Cities and towns have often developed infrastructure that enabled a variety of socio-economic interactions. Street networks within these urban settings provide key access to resources, neighborhoods, ...and cultural facilities. Studies on settlement scaling have also demonstrated that a variety of urban infrastructure and resources indicate clear population scaling relationships in both modern and ancient settings. This article presents an approach that investigates past street network centrality and its relationship to population scaling in urban contexts. Centrality results are compared statistically among different urban settings, which are categorized as orthogonal (i.e., planned) or self-organizing (i.e., organic) urban settings, with places having both characteristics classified as hybrid. Results demonstrate that street nodes have a power law relationship to urban area, where the number of nodes increases and node density decreases in a sub-linear manner for larger sites. Most median centrality values decrease in a negative sub-linear manner as sites are larger, with organic and hybrid urban sites' centrality being generally less and diminishing more rapidly than orthogonal settings. Diminishing centrality shows comparability to modern urban systems, where larger urban districts may restrict overall interaction due to increasing transport costs over wider areas. Centrality results indicate that scaling results have multiples of approximately ⅙ or ⅓ that are comparable to other urban and road infrastructure, suggesting a potential relationship between different infrastructure features and population in urban centers. The results have implications for archaeological settlements where urban street plans are incomplete or undetermined, as it allows forecasts to be made on past urban sites' street network centrality. Additionally, a tool to enable analysis of street networks and centrality is provided as part of the contribution.
Some of the most politically and culturally significant cities in first millennium BC northern Mesopotamia were located in agriculturally marginal landscapes. In order to sustain these settlements, ...variant cultivation techniques were practiced by local populations. Understanding the dynamics and implications of crop management practices requires that socio-ecological variables be addressed over recurrent crop cycles. This paper employs a coupled socio-ecological modeling approach that enables interactions between a quantitative environmental model and an agent-based social model by using the ENKIMDU simulation tool. The reconstructed landscape near the ancient city of Assur is used as the example setting to test the effectiveness of simulated cultivation strategies. These methods include sole dependence on biennial fallow and rainfall, gravity flow irrigation, application of manure, and the integration of all these approaches. Results obtained within ENKIMDU attempt to delineate agricultural constraints and potential benefits of the specific anthropogenic processes and strategies addressed.
Today our societies face great challenges with water, in terms of both quantity and quality, but many of these challenges have already existed in the past. Focusing on Asia, Water Societies and ...Technologies from the Past and Present seeks to highlight the issues that emerge or re-emerge across different societies and periods, and asks what they can tell us about water sustainability. Incorporating cutting-edge research and pioneering field surveys on past and present water management practices, the interdisciplinary contributors together identify how societies managed water resource challenges and utilised water in ways that allowed them to evolve, persist, or drastically alter their environment. The case studies, from different periods, ancient and modern, and from different regions, including Egypt, Sri Lanka, Cambodia, Southwest United States, the Indus Basin, the Yangtze River, the Mesopotamian floodplain, the early Islamic city of Sultan Kala in Turkmenistan, and ancient Korea, offer crucial empirical data to readers interested in comparing the dynamics of water management practices across time and space, and to those who wish to understand water-related issues through conceptual and quantitative models of water use. The case studies also challenge classical theories on water management and social evolution, examine and establish the deep historical roots and ecological foundations of water sustainability issues, and contribute new grounds for innovations in sustainable urban planning and ecological resilience.
For decades, it has been unclear as to how the world's first cities, in southern Mesopotamia, not only arose in a fluvial environment but also how this environment changed. This paper seeks to ...understand the long-term fluvial history of the region around Uruk, a major early city, in relation to water-human interactions. This paper applies geomorphological, historical and archaeological approaches and reveals that the Uruk region in southern Mesopotamia had been under the influence of freshwater fluvial environment since the early Holocene. It further demonstrates how canals and long-term human activities since the mid Holocene have been superimposed on the natural river channel patterns. Fieldwork has been conducted to ground-truth features identified applying remote sensing techniques. Five sediment cores were analysed to elucidate palaeoenvironmental changes. Radiocarbon ages for organic samples suggest that the oldest sediment layers, at a depth of 12.5 m, are from the Early Holocene, while results from diatom analyses imply that the whole sediment column was deposited in a freshwater environment. Intensive networks of palaeochannels and archaeological sites within the study area have been reconstructed and these networks have been divided into four different time intervals based on changes in channel courses. The first is from the early 4th to the late 1st millennium BCE; the second is from the late 1st millennium BCE to the middle 2nd millennium CE; the third lasted from after the Islamic period until the 1980s; the fourth is from the 1980s until the present. Key results include evidence for freshwater environments and favourable settlement conditions had already formed by the 8th millennium BCE. The favourable settlement environment resulted in stable (long-lived) canals between the 4th millennium BCE and 1st millennium CE. A significant settlement and irrigation expansion occurred in the early 1st millennium CE. Major abandonment ensued in the late 1st millennium CE and lasted until the mid 2nd millennium CE.
This communication article provides a call for unmanned aerial vehicle (UAV) users in archaeology to make imagery data more publicly available while developing a new application to facilitate the use ...of a common deep learning algorithm (mask region-based convolutional neural network; Mask R-CNN) for instance segmentation. The intent is to provide specialists with a GUI-based tool that can apply annotation used for training for neural network models, enable training and development of segmentation models, and allow classification of imagery data to facilitate auto-discovery of features. The tool is generic and can be used for a variety of settings, although the tool was tested using datasets from the United Arab Emirates (UAE), Oman, Iran, Iraq, and Jordan. Current outputs suggest that trained data are able to help identify ruined structures, that is, structures such as burials, exposed building ruins, and other surface features that are in some degraded state. Additionally, qanat(s), or ancient underground channels having surface access holes, and mounded sites, which have distinctive hill-shaped features, are also identified. Other classes are also possible, and the tool helps users make their own training-based approach and feature identification classes. To improve accuracy, we strongly urge greater publication of UAV imagery data by projects using open journal publications and public repositories. This is something done in other fields with UAV data and is now needed in heritage and archaeology. Our tool is provided as part of the outputs given.
The trade in antiquities and cultural objects has proven difficult to understand and yet is highly dynamic. Currently, there are few computational tools that allow researchers to systematically ...understand the nature of the legal market, which can also potentially provide insights into the illegal market such as types of objects traded and countries trading antiquities. Online sales in antiquities and cultural objects are often unstructured data; relevant cultural affiliations, types, and materials for objects are important for distinguishing what might sell, but these data are rarely organized in a format that makes the quantification of sales a simple process. Additionally, sale locations and the total value of sales are relevant to understanding the focus and size of the market. These data all provide potentially useful insights into how the market in antiquities and cultural objects is developing. Based on this, this work presents the results of a machine learning approach using natural language processing and dictionary-based searches that investigate relatively low-end but high sales volume objects sold on eBay’s U.S. site, where sales are often international, between October 2018 and May 2019. The use of named entity recognition, using a conditional random field approach, classifies objects based on the cultures in which they come from, what type of objects they are, and what the objects are made of. The results indicate that objects from the United Kingdom, affiliated with the Roman period, mostly constituting jewelry, and made of metals sell the most. Metal and jewelry objects, in fact, sold more than other object types. Other important countries for selling ancient and cultural objects include the United States, Thailand, Germany, and Cyprus. Some countries appear to more greatly sellspecific types of objects, such as Egypt being a leader in selling Islamic, terracotta, stone, and wood artifacts and Germany selling Viking/early Medieval weapons. Overall, the approach and tool used demonstrate that it is possible to monitor the online antiquities and cultural objects market while potentially gaining useful insights into the market. The tool developed is provided as part of this work so that it can be applied for other cases and online sites, where it can be applied in real time or using historical data.
Many modern cultural object collections suffer from the problem of being obtained in unethical and illegal circumstances. Additionally, information about collections, including their status, object ...descriptions, and other data need up-to-date information presented to users. We propose a novel blockchain tool called Salsal that enables the vetting of objects, individually or as part of more extensive collections, to meet required ethical and legal guidelines while informing users about relevant information regarding collections. Blockchain provides a better and more rapid way for users to know about collections using a decentralized and immutable ledger technology. Blockchain can be used to incentivize or even pressure collections to vet their objects for ethical and legal guidelines that can benefit the public who use object collections. The prototype software we have made is presented and compared to other blockchains, with code and demonstration provided. We present how our blockchain can enable benefit, providing a useful vetting process for cultural objects, and allowing a user community to contribute to collections in a transparent and secure manner.
We produce results that bridge the gap between physical and textual study of the ancient Mesopotamian landscape in the region south and west of the city of Uruk (Biblical Erech, Modern Warka). A ...brief survey of gazetteers of Mesopotamia, volumes listing place-names drawn from translated and published cuneiform texts from the 2nd and 1st Millennium BCE, are presented. The various gazetteers were reviewed for relevant place-names, and the results were recorded and analyzed. These are described in detail below, as are their implications. The resulting data are then compared to the results of a recently completed archaeological survey of the same region. The synthesis of textual and archaeological surveys indicates a more exacting methodology to add geographic objectivity to textual results, while connecting physical results to the qualitative detail available within the Uruk textual record. More broadly, we demonstrate how long-term historical records align with archaeological data, delineating state-level and local land use efforts around a major Mesopotamian city. In the 2nd millennium BCE, settlements were generally small but more numerous, but in the 1st Millennium BCE there was a shift towards fewer and larger settlements connected to the city of Uruk. These shifts reflect deliberate central, government policy and local responses.
Constant detection and monitoring of archaeological sites and objects have always been an important national goal for many countries. The early identification of changes is crucial to preventive ...conservation. Archaeologists have always considered using service drones to automate collecting data on and below the ground surface of archaeological sites, with cost and technical barriers being the main hurdles against the wide-scale deployment. Advances in thermal imaging, depth imaging, drones, and artificial intelligence have driven the cost down and improved the quality and volume of data collected and processed. This paper proposes an end-to-end framework for archaeological sites detection and monitoring using autonomous service drones. We mount RGB, depth, and thermal cameras on an autonomous drone for low-altitude data acquisition. To align and aggregate collected images, we propose two-stage multimodal depth-to-RGB and thermal-to-RGB mosaicking algorithms. We then apply detection algorithms to the stitched images to identify change regions and design a user interface to monitor these regions over time. Our results show we can create overlays of aligned thermal and depth data on RGB mosaics of archaeological sites. We tested our change detection algorithm and found it has a root mean square error of 0.04. To validate the proposed framework, we tested our thermal image stitching pipeline against state-of-the-art commercial software. We cost-effectively replicated its functionality while adding a new depth-based modality and created a user interface for temporally monitoring changes in multimodal views of archaeological sites.
The marketisation of heritage has been a major topic of interest among heritage specialists studying how the online marketplace shapes sales. Missing from that debate is a large-scale analysis ...seeking to understand market trends on popular selling platforms such as eBay. Sites such as eBay can inform what heritage items are of interest to the wider public, and thus what is potentially of greater cultural value, while also demonstrating monetary value trends. To better understand the sale of heritage on eBay’s international site, this work applies named entity recognition using conditional random fields, a method within natural language processing, and word dictionaries that inform on market trends. The methods demonstrate how Western markets, particularly the US and UK, have dominated sales for different cultures. Roman, Egyptian, Viking (Norse/Dane) and Near East objects are sold the most. Surprisingly, Cyprus and Egypt, two countries with relatively strict prohibition against the sale of heritage items, make the top 10 selling countries on eBay. Objects such as jewellery, statues and figurines, and religious items sell in relatively greater numbers, while masks and vessels (e.g. vases) sell at generally higher prices. Metal, stone and terracotta are commonly sold materials. More rare materials, such as those made of ivory, papyrus or wood, have relatively higher prices. Few sellers dominate the market, where in some months 40% of sales are controlled by the top 10 sellers. The tool used for the study is freely provided, demonstrating benefits in an automated approach to understanding sale trends.
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