Research lines

Remote sensing, Big data analysis and artificial intelligence for the study of the human past, landscape archaeology and cultural heritage risk analysis

1. Analysis of spectral properties from remotely sensed data for the identification of archaeological proxy indicators with special reference to crop-marks.
2. Development of procedures for the fusion of active and passive remote sensing data (satellite, airborne, geophysical) for the creation of predictive models to support preventive archaeology.
3. Development of processing and post-processing methodologies of active remote sensing data (LiDAR and SAR) for the analysis of microtopographic variations for the identification of archaeological features and the study of ancient landscapes.
4. Development of machine learning methods from multispectral remote sensing data (satellite and drone) for the automatic extraction of features and patterns of archaeological interest and for the analysis of natural and anthropic risk factors.
5. Hyperspectral imaging from aircraft and satellite for geoarchaeological and environmental archaeology applications.
6. Multi-temporal analysis of medium- and high-resolution Big Data satellites for change detection, spatio-temporal pattern detection for the identification and evaluation of risk factors of cultural and natural heritage.

Multiscale methodologies of integration and fusion of close-range remote sensing, sensoristics and in situ imaging techniques for the conservation and monitoring of the built and artistic heritage

1. Drone-Borne Surveying and Imaging – Designing and applying drone-based techniques for documenting, analyzing, and diagnosing the preservation state of archaeological and monumental sites.
2. Data Fusion and Feature Extraction – Integrating datasets from various imaging techniques (thermal infrared, high-frequency georadar, digital models) to identify and assess degradation pathologies in architectural surfaces and wall paintings.
3. Multiscale Environmental and Microclimatic Monitoring – Employing indoor and outdoor approaches to study environmental conditions affecting works of art.
4. Integrated Earth Observation and Multi-Platform Technologies – Combining satellite, drone, sensor, and in situ imaging for monitoring and managing tree heritage in archaeological sites and historic urban parks.
5. Seismic Risk Analysis of Historical Structures – Developing operational protocols using passive single-station techniques to assess the seismic vulnerability of leaning architectural structures.

Underwater acoustic remote sensing for in situ research on underwater cultural heritage

1. Integrated Underwater Data Analysis – Utilizing multibeam bathymetric measurements, backscatter data, and seismic data to study, monitor, and manage cultural and natural resources in underwater environments.
2. 3D Modeling of Underwater Archaeological Features – Developing procedures that integrate high-resolution bathymetric data with underwater digital photogrammetry to create detailed 3D models of submerged historical and archaeological sites. feature storico-archeologiche sommerse.
3. Land-Sea Archaeological Detection – Combining multibeam bathymetric data with LiDAR in marine-coastal environments to identify historical and archaeological targets at the land-sea interface.
4. Sub-Bottom Archaeological Mapping – Conducting integrated seismic and electrical tomography analyses to detect and map buried archaeological and topographical features in the shallow subsurface.

Spatial Data Science

1. Exploratory Spatial Data Analysis (ESDA) – Extracting significant spatial patterns and uncovering new explanatory relationships across diverse archaeological case studies.
2. Spatial Visualization Methods – Developing techniques for effectively representing spatial data to enhance interpretation and analysis.
3. Geocomputation and Decision Support Systems – Creating predictive models for archaeological research and heritage management through advanced computational methods.
4. Spatial DBMS and Big Data Systems – Implementing database management and big data frameworks to integrate archaeological and cultural heritage data with remote sensing information for improved analysis and decision-making.