Ricerc@Sapienza

Currently, potential distribution of plant species is represented by different uses of presence/absence indicators or by density-dominance-based ones such as the Importance Value (I.V.), and their geographical representation is based on statistical models (Random forest model, General Regression Models etc.) relating these indicators with climate and physical features of a given territory.

This paper presents MULESME, a software designed for the systematic mapping of surface soil moisture using Sentinel-1 SAR data. MULESME implements a multi-temporal algorithm that uses time series of Sentinel-1 data and ancillary data, such as a plant water content map, as inputs. A secondary software module generates the plant water content map from optical data provided by Landsat-8, or Sentinel-2, or MODIS. Each output of MULESME includes another map showing the level of uncertainty of the soil moisture estimates. MULESME was tested by using both synthetic and actual data.

Plants are open, irreversible and non-equilibrium systems that live via mass- and energy exchanges with the environment, and therefore, are amenable to a thermodynamic treatment: in fact, they may be considered “energy converters” because their metabolism is nothing else than a controlled ability to transform energy from one form (solar) into another (chemical energy suitable to cell metabolism) and to activate and maintain reactions at cellular- and molecular level -promoting the plant growth.

The Urban Heat Island (UHI) effect is one of the main environmental impacts of urbanization, affecting directly human health and well-being of the city dwellers, and also contributing to worsen environmental quality. As a key strategy to address sustainable urban development, the EU has advocated the development of Nature-Based solutions, such as the implementation of Green Infrastructure (GI), which can deliver a wide range of Regulating Ecosystem Services (ES).

Forests cover about 30% of the Earth surface, they are among the most biodiverse terrestrial ecosystems and represent the bulk of many ecological processes and services. The assessment of biodiversity is an important and essential goal to achieve but it can results difficult, time consuming and expensive when based on field data. Remote sensing covers large areas and provides consistent quality and standardized data, which can be used to estimate species diversity.

The effectiveness of a Metamodel-Embedded Evolution Framework for model parameter identification of a Smoothed Particles Hydrodynamic (SPH) solver, called DualSPHysics, is demonstrated when applied to the generation and propagation of progressive ocean waves. DualSPHysics is an open-source code that provides GP-GPU acceleration, allowing for highly refined simulations. The automatic optimization framework combines the global-convergence capabilities of a Multi-Objective Genetic Algorithm (MOGA) with Response Surface Method (RSM) based on a Kriging approximation.