tDAR Logo tDAR digital antiquity

Automated archaeological feature extraction from LiDAR.

Author(s): Florencia Pezzutti ; Christopher Fisher ; Conrad Albrecht ; Sharathchandra Pankanti ; Francesca Rossi

Year: 2017

» Downloads & Basic Metadata

Summary

Here we present preliminary results from a collaborative project between archaeologists and IBM research scientists focused on developing a cost-efficient algorithm for the automated recognition of archaeological features (objects) from LiDAR data.

Our research focuses on challenges of: 1) multidisciplinary work integrating expertise from diverse disciplines, 2) identifying complex archaeological features in the context of a dense urban site in a rugged topographic setting, and 3) developing a machine learning algorithm to efficiently identify archaeological features. We will present details of formulation of our approach in addressing the above-mentioned research challenges and provide preliminary results on real archeological data which we find promising.

We believe this improved LiDAR object feature recognition algorithm will ultimately be a resourceful and cost efficient (both in money and time) tool for future archaeologists conducting archaeological surveys and mapping through the application of LiDAR.


This Resource is Part of the Following Collections


Cite this Record

Automated archaeological feature extraction from LiDAR.. Florencia Pezzutti, Christopher Fisher, Conrad Albrecht, Sharathchandra Pankanti, Francesca Rossi. Presented at The 81st Annual Meeting of the Society for American Archaeology, Vancouver, British Columbia. 2017 ( tDAR id: 431329)


Keywords


Spatial Coverage

min long: -107.271; min lat: 12.383 ; max long: -86.353; max lat: 23.08 ;

Record Identifiers

Abstract Id(s): 16374

Arizona State University The Andrew W. Mellon Foundation National Science Foundation National Endowment for the Humanities Society for American Archaeology Archaeological Institute of America