Changing the settlement pattern at the beginning of the Iron Age in the north of the central plateau of Iran (Alborz Province)

• Innovative Methodology: Spatial modeling and point analysis of settlement patterns. • Environmental Influences: Settlement patterns relate to soil type and elevation. • Cluster Analysis: Iron Age sites are grouped into four clusters with distinct patterns. • Cultural Dynamics: Cultural and economic factors influenced settlements, notably in Cluster 4. • Chronological Insights: Chronological Insights: Settlement shifts from the Chalcolithic to Iron Age in Alborz. One of the crucial topics and innovations in contemporary archaeology is explaining the implicit processes involved in the emergence of settlement patterns in ancient communities. Recent studies have utilized spatially explicit modeling to interpret these patterns. In Alborz province, there are ancient sites dating from the Chalcolithic Age to the Iron Age. However, no study has yet employed explicit modeling to investigate the settlement of these sites. Through cluster analysis using the “Average Linkage” method in R software, pre-Iron Age sites were grouped together, while Iron Age sites were categorized into cluster 1, cluster 2, cluster 3, and cluster 4. Spatially explicit point pattern modeling was applied to explore potential relationships between archaeological sites and environmental variables such as elevation, slope, aspect, watershed, and soil type. The results revealed that soil type significantly influenced the settlement patterns of Iron Age clusters 1, 2, and 3. For cluster 1, the number of sites decreased in areas close to the watershed, while in cluster 2, a negative correlation with elevation was observed. In cluster 3, combining variables from clusters 1 and 2 yielded the best-fitting model, with soil type and elevation playing critical roles. For pre-Iron Age sites, elevation showed a significant negative correlation with settlement patterns. Conversely, cluster 4 displayed no significant relationship with any environmental variables, and its settlement distribution was best explained by a stationary model. These findings underscore the role of environmental variables, particularly soil type and elevation, in shaping settlement patterns during the Iron Age and pre-Iron Age periods. However, the distinct characteristics of cluster 4 suggest the potential influence of non-environmental factors, such as cultural or economic dynamics, in site distribution. The study highlights the importance of spatially explicit modeling in archaeological research and encourages integrating additional datasets to achieve a more comprehensive understanding of ancient settlement processes.

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Publication Details

Journal
Journal of Archaeological Science Reports
Published
2025-04-06
DOI
https://doi.org/10.1016/j.jasrep.2025.105104
Citations
2
Primary Topic
Archaeology and Historical Studies
Type
article
Field-Weighted Citation Impact
16.55
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article

Changing the settlement pattern at the beginning of the Iron Age in the north of the central plateau of Iran (Alborz Province)

A S Naghshineh, Hasan Rostamirad
2 citations
Journal of Archaeological Science Reports
Archaeology and Historical Studies
16.55
article

Changing the settlement pattern at the beginning of the Iron Age in the north of the central plateau of Iran (Alborz Province)

A S Naghshineh, Hasan Rostamirad
article en
2 citations

Abstract

• Innovative Methodology: Spatial modeling and point analysis of settlement patterns. • Environmental Influences: Settlement patterns relate to soil type and elevation. • Cluster Analysis: Iron Age sites are grouped into four clusters with distinct patterns. • Cultural Dynamics: Cultural and economic factors influenced settlements, notably in Cluster 4. • Chronological Insights: Chronological Insights: Settlement shifts from the Chalcolithic to Iron Age in Alborz. One of the crucial topics and innovations in contemporary archaeology is explaining the implicit processes involved in the emergence of settlement patterns in ancient communities. Recent studies have utilized spatially explicit modeling to interpret these patterns. In Alborz province, there are ancient sites dating from the Chalcolithic Age to the Iron Age. However, no study has yet employed explicit modeling to investigate the settlement of these sites. Through cluster analysis using the “Average Linkage” method in R software, pre-Iron Age sites were grouped together, while Iron Age sites were categorized into cluster 1, cluster 2, cluster 3, and cluster 4. Spatially explicit point pattern modeling was applied to explore potential relationships between archaeological sites and environmental variables such as elevation, slope, aspect, watershed, and soil type. The results revealed that soil type significantly influenced the settlement patterns of Iron Age clusters 1, 2, and 3. For cluster 1, the number of sites decreased in areas close to the watershed, while in cluster 2, a negative correlation with elevation was observed. In cluster 3, combining variables from clusters 1 and 2 yielded the best-fitting model, with soil type and elevation playing critical roles. For pre-Iron Age sites, elevation showed a significant negative correlation with settlement patterns. Conversely, cluster 4 displayed no significant relationship with any environmental variables, and its settlement distribution was best explained by a stationary model. These findings underscore the role of environmental variables, particularly soil type and elevation, in shaping settlement patterns during the Iron Age and pre-Iron Age periods. However, the distinct characteristics of cluster 4 suggest the potential influence of non-environmental factors, such as cultural or economic dynamics, in site distribution. The study highlights the importance of spatially explicit modeling in archaeological research and encourages integrating additional datasets to achieve a more comprehensive understanding of ancient settlement processes.

Journal of Archaeological Science ReportsVol. 63
Openalex Percentile: Top 2%
Archaeology and Historical Studies
16.55
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