## 1 Introduction  
In order to make urban areas more resilient to the effects of climate change, it is necessary to safeguard the presence of urban green areas and plan adaptation actions for future climate scenarios, such as, for example, applying green strategies to facilitate energy efficiency in metropolitan areas [1]. The need to transform urban systems into areas more resilient to phenomena generated by climate change makes a detailed study of the characteristics of urban green areas, relationships with buildings and relationships with the social fabric a crucial activity for the planner. In fact, as highlighted in [2], based on results of studies executed in different cities, urban green spaces play a primary role in the sustainable development of a city. In recent research, Geographical Information System (GIS)-based approaches have been implemented to analyze the characteristics of urban green spaces in sustainable urban planning. In [3], a hierarchical GIS-based method applied to study the accessibility of urban green spaces is proposed. A GIS-based study of the characteristics of urban green areas in a city, such as the green areas per capita and the distribution of the distance and accessibility of green areas throughout the city, is performed in [4]; this study is applied to the Turkish city of Kutahya. A GIS framework is proposed in [5] to classify the urban green space (UGS), by considering the various typologies of green spaces and the distribution of recreational UGS; the authors apply their model to the study area of Nagpur City, India. A multicriteria analysis model implemented in a GIS platform is proposed in [6] in order to detect suitable sites for urban green spaces; this method was applied to the city of Addis Ababa, Ethiopia. In this research we present a GIS-based integrated application framework to support the decision makers in the study of the characteristics of UGSs and their relation with the city. The main objective of this research was the experimentation of a GIS framework based on the partitioning model of a study area in urban contexts proposed in [7], implemented to perform an unsupervised partitioning in the UGSs of an urban system. The proposed GIS-based framework allows optimization of the use of the expert's knowledge to classify the different UGSs in the urban study area. We partition the urban system in homogeneous urban areas in terms of types of UGS and relationships between the presence of urban green areas, social characteristics and the built environment. In fact, unlike other works in the literature, this research is focused on the problem of analyzing not only the characteristics of urban green areas but also the set of relationships within the entire urban context. The idea of the proposed framework is to partition the city into homogeneous areas with respect not only to the characteristics of urban greenery, but also to those of the built and social fabric, in order to offer the planner a tool that allows him to identify which areas of the urban system require prioritization of green adaptive interventions, and to be able to allocate the categories of intervention based on the characteristics of the urban fabric in these areas. The main advantages of the proposed framework are the use of an unsupervised approach to partition the study area in UGSs and a high degree of usability and flexibility, as the expert can reconstruct or update the core set of indicators and the fuzzy rule set. In addition, the framework is independent from the choice of the core set of indicators and the classification of UGC types; in fact, this choice is made by the domain expert who can use the framework to autonomously build the core set of indicators, the classification of UGSs and the fuzzy rule set, based on their experience and knowledge. We have tested our framework on an urban area constituted by the municipality of Pozzuoli, Italy.