Using A.I. Tools in ArcGIS to Identify Mining Features in Northern Georgia

Summary

This is an abstract from the "SAA 2024: Individual Abstracts" session, at the 89th annual meeting of the Society for American Archaeology.

During the course of a cultural resources survey in Bartow County, Georgia for the Georgia Department of Transportation, several features related to past mining activities were identified on the surface. These features, consisting of mining cuts and collapsed tunnels, could be identified from LiDAR available from the USGS. This project takes these ground-truthed mining features and evaluates various A.I. enhanced methods of image and point data classification within ESRI's ArcGIS program for identifying these types of features. The goal is to arrive at a method that will allow the classification of the mining landscape of northern Georgia by identifying likely extant features. The resulting dataset will aid in the planning of cultural resource management activities by identifying areas with a high likelihood of mining related features as well as creating a process that can be applied to other places and landscapes with similar records of mining.

This Resource is Part of the Following Collections

• SAA 2024: Individual Abstracts   •
• Society for American Archaeology 89th Annual Meeting, New Orleans, LA (2024)

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Record Identifiers

Abstract Id(s): 40203.0