The aim of the paper is to map and evaluate the state of the multifunctional landscape of the municipality of Naples (Italy) and its surroundings, through a Spatial Decision-Making support system (SDSS) combining geographic information system (GIS) and a multi-criteria method an analytic hierarchy process (AHP). We conceive a knowledge-mapping-evaluation (KME) framework in order to investigate the landscape as a complex system. The focus of the proposed methodology involving data gathering and processing. Therefore, both the authoritative and the unofficial sources, e.g., volunteered geographical information (VGI), are useful tools to enhance the information flow whenever quality assurance is performed. Thus, the maps of spatial criteria are useful for problem structuring and prioritization by considering the availability of context-aware data. Finally, the identification of landscape services (LS) and ecosystem services (ES) can improve the decision-making processes within a multi-stakeholders perspective involving the evaluation of the trade-off. The results show multi-criteria choropleth maps of the LS and ES with the density of services, the spatial distribution, and the surrounding benefits.

The complexity of the urban spatial configuration, which affects human wellbeing and landscape functioning, necessitates data acquisition and three-dimensional (3D) visualisation to support effective decision-making processes. One of the main challenges in sustainability research is to conceive spatial models adapting to changes in scale and recalibrate the related indicators, depending on scale and data availability. From this perspective, the inclusion of the third dimension in the Urban Ecosystem Services (UES) identification and assessment can enhance the detail in which urban structure–function relationships can be studied. Moreover, improving the modelling and visualisation of 3D UES indicators can aid decision-makers in localising, analysing, assessing, and managing urban development strategies. The main goal of the proposed framework is concerned with evaluating, planning, and monitoring UES within a 3D virtual environment, in order to improve the visualisation of spatial relationships among services and to support site-specific planning choices.