Articles by Fabio Remondino

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 Tiber Valley Project aims to create a series of digital applications for 3D reconstructing, visualization and real time browsing of the ancient and current Tiber Valley landscape (particularly for the Villa dei Volusii and Lucus Feroniae areas), in four different historical phases. In this perspective, the first problem to face is the need for a valid methodology for ancient landscape ecosystem reconstruction, before dealing with monuments and building. On the basis of an intense multi-disciplinary discussion and the previous VH Lab experience in this field, in this article we are presenting a scheme for a standardized reconstruction procedure, where the landscape is built using all available sources and elevation data obtained by a photogrammetry process on historical pictures. Ecosystem areas are then calculated through GIS elaboration in GRASS-GIS environment, through a procedure which may be shared for any situation of historical landscape reconstruction, allowing the matching and the mathematical processing of geographical data aimed to the definition of different ecological areas (both in terms of natural vegetation and cultivated lands). Maps are then created to be imported in procedural landscape generation engines: the last part of the paper focuses on the lack of effective open source software in this field, and a possible proposal implementation in this sense.

The increase of 3D acquisition and modeling techniques applied to archeology is due principally to (i) their capacity to survey archeological artifacts with high precision and a non-contact approach and (ii) the possibility to create 3D digital models useful for data analysis, simulation and preservation. These benefits in terms of knowledge oblige the contemporary archaeologist to acquire a better understanding of 3D acquisition and modeling principles and practice. This evidence arises from the necessity of adopting a common language for experts in 3D data management and archaeologists with the principal aim being the understanding of each other’s requirements and sharing of the purposes of the project. In this article the authors propose a concise but exhaustive explanation of the working principles of active and passive 3D acquisition techniques. For each one a description of instruments and methodologies is developed, pointing out pros and cons of every technique. In conclusion, a sensor fusion approach is presented as an interesting solution to increase the instrument performances while obtaining at the same time a quality improvement of 3D acquisition and modeling results. A final multi-resolution application about Pompeii Forum 3D modeling follows and closes the article.