A total viewshed approach to local visibility in the Chaco World

Dungan, Katherine; White, Devin; Déderix, Sylviane; Mills, Barbara J.; Safi, Kristin

doi:10.15184/aqy.2018.135

Cited by 23 publications

(18 citation statements)

References 22 publications

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“…We first processed the maximum-height surface, which preserves the most contrast in vertical information from the higher-resolution source elevation model and facilitates identifying prominent points, using an aggregate viewshed application that is accelerated by a graphical processing unit to shorten runtime, resulting in a visibility-frequency map whose cell-value distribution closely resembles a power law; this is the first time such an application has been applied at a continental scale 86 . We then log-transformed the data to approximate a normal distribution, and selected cells whose values were ≥ 3 standard deviations (σ) from the mean as the most visible locations.…”

Section: Model Inputsmentioning

confidence: 99%

Landscape rules predict optimal superhighways for the first peopling of Sahul

et al. 2021

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Section: Model Inputsmentioning

confidence: 99%

Landscape rules predict optimal superhighways for the first peopling of Sahul

et al. 2021

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“…GIS is often used as a framework for analyses in landscape archaeology (Howey and Brouwer Burg 2017; Parcak 2017). To that end, two types of analysis of how people interact with their landscape through sight and movement, visibility (e.g., Bernardini et al 2013; Dungan et al 2018), and cost path analysis (Gustas and Supernant 2019; Taliaferro et al 2010) are frequently applied to archaeological datasets. Even more common is the use of GIS for spatial database management, where GIS allows archaeologists to perform typical spatial documentation but in a more efficient manner (Howey and Brouwer Burg 2017; Verhagen 2017).…”

Section: Archaeology In a Digital Agementioning

confidence: 99%

Integrating Digital Datasets into Public Engagement through ArcGIS StoryMaps

Howland

Liss

Levy

et al. 2020

Adv. archaeol. pract.

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Archaeologists have a responsibility to use their research to engage people and provide opportunities for the public to interact with cultural heritage and interpret it on their own terms. This can be done through hypermedia and deep mapping as approaches to public archaeology. In twenty-first-century archaeology, scholars can rely on vastly improved technologies to aid them in these efforts toward public engagement, including digital photography, geographic information systems, and three-dimensional models. These technologies, even when collected for analysis or documentation, can be valuable tools for educating and involving the public with archaeological methods and how these methods help archaeologists learn about the past. Ultimately, academic storytelling can benefit from making archaeological results and methods accessible and engaging for stakeholders and the general public. ArcGIS StoryMaps is an effective tool for integrating digital datasets into an accessible framework that is suitable for interactive public engagement. This article describes the benefits of using ArcGIS StoryMaps for hypermedia and deep mapping–based public engagement using the story of copper production in Iron Age Faynan, Jordan, as a case study.

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“…In terms of attention, overly-detailed art can appear confusing and demand considerable concentration, such as the convoluted interwoven 'ribbon beasts' of early Medieval (Anglo-Saxon, Viking) northwestern Europe (Wilson 2010) or the intricately painted murals of Mayan Teotehuacan (Webster and Toby Evans 2018). In the physical sense, GIS can eloquently reveal how affordances at the landscape scale can be accentuated or made obvious by modifications such as Late Bronze Age linear ditches cut into the white chalk of Wessex (Llobera 1996;Webster 1999); how height differentials between objects and viewers in the landscape can create psychological effect (Llobera 2001) and how viewshed manipulation can enhance the impressiveness of structures such as Chacoan great houses (Dungan et al 2018).…”

Section: Scale and Attentionmentioning

confidence: 99%