# Virtual Reality in Cultural Heritage: A Setup for Balzi
## 3 Materials and Methods  
### Data Acquisition and Photogrammetry  
The first phase of the Balzi Rossi Museum project endeavor entailed the implementation of photogrammetry, a pivotal process for both the preservation of the site and the development of a VR narrative. To this purpose, we executed every stage of photogrammetry, from data acquisition through drones to 3D point cloud calculations and 3D mesh generation, using several kinds of high-precision sensors for multiphase multi-spectral data collection. This is the list of drones and related sensing devices used in three different campaigns, performed between September 2021 and November 2022:  
* DJI Matrice 210 V2 RTK with thermal sensors and 4K DJI cameras: An enterprise-level drone, equipped with Zenmuse Xt2 thermal sensors and Z30 ultra-HD cameras, and RTK Ground Station to improve the GPS precision. * DJI Phantom P4 multispectral RTK: A compact prosumer-level drone, equipped with custom 5 + 1 multispectral sensors (NIR 0.75-1.4 \(\upmu\)m, Red-Edge, R, G, B channels and visible light), originally designed for precision agriculture and able to capture images at various wavelengths to facilitate the discovery of engravings inside the Balzi Rossi caves. * DJI Matrice 300 RTK with Zenmuse LIDAR L1: An enterprise-level drone capable of carrying heavy instrumentation like the Zenmuse L1, which integrates a Livox Lidar module, a high-accuracy IMU, and a camera with a 1-inch CMOS on a three-axis stabilized gimbal. It also features artificial intelligence for enhanced stability and the OcuSync video transmission system for rapid data transfer. * DJI Mini: An ultra-compact consumer-level drone with a 12 MP 4K camera, used to take pictures in very cluttered spaces like the top and inner parts of the caves. These drones collected approximately 4000 images clustered in 11 groups and +100 million points of LIDAR scans over three different flights with RTK precision of +/ -0.5 cm horizontally and +/ -1.5 cm vertically. Multispectral data acquisition has been tested across various wavelengths and modes. Aerial data acquisitions made during the day with drones were affected by sunlight shadows, dynamically changing throughout the day because the Balzi Rossi cliffs are exposed to the south. Therefore, discovered candidate findings during aerial inspections were analyzed in detail within the caves during nightly data captures with a custom fixed installation based on four high-precision sensors (NIR, R, G, B) geometrically aligned with a professional Panasonic Lumix DC-S5 and encircled within coherent light LED panels operating at 4500 Kelvin degrees. All of the collected data were processed in two distinct ways to meet the conservation and communication objectives of the Balzi Rossi Museum project. **For Preservation**: The data processing for site conservation employed two main softwares:DJI Terra V.4.0: This proprietary software from DJI facilitates mission planning, area mapping, and processing of data collected by drones. It allowed for the creation of a three-dimensional, georeferenced virtual model, as well as the autonomous generation of a 3D model from the data. * Cloud Compare V 2.12.0: Used for processing point clouds and 3D models, this software turns a set of points with spatial coordinates into detailed three-dimensional models. The photogrammetry provided an extremely precise point cloud. By establishing a reference scale based on the distance between railway tracks, we achieved a digital model with millimeter-level precision, geolocated and ready for future analysis and studies and allowing precise monitoring of changes over time. **For Communication**: The second process, focused on communication, aimed to produce the VR experience. The data processed with the previous software were not directly compatible with the Unreal Engine graphics engine, used for VR. Moreover, most of the data was superfluous for the required 3D model.