3D spatial morphological analysis of mound tombs based on LiDAR data

被引:6
|
作者
Yang, Lin [1 ,2 ]
Sheng, Yehua [1 ,2 ]
Pei, Anping [3 ]
Wu, Yi [1 ]
机构
[1] Nanjing Normal Univ, Key Lab Virtual Geog Environm, Minist Educ, 1 Wenyuan Rd, Nanjing, Peoples R China
[2] Nanjing Normal Univ, Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing, Peoples R China
[3] Nanjing Normal Univ, Dept Cultural Rel & Museum, Nanjing, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
LiDAR data; mound tomb; spatial morphological analysis; centripetalism; 3D archaeological models; ARCHAEOLOGICAL RESEARCH; RELIEF MODELS; RECONSTRUCTION; TOOL;
D O I
10.1080/19475683.2020.1780313
中图分类号
P9 [自然地理学]; K9 [地理];
学科分类号
0705 ; 070501 ;
摘要
Mound tombs, popular in the south Yangzi River area in Shang and Zhou Dynasties, are regional cultural remains in China. With the aims of protecting and scientifically analysing cultural relics, laser scanning technology was adopted to study Zhaihuatou mound tombs located in Nonglin Village in Tianwang town, Jiangsu Province. Multiple tombs are held within one mound in good keep and with the typical construction of centripetalism. Accurate tomb LiDAR (Light Detection And Ranging) data were acquired by applying terrestrial laser scanning technology to the field mound excavation. Subsequently, a spatial morphological analysis of the tombs was conducted on the basis of archaeological rules and GIS spatial data processing methods. Using the theory of centripetalism construction of multi-tomb-one-mounds, we proposed an algorithm to determine the concentrated area of the geometric directions of tombs, and centripetalism theory was scientifically validated in comparing results with the excavation data. Spatial data clustering methods were used to analyse and deduce the spatial distribution characteristics of the tombs. We propose and demonstrate that the burial system is in the form of family-clan aggregation, and is useful for developing research on regional burials. Experimental data show that the proposed method is a novel example of how spatial analysis can foster more precise field archaeological excavations on a large scale, and it is significant to study various types of tombs, relics and ruins.
引用
收藏
页码:315 / 325
页数:11
相关论文
共 50 条
  • [41] Motion Analysis and Performance Improved Method for 3D LiDAR Sensor Data Compression
    Tu, Chenxi
    Takeuchi, Eijiro
    Carballo, Alexander
    Miyajima, Chiyomi
    Takeda, Kazuya
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2021, 22 (01) : 243 - 256
  • [42] 3D Building Scene Reconstruction Based on 3D LiDAR Point Cloud
    Yang, Shih-Chi
    Fan, Yu-Cheng
    2017 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS - TAIWAN (ICCE-TW), 2017,
  • [43] Classification of Outdoor 3D Lidar Data Based on Unsupervised Gaussian Mixture Models
    Maligo, Artur
    Lacroix, Simon
    2015 IEEE INTERNATIONAL SYMPOSIUM ON SAFETY, SECURITY, AND RESCUE ROBOTICS (SSRR), 2015,
  • [44] Classification of Outdoor 3D Lidar Data Based on Unsupervised Gaussian Mixture Models
    Maligo, Artur
    Lacroix, Simon
    IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2017, 14 (01) : 5 - 16
  • [45] 3D LOCAL SCALE SOLAR RADIATION MODEL BASED ON URBAN LIDAR DATA
    Redweik, P.
    Catita, C.
    Brito, M. C.
    ISPRS HANNOVER WORKSHOP 2011: HIGH-RESOLUTION EARTH IMAGING FOR GEOSPATIAL INFORMATION, 2011, 39-4 (W19): : 265 - 269
  • [46] Tree species classification of airborne LiDAR data based on 3D deep learning
    Liu M.
    Han Z.
    Chen Y.
    Liu Z.
    Han Y.
    Guofang Keji Daxue Xuebao/Journal of National University of Defense Technology, 2022, 44 (02): : 123 - 130
  • [47] Maize Point Cloud Data Filtering Algorithm Based on Vehicle 3D LiDAR
    Zhang M.
    Miao Y.
    Qiu R.
    Ji Y.
    Li H.
    Li M.
    Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery, 2019, 50 (04): : 170 - 178
  • [48] The LiDAR-Based 3D Stratigraphic Model Calibrated with Limited Borehole Data
    Yeh, Chih-Hsiang
    Lu, Yu-Chen
    Juang, C. Hsein
    Dong, Jia-Jyun
    GEO-RISK 2023: ADVANCES IN MODELING UNCERTAINTY AND VARIABILITY, 2023, 347 : 205 - 213
  • [49] 3D building reconstruction from LiDAR data based on Delaunay TIN approach
    Zhang, Dongdong
    Du, Peijun
    INTERNATIONAL SYMPOSIUM ON LIDAR AND RADAR MAPPING 2011: TECHNOLOGIES AND APPLICATIONS, 2011, 8286
  • [50] Morphological analysis of 3d atom probe data using Minkowski functionals
    Mason, Daniel R.
    London, Andrew J.
    ULTRAMICROSCOPY, 2020, 211