Automated mound detection using lidar and object-based image analysis in Beaufort County, South Carolina

Abstract

The study of precontact anthropogenic mounded features-earthen mounds, shell heaps, and shell rings-in the American Southeast is stymied by the spotty distribution of systematic surveys across the region. Many extant, yet unidentified, archaeological mound features continue to evade detection due to the heavily forested canopies that occupy large areas of the region, making pedestrian surveys difficult and preventing aerial observation. Object-based image analysis (OBIA) is a tool for analyzing light and radar (lidar) data and offers an inexpensive opportunity to address this challenge. Using publicly available lidar data from Beaufort County, South Carolina, and an OBIA approach that incorporates morphometric classification and statistical template matching, we systematically identify over 160 previously undetected mound features. This result improves our overall knowledge of settlement patterns by providing systematic knowledge about past landscapes.

Object‐based image analysis: a review of developments and future directions of automated feature detection in landscape archaeology

“…Morphological variables used for classification include: Circularity (Davis et al, ; Freeland et al, ; Witharana et al, ) Rectangularity (Zingman et al, ) Area (Davis et al, ; Magnini et al, ; Witharana et al, ) Length and width (Magnini et al, ; Toumazet, Vautier, Roussel, & Dousteyssier, ) Size (Cerrillo‐Cuenca, ; Davis et al, ; Zingman et al, ) Curvature (Cerrillo‐Cuenca, ) Edge detection (Traviglia & Torsello, ; Witharana et al, ; Zingman et al, ) Elevation (Davis et al, ; Guyot et al, ) …”

“…The increase in studies post‐2010 sees a slight diversification in the use of OBIA methods, but as Table shows, most studies use it for the sole purpose of automating the detection of archaeological features (e.g. Davis et al, ; Sevara & Pregesbauer, ; Trier et al, ; Trier & Pilø, ; Verhagen & Drăguţ, ). Some researchers, however, are using OBIA to protect and monitor sites at risk of destruction (e.g.…”

“…Parcak (, 110) claims that automated archaeological site detection is impossible because every archaeological project is dependent on local variables. But local variables are precisely what OBIA can take into consideration when analysing remote sensing data, and regionally specific algorithms are essential for the success of automated prospection (see Davis et al, ). Parcak (,110) goes on to state that computers cannot pick up on the same subtleties in remotely sensed data as humans can by eye.…”

“…However, the very fact that recent studies using automated means have detected sites that manual analysis has overlooked directly challenges this claim (e.g. Davis et al, ; Witharana et al, ).…”

“…In the span of two weeks, Quintus et al () evaluated LiDAR covering approximately 5–10 km 2 , whereas semi‐automated OBIA methods have allowed for the systematic evaluation of LiDAR datasets covering thousands of square kilometres in the same amount of time (e.g. Davis et al, ).…”