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

Author:

Shin Young-Ha1,Shin Sang-Yeop2ORCID,Rastiveis Heidar2ORCID,Cheng Yi-Ting2ORCID,Zhou Tian2ORCID,Liu Jidong2ORCID,Zhao Chunxi2,Varinlioğlu Günder3,Rauh Nicholas K.4,Matei Sorin Adam4,Habib Ayman2ORCID

Affiliation:

1. Department of Geoinformation Engineering, Sejong University, Seoul 05006, Republic of Korea

2. Lyles School of Civil Engineering, Purdue University, West Lafayette, IN 47907, USA

3. Art History, Mimar Sinan Fine Arts University, Istanbul 34427, Turkey

4. College of Liberal Arts, Purdue University, West Lafayette, IN 47907, USA

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%.

Funder

Koç University Stavros Niarchos Foundation Center for Late Antique and Byzantine Studies

Mimar Sinan Fine Arts University Scientific Research Fund

multiple Purdue University grants and awards

Laboratory & University Core Facility Research Equipment Program

College of Liberal arts Aspire program

Purdue University for research activities

Republic of Korea’s MSIT

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

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