Remote Sensing for Urban Green Infrastructure. The analytical approach to meta-design process for climate risk reduction.

Urban and sub-urban systems are increasingly exposed to high vulnerability to climate risks with a long-term cascading impact on communities, the physical environment and ecosystems.Cities represent the areas where the world's population is most concentrated (UN World Urbanization Prospects,2018) with major impacts on land use change and reduction of permeable surfaces. This condition increases the level of climate risk for urban areas as it increases the exposure of assets and individuals but also affects the ability of urban systems to respond to extreme weather phenomena.

In this framework, Urban Green Infrastructure (UGI) is recognised by international literature and policy as a strategic factor in reducing the vulnerability of urban systems to climate change impacts such as heat island, heat canyon, flooding, runoff. I.G.U., in fact, produce ecosystem services capable of mitigating climate stress phenomena in cities by cooling (shading and evapotranspiration) and controlling runoff.
The scientific literature shows that interest in the U.G.I. project has shifted from a predominantly empirical and qualitative approach to an approach that sees the analytical implementation of information as an indispensable support of the project in terms of simulation, monitoring and control of the climate efficiency of infrastructures.

In particular, the analytical approach is functional to the "site-specific" and "hazard-specific" condition that characterises the U.G.Is. project. Among the main objects of investigation, the scientific community has long identified ecosystem services as a discriminating factor in assessing the climate efficiency of urban green areas. Recent studies have also made explicit the need to develop methods for the analytical measurement of ecosystem services in order to guide design towards appropriate climate performance thresholds.Starting from the assumption that information is the opposite of uncertainty (Ciribini, 1984), the U.G.I. design process must necessarily take advantage of new knowledge methods aimed at reducing the risk of failure and error, according to a predictive logic that aims to identify the most appropriate solution for a given urban context.

Remote sensing is an essential source of information on ecosystems and the state of natural capital for large-scale applications, but in the last two decades, the availability and advent of optical remote sensing and Earth observation data with various spectral, radiometric, spatial and temporal resolutions have increased significantly and constitute a very useful source of data even at the urban and site scale.

The paper presents a methodology for using remote sensing in the context of the U.G.I. project and in particular for mapping ecosystem services at the urban district scale.The methodology is tested on a case study chosen in the context of the metropolitan city of Naples and specifically in the eastern area, characterised by a peri-urban condition with strong environmental criticality.