, with a significant sensitivity to recreational opportunities”. This research’s findings could prove to be insightful for urban planning, since they could be applied in two major ways. Firstly, given an identified Ecosystem Service Hub, the development of the surrounding area could be adjusted to encompass primarily the optimal house and neighborhood characteristics. Secondly, given the “house composition” of a certain area, the optimal location and profile of a new Ecosystem Service Hub could be selected. In both cases, maximizing the value of surrounding real estate is achieved through optimal spatial configurations. In conclusion, the added value of urban open spaces is plural and reflects the use and non-use value derived from residents. This research’s rough estimation of an average of 80,86 € per m2 per house is an indication of this added value, subject, however, to the narrow scope of the study. Attributing this added value to particular open spaces’ characteristics could only be executed through qualitative correlations. In order to enrich the previous results, an integration of multiple valuation methods (social and ecological), which incorporate the various value dimensions, is recommended. More conclusive and definitive results will motivate planners to opt for polices revolving around ecosystem services and natural capital, thus, satisfying the steadily increasing demand.