Anthropology Commons^™

The Integration Of Lidar And Legacy Datasets Provides Improved Explanations For The Spatial Patterning Of Shell Rings In The American Southeast, Dylan S. Davis, Robert Dinapoli, Matthew Sanger, Carl P. Lipo

Anthropology Faculty Scholarship

Archaeologists have struggled to combine remotely sensed datasets with preexisting information for landscape-level analyses. In the

American Southeast, for example, analyses of lidar data using automated feature extraction algorithms have led to the identification of over

40 potential new pre-European-contact Native American shell ring deposits in Beaufort County, South Carolina. Such datasets are vital for understanding settlement distributions, yet a comprehensive assessment requires remotely sensed and previously surveyed archaeological data. Here, we use legacy data and airborne lidar-derived information to conduct a series of point pattern analyses using spatial models that we designed to assess the factors that best explain …

The Integration Of Lidar And Legacy Datasets Provides Improved Explanations For The Spatial Patterning Of Shell Rings In The American Southeast, Dylan S. Davis, Robert Dinapoli, Matthew Sanger, Carl Lipo

Anthropology Datasets

Archaeologists have struggled to combine remotely sensed datasets with preexisting information for landscape-level analyses. In the American Southeast, for example, analyses of lidar data using automated feature extraction algorithms have led to the identification of over 40 potential new pre-European-contact Native American shell ring deposits in Beaufort County, South Carolina. Such datasets are vital for understanding settlement distributions, yet a comprehensive assessment requires remotely sensed and previously surveyed archaeological data. Here, we use legacy data and airborne lidar-derived information to conduct a series of point pattern analyses using spatial models that we designed to assess the factors that best explain …

Unveiling The Past: Using Lidar To Discover Lost Archaeological Features In The American Southeast, Dylan S. Davis

GIS Day

Artificial mounds and rings are morphologically heterogeneous. While they share many compositional traits, their outlines on landscapes widely vary across geographic regions. As such, automated identification of these deposits requires the use of algorithms that are capable of evaluating a range of criteria and assessing objects that fall within acceptable ranges for each analyzed attribute. Object-based image analysis (OBIA) is one solution to this problem. Here, I develop a combined OBIA method utilizing two different approaches – multiresolution segmentation and template matching – in order to locate these features semi-automatically. The results of this study indicate the success of this …