Investigating Luoyang by Remote Sensing: First Results

  • Fulong Chen
  • Nicola Masini
  • Enzo Rizzo
  • Ruixia Yang
  • Gerardo Romano
  • Antonio Pecci
  • Rosa LasaponaraEmail author
Part of the Geotechnologies and the Environment book series (GEOTECH, volume 16)


Since the launch of the Silk Road Economic Belt (SREB) initiative in China, archaeological prospection has been increasingly emphasized by archaeologists, scientists, and government officials to uncover the civilization of the past and the evidence of the friendship between West and East. Compared with traditional field archaeology, remote sensing is an irreplaceable tool in archaeological investigations, taking advantage of large spatial coverage and high-spectral sensitivity to anomalies linking the occurrence of buried relics. In the framework of a Chinese–Italian bilateral project entitled “Smart Management of Cultural Heritage Sites in Italy and China: Earth Observation and Pilot Project,” in 2014 we undertook preliminary investigations on some test sites in Han-Wei capital city and Dingding Gate in Luoyang City toassess the performance of remote sensing, including space-borne synthetic aperture radar (SAR), unmanned aerial vehicles (UAV), and the surface geoelectrical method for the detection of archaeological features. The investigations have been planned considering that the characteristics of the expected archaeological features and the subsoil are not ideal for applications based on the use of remote sensing and geophysics. In fact, past archaeological excavations unearthed deep walls built in rammed earth with stone foundations covered by clayey soil. The aim of this preliminary investigation campaign has been to provide indications for a cost-efficient scientific mission to be conducted in the future on wider areas in Luoyang with the prospect of performing archaeological excavations.


SAR ERT UAV Archaeological prospection Luoyang China 



This work was supported by funding from the Hundred Talents Program of the Chinese Academy of Sciences (CAS) (Y5YR0300QM), Youth Director Fund Category-A of Institute of Remote Sensing and Digital Earth, CAS (Y5ZZ02101B), and the Italian Ministry of Foreign Affairs in the framework of the Great Relevance Project “Smart management of cultural heritage sites in Italy and China: Earth observation and pilot projects.”

Author Contributions Fulong Chen, Nicola Masini, and Rosa Lasaponara did the SAR data processing and methodology development. Fulong Chen together with Nicola Masini designed the research. UAV surveys have been performed by Ruixia Yang and processed by Antonio Pecci. Geophysical data have been acquired and processed by Enzo Rizzo and Gerardo Romano. Fulong Chen, Nicola Masini, Rosa Lasaponara, and Enzo Rizzo have interpreted the results of remote sensing and geophysical investigations. Fulong Chen and Nicola Masini drafted the manuscript. All authors contributed to the field campaign as well as the finalization of this paper.


  1. AgisoftPhotoScan User Manual (2014) Professional edition, version 1.1Google Scholar
  2. Buck PE, Sabol DE, Alan R, Gillespie AR (2003) Sub-pixel artefact detection using remote sensing. J Archaeol Sci 30:973–989CrossRefGoogle Scholar
  3. Capozzoli L, Caputi A, De Martino G, Giampaolo V, Luongo R, Perciante F, Rizzo E (2015) Electrical and electromagnetic techniques applied to an archaeological framework reconstructed in laboratory, 8th International workshop on advanced ground penetrating Radar – IWAGPR 2015, Florence, Italy, 7–10 July, 2015.Google Scholar
  4. Cavalli RM, Colosi F, Palombo A, Pignatti S, Poscolieri M (2007) Remote hyperspectral imagery as a support archaeological prospection. J Cult Herit 8:272–283CrossRefGoogle Scholar
  5. Chen L, Li Y, Shi Z, Xie X (2004) Excavation report on the dingding gate. Chinese Archaeol 6:87–94Google Scholar
  6. Chen F, Lasaponara R, Masini N (2015a) An overview of satellite synthetic aperture radar remote sensing in archaeology: From site detection to monitoring. J Cult Herit
  7. Chen F, Masini N, Yang R, Milillo P, Feng D, Lasaponara R (2015b) A space view of radar archaeological marks: first applications of COSMO-SkyMed X-band data. Remote Sens 7(1):24–50. doi: 10.3390/rs70100024 CrossRefGoogle Scholar
  8. Chen F, Masini N, Liu J, You J, Lasaponara R (2016) Multi-frequency satellite radar imaging of cultural heritage: the case studies of the Yumen Frontier Pass and Niya ruins in the Western regions of the silk road corridor. Int J Digit Earth. doi: 10.1080/17538947.2016.1181213 Google Scholar
  9. Chianese D, Lapenna V, Di Salvia S, Perrone A, Rizzo E (2010) Joint geophysical measurements to investigate the Rossano of Vaglio archaeological site (Basilicata Region, Southern Italy). J Archaeol Sci 37:2237–2244CrossRefGoogle Scholar
  10. Crawford O G S (1929) Air photography for archaeologists. Ordnance survey professional papers, new series, 12. HMSO, SouthamptonGoogle Scholar
  11. Keay SJ, Parcak SH, Strutt KD (2014) High resolution space and ground-based remote sensing and implications for landscape archaeology: the case from Portus, Italy. J Archaeol Sci 52:277–292CrossRefGoogle Scholar
  12. Lasaponara R, Masini N (2013) Satellite synthetic aperture radar in archaeology and cultural landscape: an overview. Archaeol Prospect 20:71–78. doi: 10.1002/arp.1452 CrossRefGoogle Scholar
  13. Lasaponara R, Masini N, Pecci A, Perciante F, Pozzi Escot D, Rizzo E, Scavone M, Sileo M (2016) Qualitative evaluation of COSMO SkyMed in the detection of earthen archaeological remains: The case of Pachamacac (Peru). J Cult Herit. doi: 10.1016/j.culher.2015.12.010
  14. Lee J-S (1980) Digital image enhancement and noise filtering by use of local statistics. IEEE Trans Pattern Anal Mach Intell 2:165–168CrossRefGoogle Scholar
  15. Masini N, Lasaponara R (2007) Investigating the spectral capability of QuickBird data to detect archaeological remains buried under vegetated and not vegetated areas. J Cult Herit 8:53–60CrossRefGoogle Scholar
  16. Neitzel F, Klonowski J (2011) Mobile 3D mapping with a low-cost UAV system. Int Arch Photogramm Remote Sens Spatial Inf Sci XXXVIII-1/C22:39–44Google Scholar
  17. Nex F, Remondino F (2013) UAV for 3D mapping applications: a review. Appl Geomat 6:1–15CrossRefGoogle Scholar
  18. Rizzo E, Chianese D, Lapenna V (2005) Integration of magnetometric, GPR and geoelectric measurements applied to the archaeological site of Viggiano (Southern Italy, Agri Valley-Basilicata). Near Surface Geophys 3:13–19CrossRefGoogle Scholar
  19. Rowlands A, Sarris A (2007) Detection of exposed and subsurface archaeological remains using multi-sensor remote sensing. J Archaeol Sci 34:795–803CrossRefGoogle Scholar
  20. Tapete D, Cigna F (2016) Chapter 5: SAR for landscape archaeology. In: Masini N, Soldovieri F (eds) Sensing the past. Geoscience and sensing technologies for cultural heritage. Springer, Cham, pp 101–116, chapter 5Google Scholar
  21. Westoby MJ, Brasington J, Glasser NF, Hambrey MJ, Reynolds JM (2012) ‘Structure-from-Motion’ photogrammetry: a low-cost, effective tool for geoscience applications. Geomorphology 179:300–314CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Fulong Chen
    • 1
    • 2
  • Nicola Masini
    • 3
  • Enzo Rizzo
    • 4
  • Ruixia Yang
    • 1
    • 2
  • Gerardo Romano
    • 4
    • 5
  • Antonio Pecci
    • 6
  • Rosa Lasaponara
    • 7
    Email author
  1. 1.Key Laboratory of Digital Earth ScienceInstitute of Remote Sensing and Digital Earth, Chinese Academy of SciencesBeijingChina
  2. 2.International Centre on Space Technologies for Natural and Cultural Heritage Under the Auspices of UNESCOBeijingChina
  3. 3.CNR-IBAM Institute for Archaeological and Monumental HeritageTito ScaloItaly
  4. 4.Institute of Methodologies for Environmental Analysis, National Research CouncilTito ScaloItaly
  5. 5.University of BariTito ScaloItaly
  6. 6.Institute for Archaeological and Monumental Heritage, National Research CouncilTito ScaloItaly
  7. 7.CNR-IMAA, Institute of Methodologies for Environmental Analysis85050 Tito ScaloItaly

Personalised recommendations