Articles by Giuseppe P. Cirigliano

This paper reports preliminary outcomes of the 'Hidden Landscapes of Latium project', applied to the Presidential Estate of Castelporziano, an exceptionally well‑preserved coastal landscape in the central Mediterranean and, concurrently, a highly challenging forested context for landscape archaeology. The study area, about 60 km², characterized by dense and continuous vegetation cover, was surveyed by airborne LiDAR acquisition at very high point density (in average 350 pts/m²), with the goal to facilitate under‑canopy archaeological detection in a highly challenging Mediterranean environments. We provide a critical appraisal of the acquisition strategy, with particular attention to sampling density and flight design as determinative factors for the detection of subtle anthropogenic micro‑topographies. The acquired dataset was subjected to a semantic‑segmentation processing pipeline that integrates multi‑level and multi‑resolution machine‑learning techniques for the automated classification of ground, vegetation, and structural elements. Results indicate that the combination of archaeologist-addressed, high‑resolution LiDAR acquisition and advanced semantic classification substantially enhance the interpretability of forested archaeological landscapes and enables the identification of features previously obscured by vegetation. Castelporziano thus constitutes a valuable testbed for evaluating the applicability, transferability, and limitations of LiDAR‑based methodologies within Mediterranean landscape archaeology.

This paper presents an integrated geophysical and UAV-LiDAR investigation of the Rusellae (Roselle) hinterland, carried out within the Emptyscapes framework aimed at moving beyond site-based approaches toward a continuous, landscape-scale reconstruction of settlement and land-use dynamics. While extensive field survey, aerial imagery and large-scale magnetometry are effective in the open agricultural portions of the Ager Rusellanus, densely vegetated hill slopes remain a major source of knowledge bias. To address this gap, we combined (i) new magnetic prospections (ca. 70 ha) in the south-western sector of the study area with (ii) a drone-based high-density LiDAR survey (ca. 550 ha) acquired with a RIEGL miniVUX-3 at low altitude and controlled speed, achieving an average density >700-800 pts/m². Point clouds were processed through a multi-level, multi-resolution semantic segmentation workflow, using a Point Transformer deep-learning architecture to classify ground, vegetation and above-ground structures and to produce high-resolution DTMs and DFMs for GIS-based analysis. Results reveal a markedly more structured landscape in wooded areas than previously documented, including extensive terracing systems, mobility corridors, funerary districts with rock-cut hypogea, and traces of later productive activities. The study highlights both the potential and the limits of high-density UAV-LiDAR and ML-based processing, stressing the need for targeted ground validation in Mediterranean under-canopy contexts.

The application of high-resolution drone LiDAR reveals new potential to detect and interpret subtle archaeological features in Mediterranean forested landscapes, where dense vegetation and low-relief topography strongly limit traditional survey methods. This paper presents preliminary results from an integrated archaeological and geomorphological analysis of drone-derived LiDAR data over the urban landscape of Roselle and its environs (southern Tuscany). Using high-resolution digital terrain models (DTMs) and digital feature models (DFMs), supported by targeted ground verification and geomorphological mapping, we identified and mapped a previously unknown western necropolis comprising more than 50 round barrows, features that were entirely invisible in conventional aerial imagery. By contrast, a known southern necropolis shows markedly lower visibility in the LiDAR data despite comparable data quality and vegetation cover. Comparison of these two funerary areas demonstrates that funerary architecture, substrate lithology, and geomorphological processes interact to govern archaeological visibility. Round barrows cut directly into outcropping bedrock produce stable, long-lived microtopographic anomalies, whereas masonry tombs affected by colluvial processes tend to be progressively obscured and smoothed. These results underscore the necessity of integrating geomorphological analysis into LiDAR-based archaeological interpretation and highlight geomorphology as a key control on the long-term preservation and detectability of funerary landscapes in Mediterranean settings.

The Monti Aurunci Regional Park, located in southern Lazio, Italy, is renowned for its geological and naturalistic features as well as its archaeological significance. This area hosts a wealth of archaeological sites covering from pre-Roman and Roman periods to the modern era, many of which remain largely unexplored. These sites are currently being investigated as part of the Monti Aurunci Project (MAP, https://www.archeologiadiffusa.org/2022/09/17/ map/), an initiative led by the University for Foreigners of Siena. Among the notable sites in this region is the multi-layered and abandoned hillfort known as ‘Le Mura di Campello’. How- ever, dense forest cover significantly hinders the identification, interpretation, and mapping of archaeological remains in the area. Furthermore, the lack or low quality of existing datasets limits their usability for archaeological purposes. To address these challenges, a drone-based LiDAR survey was conducted in the winter of 2023, yielding high-resolution data that have proven invaluable for archaeological analysis. With an average point density of 142 points per square meter, the LiDAR data facilitated the identification of numerous archaeological features, enriching the understanding of the Monti Aurunci’s cultural heritage. Over 100 pre- viously undocumented features were mapped, including terracing systems, hillforts, dwellings, walls, and road system. The results obtained have refined our understanding of the historical settlement dynamics in the Monti Aurunci area and opened the door to new methodological approaches, offering promising future research directions.