Object‐based image analysis (OBIA) is a method of assessing remote sensing data that
uses morphometric and spectral parameters simultaneously to identify features in remote …

Airborne LiDAR is a widely accepted tool for archaeological prospection. Over the last
decade an archaeology-specific data processing workflow has been evolving, ranging from …

Computer-aided methods for the automatic detection of archaeological objects are needed
to cope with the ever-growing set of largely digital and easily available remotely sensed …

Although the history of automated archaeological object detection in remotely sensed data is
short, progress and emerging trends are evident. Among them, the shift from rule-based …

This article presents results of a case study within a project that seeks to develop heavily
automated analysis of digital topographic data to extract archaeological information and to …

In this paper, we report the results of our work on automated detection of qanat shafts on the
Cold War-era CORONA Satellite Imagery. The increasing quantity of air and space-borne …

The objective of this project is to create a new implementation of a deep learning model that
uses digital elevation data to detect shipwrecks automatically and rapidly over a large …

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 …

Sixty-six new archaeological sites have been discovered thanks to the combined use of
different remote sensing techniques and open access geospatial datasets (mainly aerial …

This article presents a novel deep learning method for semi-automated detection of historic
mining pits using aerial LiDAR data. The recent emergence of national scale remotely …