Airborne LiDAR acquisition, post-processing and accuracy-checking for a 3D WebGIS of Copan, Honduras

Authors

Jennifer von Schwerin, German Archaeological InstituteFollow
Heather Richards-Rissetto, University of Nebraska-LincolnFollow
Fabio Remondino, Bruno Kessler FoundationFollow
Maria Grazia Spera, Bruno Kessler FoundationFollow
Michael Auer, University of HeidelbergFollow
Nicolas Billen, University of HeidelbergFollow
Lukas Loos, University of HeidelbergFollow
Laura Stelson, University of BonnFollow
Markus Reindel, German Archaeological Institute

Document Type

Article

Date of this Version

2-2016

Citation

von Schwerin, J., H. Richards-Rissetto, F. Remondino, M. Grazia Spera, M. Auer, N. Billen, L. Loos, L. Stelson, M. Reindel. 2016. Airborne LiDAR acquisition, post-processing and accuracy-checking for a 3D WebGIS of Copan, Honduras. Journal of Archaeological Science: Reports. Volume 5. February 2016. Pages 85-104. http://dx.doi.org/10.1016/j.jasrep.2015.11.005

Comments

Copyright © 2015 Elsevier Ltd. Used by permission.

Abstract

Archaeological projects increasingly collect airborne LiDAR data to use as a remote sensing tool for survey and analysis. Publication possibilities for LiDAR datasets, however, are limited due to the large size and often proprietary nature of the data. Fortunately, web-based, geographic information systems (WebGIS) that can securely manage temporal and spatial data hold great promise as virtual research environments for working with and publishing LiDAR data. To test this and to obtain new data for archaeological research, in 2013, the MayaArch3D Project (www.mayaarch3d.org) collected LiDAR data for the archaeological site of Copan, Honduras. Results include: 1) more accurate archaeological maps, 2) identification of unrecorded archaeological features, 3) an assessment of combining LiDAR and ground-checking to increase data accuracy in ecologically and topographically diverse landscapes, and 4) newLiDAR datasets that are hosted in a 3DWebGIS and integrated with other archaeological data to enhance data accessibility and collaborative research.