Sampling methods for archaeological predictive modeling: Spatial autocorrelation and model performance

Comer, Jacob A.; Comer, Douglas C.; Dumitru, Ioana A.; Priebe, Carey E.; Patsolic, Jesse

doi:10.1016/j.jasrep.2022.103824

Cited by 2 publications

(1 citation statement)

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“…Modeling the relationship between known archaeological features and their material and spatial environments can give insights into the locations of presently unknown features, aiding in archaeological prospection and survey and informing an understanding of human-environment relationships. Recent studies have evaluated the predictive power of different statistical approaches and sampling strategies (e.g., Castiello and Tonini 2021;Comer et al 2023;Kelly et al 2023;Yaworsky et al 2020) and developed techniques for raster imagery analysis using machine learning and object-based imagery analysis (e.g., Magnini and Bettineschi 2021).…”

Section: Predictive Modeling Zonal Statistics and Archaeological Pros...mentioning

confidence: 99%

Open-Access Archaeological Predictive Modeling Using Zonal Statistics: A Case Study from Zanzibar, Tanzania

Alders

2023

JCAA

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This paper presents a case study using zonal statistical analysis for archaeological predictive modeling with open-access software and free geospatial datasets. The method is applied to the rural landscapes of Zanzibar, Tanzania on the Swahili Coast. This study used QGIS (version 3.28) to perform zonal statistical analyses of environmental datasets weighted by settlement classes digitized from a 1907 historical map, to create predictive models for settlement across the island. These models were compared against the locations of major precolonial archaeological sites on the island and site data from a random stratified archaeological survey in an environmentally diverse region of northern Zanzibar. The results show strong correspondences between larger permanent site locations and areas of high likelihood for site detection in the predictive model. Additionally, there were correspondences between areas of lower likelihood for site detection and smaller, ephemeral sites related to agricultural production in swidden field plots. These results attest to Swahili rural complexity and enable an understanding of the specific environmental affordances that structured settlement and land use over the last millennium, in ways that shaped colonial contact in rural areas and altered the sociopolitical development of Zanzibar and the East African coast. The methods described here may be applicable for researchers and heritage managers in Africa and the Global South, where funding for large-scale field projects, expensive satellite imagery, or software licensing is limited.

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Section: Predictive Modeling Zonal Statistics and Archaeological Pros...mentioning

confidence: 99%

Open-Access Archaeological Predictive Modeling Using Zonal Statistics: A Case Study from Zanzibar, Tanzania

Alders

2023

JCAA

View full text Add to dashboard Cite

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Extraction of Vital Sign Based on PE and ICEEMDAN for UWB Radar

Li,

Yang,

et al. 2024

IEEE Sensors J.

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Sampling methods for archaeological predictive modeling: Spatial autocorrelation and model performance

Cited by 2 publications

References 28 publications

Open-Access Archaeological Predictive Modeling Using Zonal Statistics: A Case Study from Zanzibar, Tanzania

Open-Access Archaeological Predictive Modeling Using Zonal Statistics: A Case Study from Zanzibar, Tanzania

Extraction of Vital Sign Based on PE and ICEEMDAN for UWB Radar

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