Drone-based magnetometer prospection for archaeology

被引:5
|
作者
Stele, Andreas [1 ,4 ]
Kaub, Leon [2 ]
Linck, Roland [1 ,2 ]
Schikorra, Markus [3 ]
Fassbinder, Jorg W. E. [2 ]
机构
[1] Bavarian State Dept Monuments & Sites BLfD, Munich, Germany
[2] Ludwig Maximilians Univ Munchen, Geophys Dept Earth & Environm Sci, Munich, Germany
[3] Sensys Sensor & Systemtechnol GmbH, Bad Saarow Pieskow, Germany
[4] Ref ZV Archaeol Prospect, Bavarian State Dept Monuments & Sites, Hofgraben 4, D-80539 Munich, Germany
关键词
Uncrewed aerial systems magnetometry; Drone-based vs ground-based magnetometry; Archaeological prospection; 3-Axis fluxgate magnetometers; Caesium total field magnetometers; Frequency component analysing; Sensor resolution tests;
D O I
10.1016/j.jas.2023.105818
中图分类号
Q98 [人类学];
学科分类号
030303 ;
摘要
Magnetometry is one of the most efficient and successful methods of archaeological prospection. Drone-based prospecting is increasingly being used in many fields of remote sensing but with respect to magnetometry, with rather poor results. For magnetic surveys, drone prospecting comes with the problem that magnetic and mechanical disturbances originating from the aircraft decrease the quality of the measurements.Here we present the adaptation of a commercial three-axis fluxgate magnetometer setup, which can be suit-able for archaeological prospection, after applying appropriate filter methods and minimising the flying altitude and speed. For approval of the system, we performed drone-based surveys in high spatial resolution (50 cm line spacing) at constant, ultra-low sensor altitudes of 45 +/- 10 cm and 75 +/- 10 cm. We chose an archaeological site from the roman period as survey site (3.8 ha), where high-quality ground-based caesium magnetometer data was available. This allows us to demonstrate the first detailed comparison of drone-based and ground-based magnetic survey data for archaeology. For further evaluation, the influence of the drone on the measurements is assessed, drift and sensor resolution checks are carried out, and suitable data filtering methods are evaluated.Our results show that we can detect main archaeological features such as ditches, pits, fireplaces and remnants of stone fundaments with the drone-based setup, which are the relevant structures for the majority of archae-ological prospections worldwide. Further, we can prove that the data quality can significantly be increased by lowering the flight altitude and speed. We conclude that drone-based magnetometry serves above all to cover large and inaccessible areas in short time. Our findings are a first step towards the development of standards for drone-based archaeological prospection approaches.
引用
收藏
页数:11
相关论文
共 50 条
  • [31] Wireless Powering of Drone-Based MANETs for Disaster Zones
    Calvo, Jose Angel Leon
    Alirezaei, Gholamreza
    Mathar, Rudolf
    [J]. 2017 IEEE INTERNATIONAL CONFERENCE ON WIRELESS FOR SPACE AND EXTREME ENVIRONMENTS (WISEE), 2017, : 98 - 103
  • [32] TOOLS OF THE TRADE Drone-based surveys of mineral deposits
    Jackisch, Robert
    [J]. NATURE REVIEWS EARTH & ENVIRONMENT, 2020, 1 (04) : 187 - 187
  • [33] Drone-Based Warehouse Inventory Management with IoT for Perishables
    Piramuthu, Selwyn
    [J]. SMART SERVICES SUMMIT, 2022, : 13 - 21
  • [34] Drone-based 3DInISAR: Experimental Results
    Giusti, Elisa
    Ghio, Selenia
    Martorella, Marco
    [J]. 2023 IEEE RADAR CONFERENCE, RADARCONF23, 2023,
  • [35] THERMAL PROSPECTION FOR ARCHAEOLOGY
    BELLERBY, TJ
    NOEL, M
    BRANIGAN, K
    [J]. GEOPHYSICAL JOURNAL-OXFORD, 1988, 92 (03): : 551 - 551
  • [36] Drone-based power-line tracking system
    Jeong J.
    Kim J.
    Yoon T.S.
    Park J.B.
    [J]. Park, Jin Bae (jbpark@yonsei.ac.kr), 2018, Korean Institute of Electrical Engineers (67): : 773 - 781
  • [37] Drone-Based Highway-VANET and DAS Service
    Seliem, Hafez
    Shahidi, Reza
    Ahmed, Mohamed Hossam
    Shehata, Mohamed S.
    [J]. IEEE ACCESS, 2018, 6 : 20125 - 20137
  • [38] Autonomous Drone-Based Antenna Radiation Pattern Characterization
    Owais, Muhammad
    Midtiby, Henrik
    Trifon, Diana
    Hasan, Agus
    [J]. 2022 INTERNATIONAL CONFERENCE ON UNMANNED AIRCRAFT SYSTEMS (ICUAS), 2022, : 207 - 213
  • [39] Reliability of marine faunal detections in drone-based monitoring
    Colefax, Andrew P.
    Butcher, Paul A.
    Pagendam, Daniel E.
    Kelaher, Brendan P.
    [J]. OCEAN & COASTAL MANAGEMENT, 2019, 174 : 108 - 115
  • [40] DroneSURF: Benchmark Dataset for Drone-based Face Recognition
    Kalra, Isha
    Singh, Maneet
    Nagpal, Shruti
    Singh, Richa
    Vatsa, Mayank
    Sujit, P. B.
    [J]. 2019 14TH IEEE INTERNATIONAL CONFERENCE ON AUTOMATIC FACE AND GESTURE RECOGNITION (FG 2019), 2019, : 207 - 213