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      Creating the funerary landscape of Eastern Sudan

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      PLOS ONE
      Public Library of Science (PLoS)

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          Abstract

          Funerary landscapes are eminent results of the relationship between environments and superstructural human behavior, spanning over wide territories and growing over centuries. The comprehension of such cultural palimpsests needs substantial research efforts in the field of human ecology. The funerary landscape of the semi-arid region of Kassala (Eastern Sudan) represents a solid example. Therein, geoarchaeological surveys and the creation of a desk-based dataset of thousands of diachronic funerary monuments (from early tumuli up to modern Beja people islamic tombs) were achieved by means of fieldwork and remote sensing over an area of ∼4100 km 2. The wealth of generated information was employed to decipher the spatial arrangement of sites and monuments using Point Pattern Analysis. The enormous number of monuments and their spatial distribution are here successfully explained using, for the first time in archaeology, the Neyman-Scott Cluster Process, hitherto designed for cosmology. Our study highlights the existence of a built funerary landscape with galaxy-like aggregations of monuments driven by multiple layers of societal behavior. We suggest that the distribution of monuments was controlled by a synthesis of opportunistic geological constraints and cultural superstructure, conditioned by the social memory of the Beja people who have inhabited the region for two thousand years and still cherish the ancient tombs as their own kin’s.

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                Author and article information

                Contributors
                (View ORCID Profile)
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                Journal
                PLOS ONE
                PLoS ONE
                Public Library of Science (PLoS)
                1932-6203
                July 7 2021
                July 7 2021
                : 16
                : 7
                : e0253511
                Article
                10.1371/journal.pone.0253511
                e055a2cf-6190-458e-bdc2-4eab294ea6cb
                © 2021

                http://creativecommons.org/licenses/by/4.0/

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