Cultural and natural heritage faces increasing threats from climate change and pollution. To address this, the INACO project (INnovative strategies for the Adoption of risk management plans to enhance the resilience of sensitive Cultural and natural heritage Objectives against climate hazards in river basin districts) aims to develop and enhance innovative tools for safeguarding these valuable assets. Our research focuses on the Risk Mapping Tool for Cultural Heritage Protection, a powerful instrument that combines both Earth Observation-based data and outputs from climate models. This integrated approach provides a comprehensive view of current and future risks by incorporating satellite observations with predictive climate projections. The tool's primary objective is to integrate novel variables, such as extreme indices and air quality data, to provide more accurate risk assessments. This advanced capability will directly support policy and decision-makers in their efforts to effectively manage and preserve heritage by delivering concrete, data-driven strategies.

This work presents the application of Electrical Resistivity Tomography (ERT) as a key geophysical technique for the characterization of the shallow subsurface in two pilot sites, Brovinje and Havišće, located in coastal areas of Croatia. These investigations were conducted within the framework of the Project RESONANCE – Interreg Italy-Croatia, aiming to improve landslide risk prevention and management. The ERT surveys provided crucial insights into the geological and structural settings of the areas. At the Brovinje site, ERT imaging allowed for the characterization of the structural style and the identification of lithological units, discerning between high-resistivity limestone and lower-resistivity marl. At the Havišće site, the surveys revealed the presence of incoherent dumped material, approximately 3-5 meters thick, and highlighted significant fracture zones. The results demonstrate the effectiveness of ERT in providing valuable subsurface geological information essential for comprehensive landslide risk assessment and mitigation strategies in coastal environments.

This paper examines the application of high-resolution satellite remote sensing and vegetation index analysis for the non-invasive investigation of the Villa of Sette Bassi, a major Roman archaeological site located on the outskirts of Rome. Utilizing Pléiades Neo satellite data and a suite of eleven vegetation indices, the study identifies subsurface anomalies indicative of buried architectural features. The methodological framework integrates rigorous image preprocessing, index derivation, and correlation with geophysical and historical datasets. The findings underscore the efficacy of select indices in complex Mediterranean landscapes. This work advances the methodological discourse in archaeological remote sensing, offering a scalable and replicable protocol for cultural heritage monitoring and landscape archaeology.

In this paper, Fiber Optics Reflectance Spectroscopy (FORS) was used to measure the concentration of pigments in paintings on a paper substrate. There is currently no agreement on a general quantitative approach using FORS, even if several attempts have been made in the past with varying degrees of success. In our approach, reflectance spectra were processed using the Kubelka-Munk (K-M) theoretical model of light propagation in an optical inhomogeneous medium. Experimental tests were carried out on mockups prepared using mixtures of two pigments (ultramarine blue and Naples yellow) and their reflectance spectra were acquired using a set-up with an integrating sphere. Given the linear relationship between the scattering and absorption coefficients of the pigments, and knowing the volume concentration of the pigments, the method enables both identification and quantification of components in the binary paint mixtures from FORS spectra.

Natural product residues found in objects of historical or artistic significance present a highly complex chemical matrix. With ongoing advances in analytical and instrumental techniques, the strategies for identifying these residues are evolving. The traditional marker-based approach, which focuses on specific target molecules, is increasingly being replaced by more holistic methods that consider the full chemical profile. In this context, multivariate data analysis plays a crucial role in extracting meaningful information from such complex datasets. This study employs untargeted Surface-Enhanced Raman Scattering Spectroscopy (SERS) to explore variables that distinguish dyes extracted from various lake pigments, prepared using distinct recipes and subjected to different extraction methods. The use of ANOVA Simultaneous Component Analysis (ASCA) enabled the assessment of how various factors influence the molecular pattern observed.