UAV-Based Remote Sensing for Detection and Visualization of Partially-Exposed Underground Structures in Complex Archaeological Sites

Abstract

The utilization of remote sensing technologies for archaeology was motivated by their ability to map large areas within a short time at a reasonable cost. With recent advances in platform and sensing technologies, uncrewed aerial vehicles (UAV) equipped with imaging and Light Detection and Ranging (LiDAR) systems have emerged as a promising tool due to their low cost, ease of deployment/operation, and ability to provide high-resolution geospatial data. In some cases, archaeological sites might be covered with vegetation, which makes the identification of below-canopy structures quite challenging. The ability of LiDAR energy to travel through gaps within vegetation allows for the derivation of returns from hidden structures below the canopy. This study deals with the development and deployment of a UAV system equipped with imaging and LiDAR sensing technologies assisted by an integrated Global Navigation Satellite System/Inertial Navigation System (GNSS/INS) for the archaeological mapping of Dana Island, Turkey. Data processing strategies are also introduced for the detection and visualization of underground structures. More specifically, a strategy has been developed for the robust identification of ground/terrain surface in a site characterized by steep slopes and dense vegetation, as well as the presence of numerous underground structures. The derived terrain surface is then used for the automated detection/localization of underground structures, which are then visualized through a web portal. The proposed strategy has shown a promising detection ability with an F1-score of approximately 92%.

Hash Encoding and Brightness Correction in 3D Industrial and Environmental Reconstruction of Tidal Flat Neural Radiation

“…In Formula (11), ⊕ denotes the bit-wise XOR operation, W is the hash table's maximum size, and π is a prime number (π 1 = 1, π 2 = 2,654,435,761, and π 3 = 805,459,861).…”

“…Unmanned aerial vehicles (UAVs), renowned for their agility, versatility, speed, and cost-effectiveness, serve as invaluable platforms for aerial photography, enabling the swift capture of high-resolution images with vast potential for generating geographic mapping data [ 1 , 2 ]. Over recent decades, UAV photogrammetry has found applications across various disciplines within the geosciences, including sedimentology [ 3 , 4 ], earthquake geology [ 5 , 6 ], structural geology [ 7 ], geomorphology [ 8 ], engineering geology [ 9 , 10 ], archaeology [ 11 , 12 ], forestry [ 13 , 14 ], and landscape evolution and natural hazards [ 15 , 16 ]. Innovative techniques such as RTK or PPK aero photogrammetric surveying have yielded numerous accurate 3D models [ 7 , 17 ].…”

Automated Fine-Scale Forest Inventory Using Backpack Lidar – A Strategy Based on Feature Extraction, Matching, and Tracking From Integrated Scans

“…Tree trunks are modeled as cylindrical features to provide horizontal control and ground patches are used as plane features to provide vertical control. To extract these features, initially, the modified Cloth Simulation Filter (mCSF) (Shin et al, 2023) is employed to derive a Digital Terrain Model (DTM) for each IS. Considering a 0.2m for bare-earth threshold, the points are then divided into above-ground and bare-earth points, which are utilized for tree trunk and ground patch extraction, respectively.…”

A Case Study of the Integration of Ground-Based and Drone-Based Ground-Penetrating Radar (GPR) for an Archaeological Survey in Hulata (Israel): Advancements, Challenges, and Applications

“…Using real-time kinematic (RTK) GPS positioning facilitates the replication of precise survey paths [24]. It is incorporated with signal processing techniques like cross-correlation-based background subtraction and interference suppression, ensuring the accurate identification of subsurface targets [25,26]. Drone-borne GPR enables the mapping of geotechnical properties such as the soil moisture [27] and field-scale soil electrical conductivity [28].…”