Predictive modeling for archaeological site locations: Comparing logistic regression and maximal entropy in north Israel and north-east China

Wachtel, Ido; Zidon, Royi; Garti, Shimon; Shelach-Lavi, Gideon

doi:10.1016/j.jas.2018.02.001

Cited by 36 publications

(26 citation statements)

References 18 publications

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“…As a result of the importance of farming, these areas would have been extremely important. Soil represents a significant factor used in APM [20].…”

Section: Methodsmentioning

confidence: 99%

“…Quantitative methods can limit bias, which helps to reduce the effects of this problem and can improve the replicability of the workflow for use in other locations. The most commonly used geospatial formulae for predictive modelling are maximum entropy (MaxEnt) [19], logistic regression [20], evidential reasoning [14], fuzzy logic [21], weight of evidence [22] and multivariate statistics [23].…”

Section: Introductionmentioning

confidence: 99%

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GIS-Based and Statistical Approaches in Archaeological Predictive Modelling (NE Romania)

2019

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Archaeological predictive modelling (APM) is an important method for archaeological research and cultural heritage management. This study tests the viability of a new statistical method for APM. Frequency ratio (FR) is widely used in the field of geosciences but has not been applied in APM. This study tests FR in a catchment from the north-eastern part of Romania to predict the possible location(s) of Eneolithic sites. In order to do that, three factors were used: soils, heat load index and slope position classification. Eighty percent of the sites were used to build the model, while the remaining 20% were used to externally test the model’s performance. The final APM was made with the help of GIS software and classified into four susceptibility classes: very high, high, medium and low. The success rate curve and the prediction rate curve reported values of the area under curve (AUC) of 0.72, and 0.75 respectively. The Kvamme’s Gain value for the model has a value of 0.56. Therefore, the final APM is reliable, so FR is a viable technique for APM. The final map can be successfully used in archaeological research, cultural heritage management and protection, preventive archaeology and sustainable development.

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“…As a result of the importance of farming, these areas would have been extremely important. Soil represents a significant factor used in APM [20].…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

GIS-Based and Statistical Approaches in Archaeological Predictive Modelling (NE Romania)

2019

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“…Since its publication in 2004, MaxEnt has rapidly become the dominant modeling approach for species distribution thanks to its high performance [ 17 ]. In recent years, it was also adapted for archeological locational modeling [ 18 , 19 , 20 , 21 , 22 ]. However, MaxEnt is still not widely used in archaeology, where it has great potential to advance our knowledge of early societies.…”

Section: Introductionmentioning

confidence: 99%

“…In a previous paper [ 22 ], we compared the conventional statistical approach to locational/predictive modeling with MaxEnt. Our main conclusion was that MaxEnt has the ability to provide stable and effective results based on small and partial archeological data set.…”

Section: Introductionmentioning

confidence: 99%

Using the Maximal Entropy Modeling Approach to Analyze the Evolution of Sedentary Agricultural Societies in Northeast China

Wachtel

Zidon

Shelach-Lavi

2020

Entropy

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The emergence of agriculture and the evolution of sedentary societies are among the most important processes in human history. However, although archeologists and social scientists have long been studying these processes, our understanding of them is still limited. This article focuses on the Fuxin area in present-day Liaoning province in Northeast China. A systematic archeological survey we conducted in Fuxin in recent years located sites from five successive stages of the evolution of agricultural sedentary society. We used the principles of Maximal Entropy to study changes in settlement patterns during a long-term local trajectory, from the incipient steps toward a sedentary agricultural way of life to the emergence of complex societies. Based on the detailed data collected in the field, we developed a geo-statistical model based on Maximal Entropy (MaxEnt) that characterizes the locational choices of societies during different periods. This combination of high-resolution information on the location and density of archeological remains, along with a maximal entropy-based statistical model, enabled us to chart the long-term trajectory of the interactions between human societies and their natural environment and to better understand the different stages of the transition to developed sedentary agricultural society.

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“…We focus on rockshelters, as they-in contrast to open-air sitesprovide particularly favourable conditions for the preservation of both tephra and traces of human settlement. Using available digital elevation models and the rockshelter database, we created an archaeological predictive model using the weighted-layer overlay approach and a MaxEnt-model for cross-validation (Sauer 2018;Wachtel et al 2018). Both models were tested on 140 Final Palaeolithic locales in the Central Uplands of Germany, in-and outside of Hessen.…”

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confidence: 99%

Rockshelters and the impact of the Laacher See eruption on Late Pleistocene foragers

2018

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Predictive modeling for archaeological site locations: Comparing logistic regression and maximal entropy in north Israel and north-east China

Cited by 36 publications

References 18 publications

GIS-Based and Statistical Approaches in Archaeological Predictive Modelling (NE Romania)

GIS-Based and Statistical Approaches in Archaeological Predictive Modelling (NE Romania)

Using the Maximal Entropy Modeling Approach to Analyze the Evolution of Sedentary Agricultural Societies in Northeast China

Rockshelters and the impact of the Laacher See eruption on Late Pleistocene foragers

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