This research employs machine learning (Mask Region-Based Convolutional Neural Networks [Mask R-CNN]) and cluster analysis (Density-based spatial clustering of applications with noise [DBSCAN]) to identify more than 20,000 relict charcoal hearths (RCHs) organized in large “fields” within and around State Game Lands (SGLs) in Pennsylvania. This research has two important threads that we hope will advance the archaeological study of landscapes. The first is the significant historical impact of charcoal production, a poorly understood industry of the late eighteenth to early twentieth century, on the historic and present landscape of the United States. Although this research focuses on charcoal production in Pennsylvania, it has broad application for both identifying and contextualizing historical charcoal production throughout the world and for better understanding modern charcoal production. The second thread is the use of open data, open source, and open access tools to conduct this analysis, as well as the open publication of the resultant data. Not only does this research demonstrate the significance of open access tools and data but the open publication of our code as well as our data allow others to replicate our work, to tweak our code and protocols for their own work, and reuse our results.

As the use of large-scale radiocarbon datasets becomes more common and applications of Bayesian chronological modeling become a standard aspect of archaeological practice, it is imperative that we grow a community of both effective users and consumers. Indeed, research proposals and publications now routinely employ Bayesian chronological modeling to estimate age ranges such as statistically informed starts, ends, and spans of archaeological phenomena. Although advances in interpretive techniques have been widely adopted, sampling strategies and determinations of appropriate sample sizes for radiocarbon data remain generally underdeveloped. As chronological models are only as robust as the information we feed into them, formal approaches to assessing the validity of model criteria and the appropriate number of radiocarbon dates deserve attention. In this article, through a series of commonly encountered scenarios, we present easy-to-follow instructions for running simulations that should be used to inform the design and construction of chronological models.

This article introduces datplot, an R package designed to prepare chronological data for visualization, focusing on the treatment of objects dated to overlapping periods of time. Datplot is suitable for all disciplines in which scientists long for a synoptic method that enables the visualization of the chronology of a collection of heterogeneously dated objects. It is especially helpful for visualizing trends in object assemblages over long periods of time—for example, the development of pottery styles—and it can also assist in the dating of stratigraphy. As both authors come from the field of classical archaeology, the examples and case study demonstrating the functionality of the package analyze classical materials. In particular, we focus on presenting an assemblage of epigraphic evidence from Bithynia (northwestern Turkey), with a microregional focal point in the territory of Nicaea (modern Iznik). In the article, we present the internal methodology of datplot and the process of preparing a dataset of categorically and numerically dated objects. We demonstrate visualizing the data prepared by datplot using kernel density estimation and compare the outcome with more established methods such as histograms and line graphs.

The documentation and analysis of archaeological lithics must navigate a basic tension between examining and recording data on individual artifacts or on aggregates of artifacts. This poses a challenge both for artifact processing and for database construction. We present here an R Shiny solution that enables lithic analysts to enter data for both individual artifacts and aggregates of artifacts while maintaining a robust yet flexible data structure. This takes the form of a browser-based database interface that uses R to query existing data and transform new data as necessary so that users entering data of varying resolutions still produce data structured around individual artifacts. We demonstrate the function and efficacy of this tool (termed the Queryable Artifact Recording Interface [QuARI]) using the example of the Stelida Naxos Archaeological Project (SNAP), which, focused on a Paleolithic and Mesolithic chert quarry, has necessarily confronted challenges of processing and analyzing large quantities of lithic material.

The collection of 3D point data is a common bottleneck for archaeological excavations despite an increasing range of powerful spatial data collection technologies. Total stations often require a dedicated operator, and they are optimal for excavation-level data collection over relatively short line-of-site distances. Precision Global Navigation Satellite Systems (GNSS) require reliable communication with constellations of distant satellites and may not be accurate enough for all data recording contexts. A new category of spatial data collection hardware, called Indoor Positioning Systems (IPS), or “indoor GPS,” has the potential to provide a more cost-effective and efficient approach to the collection of point data during excavations by making 3D point data collection widely available and accessible. Additionally, such systems may allow greater detail in digital field data recording by enabling the collection of shape data via continuous recording. In this article, we present one such IPS system—the Marvelmind IPS—discuss its potential value and limitations, and provide a case study of a field test of the system at the Chalcolithic (4600–3600 BC) site of Horvat Duvshan, Israel.

The production of three-dimensional (3D) digital meshes of surface and computed tomographic (CT) data has become widespread in morphometric analyses of anthropological and archaeological data. Given that processing methods are not standardized, this leaves questions regarding the comparability of processed and digitally curated 3D datasets. The goal of this study was to identify those processing parameters that result in the most consistent fit between CT-derived meshes and a 3D surface model of the same human mandible. Eight meshes, each using unique thresholding and smoothing parameters, were compared to assess whole-object deviations, deviations along curves, and deviations between specific anatomical features on the surface model when compared with the CT scans using a suite of comparison points. Based on calculated gap distances, the mesh that thresholded at “0” with an applied smoothing technique was found to deviate least from the surface model, although it is not the most biologically accurate. Results have implications for aggregated studies that employ multimodal 3D datasets, and caution is recommended for studies that enlist 3D data from websites and digital repositories, particularly if processing parameters are unknown or derived for studies with different research foci.

Often understudied by archaeologists, ground stone tools (GST) were ubiquitous in the ancient Maya world. Their applications ranged from household tools to ceremonial equipment and beyond. Little attention has been focused on chemically sourcing the raw stone material used in GST production, largely because these tools were fashioned out of igneous or sedimentary rock, which can present characterization challenges. And, although portable X-ray fluorescence (pXRF) has been applied widely to source obsidian, the utility of pXRF for geochemically sourcing other kinds of stone remains underexplored. We present a small-scale application of pXRF for determining granite provenance within a section of the Middle Belize Valley in Belize, Central America. Belize is an ideal location to test chemical sourcing studies of granite because there are only three tightly restricted and chemically distinct sources of granite in the country, from which the overwhelming majority of granite for ancient tool production derived. The method described here demonstrates that successful and accurate geological characterizations can be made on granite GST. This cutting-edge sourcing technique has the potential to be more widely applied in other regions to reveal deeper connections between the sources of GST production and sites of consumption across space and through time.

From 2016 to 2019, the University of Hawai‘i West O‘ahu conducted archaeological field schools at Honouliuli National Historic Site to teach our students basic archaeological skills. Because the site was the largest Japanese and Japanese American concentration camp on O‘ahu, the field school initiated a program related to social justice and democratic principles for the imprisonment of US citizens and legal residents based on racial and national profiling. The demography of O‘ahu created a special bond to the incarcerees’ stories and the students of Asian and Hawaiian descent. Through field trips, student discussion, and curriculum development, we focused on the pedagogical benefit of experiential learning. Field trips to the National Park Service's World War II Valor in the Pacific Park System on O‘ahu, King Kamehameha V Judiciary History Center, and the Japanese Cultural Center of Hawai‘i allowed the students to see and understand the historical context of the Japanese internment from the mid-nineteenth century, with the development of plantations and early colonialism, to the beginning of World War II and the internment of the more than 300 Japanese and Japanese American—as well as European and Okinawan—civilians and the imprisonment of over 4,000 prisoners of war.

Research indicates that sexual harassment and assault commonly occur during archaeological field research, and students, trainees, and early career professionals are more frequently subjected to harassing behaviors compared to mid-career and senior scientists. Specific to archaeological education, the undergraduate educational requirement of a field school puts students and trainees in situations where harassment historically has been unchecked. We present the results of a systematic content analysis of 24 sets of field school documents. We analyzed these documents with attention to how field school policies, procedures, and language may impact students’ perceptions of their expected behaviors, logistics and means of reporting, and stated policies surrounding sexual harassment and assault. Coding was conducted using an a priori coding scheme to identify practices that should lead to a safe and supportive field learning environment. Our coding scheme resulted in 11 primary codes that we summarized as three primary themes: (1) field school organization and expected student behavior, (2) logistics of the course, and (3) stated policies surrounding sexual harassment and assault. Based on these themes, we provide recommendations to modify field school documents and practices to create a field school that provides safe opportunities for students to learn.

This article shows how to record current events from an archaeological perspective. With a case study from the COVID-19 pandemic in Norway, we provide accessible tools to document broad spatial and behavioral patterns through material culture as they emerge. Stressing the importance of ethical engagement with contemporary subjects, we adapt archaeological field methods—including geolocation, photography, and three-dimensional modeling—to analyze the changing relationships between materiality and human sociality through the crisis. Integrating data from four contributors, we suggest that this workflow may engage broader publics as anthropological data collectors to describe unexpected social phenomena. Contemporary archaeological perspectives, deployed in rapid response, provide alternative readings on the development of current events. In the presented case, we suggest that local ways of coping with the pandemic may be overshadowed by the materiality of large-scale corporate and state response.

Over the past few years our body politic has become increasingly polarized: Republicans versus Democrats, conservatives versus liberals. That polarization filters down to governmental actions, policies, and decisions, evidenced in disagreements over regulation versus deregulation and fossil fuels versus renewable energy. Such polarization—whether legislative, administrative, or judicial and whether at the federal, state, or tribal level—can and does impact the management of our archaeological resources and the way cultural resource management is practiced in the United States. Given that most archaeologists in the United States are employed in cultural resource management, these actions affect their employment. Consequently, it is more critical than ever that archaeologists become cultural resource management and historic preservation advocates. This article discusses the whys and hows of preservation advocacy. Active, science-based advocacy by preservationists can engage governmental decision-makers to give due consideration to cultural resources and their management when making decisions or drafting and voting on legislation. Although the discussion focuses on advocacy at the federal level, the observations and suggestions are applicable at the state and local level.

Full-coverage pedestrian survey to record cultural features on unexplored archaeological landscapes is costly in terms of time, money, and personnel. Over the past two decades, researchers have implemented remote sensing and landscape data collection techniques using unmanned aerial vehicles (UAVs) to combat some of these burdens, but the initial cost of equipment, software, and processing power has hindered the ubiquitous implementation of UAV technology as an accessible companion tool to traditional archaeological survey. This article presents a free and open-source, technology-independent analytical framework for the collection and processing of UAV images to produce high-resolution digital terrain models limited only by the equipment available to the researcher. Results from the free and open-source protocol are directly compared to those produced using proprietary software to illustrate the capabilities of freely available data processing tools for UAV-collected images. By replicating the methods outlined here, researchers should be able to identify and target areas of interest to increase fieldwork efficiency, decrease costs of implementing this technology, and produce high-resolution digital terrain models to conduct spatial analyses that pursue a deeper understanding of cultural landscapes.

Daily data collection during archaeological fieldwork forms the basis for later interpretation and analysis. Across the world, we observe a wide variety of digital data collection methods and tools employed during fieldwork. Here, we detail the daily practices at four recent survey and excavation projects in the South Caucasian country of Armenia. As archaeology continues to become ever more digital, it is useful to consider these day-to-day recording processes at a typical field project. We provide details on both the types of data collected and the ways they are collected so as to foreground these topics. Finally, we reflect on how our work is currently impacted by digital changes and how it may continue to change in the future.