Open Access. Powered by Scholars. Published by Universities.®
Social and Behavioral Sciences Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Social and Behavioral Sciences
Mapping Complex Land Use Histories And Urban Renewal Using Ground Penetrating Radar: A Case Study From Fort Stanwix, Tyler Stumpf, Daniel P. Bigman, Dominic J. Day
Mapping Complex Land Use Histories And Urban Renewal Using Ground Penetrating Radar: A Case Study From Fort Stanwix, Tyler Stumpf, Daniel P. Bigman, Dominic J. Day
Anthropology Graduate Research
Fort Stanwix National Monument, located in Rome, NY, is a historic park with a complex use history dating back to the early Colonial period and through the urban expansion and recent economic revitalization of the City of Rome. The goal of this study was to conduct a GPR investigation over an area approximately 1 acre in size to identify buried historic features (particularly buildings) so park management can preserve these resources and develop appropriate educational programming and management plans. The GPR recorded reflection events consistent with our expectations of historic structures. Differences in size, shape, orientation, and depth suggest that …
A 3d Point Cloud Deep Learning Approach Using Lidar To Identify Ancient Maya Archaeological Sites, Heather Richards-Rissetto, David Newton, Aziza Al Zadjali
A 3d Point Cloud Deep Learning Approach Using Lidar To Identify Ancient Maya Archaeological Sites, Heather Richards-Rissetto, David Newton, Aziza Al Zadjali
Department of Anthropology: Faculty Publications
Airborne light detection and ranging (LIDAR) systems allow archaeologists to capture 3D data of anthropogenic landscapes with a level of precision that permits the identification of archaeological sites in difficult to reach and inaccessible regions. These benefits have come with a deluge of LIDAR data that requires significant and costly manual labor to interpret and analyze. In order to address this challenge, researchers have explored the use of state-of-the-art automated object recognition algorithms from the field of deep learning with success. This previous research, however, has been limited to the exploration of deep learning processes that work with only 2D …