Integrating Point Process Models, Evolutionary Ecology and Traditional Knowledge Improves Landscape Archaeology—A Case from Southwest Madagascar
Integrating Point Process Models, Evolutionary Ecology and Traditional Knowledge Improves Landscape Archaeology—A Case from Southwest Madagascar
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整合点过程模型、进化生态学和传统知识改进景观考古学——以马达加斯加西南部为例
DOI：
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Kristina G. Douglass
中科院分区：
文献类型：
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作者：
Dylan S. Davis;R. DiNapoli;Kristina G. Douglass
景观考古学使用预测模型来提高我们对世界各地现存考古特征的了解已经有很长的历史了。然而，空间统计学的重要进展在考古预测建模方面进展缓慢。特别是，点过程模型(PPM)提供了一种强大的解决方案来显式地对点模式的一阶和二阶属性进行建模。在这里，我们使用PPM来改进最近开发的基于遥感的预测算法，该算法适用于马达加斯加西南海岸的考古记录。这一初步的遥感模型得出了80%的真实正确率，迅速扩大了我们对该地区考古记录的了解。尽管该模型的成功率很高，但它产生了大量(~20%)的假阳性结果。在本文中，我们开发了一系列PPM模型，以提高该模型在预测马达加斯加西南部考古沉积物位置方面的准确性。我们说明了如何迭代地使用PPM、传统生态知识、遥感和田野工作来提高预测模型的准确性并增强对考古记录的解释。我们使用一个明确的行为生态学理论框架，利用空间建模方法来阐述和检验假设。我们的建模过程可以被世界各地的考古学家复制，以帮助进行实地考察、后勤和规划。
Landscape archaeology has a long history of using predictive models to improve our knowledge of extant archaeological features around the world. Important advancements in spatial statistics, however, have been slow to enter archaeological predictive modeling. Point process models (PPMs), in particular, offer a powerful solution to explicitly model both first- and second-order properties of a point pattern. Here, we use PPMs to refine a recently developed remote sensing-based predictive algorithm applied to the archaeological record of Madagascar’s southwestern coast. This initial remote sensing model resulted in an 80% true positive rate, rapidly expanding our understanding of the archaeological record of this region. Despite the model’s success rate, it yielded a substantial number (~20%) of false positive results. In this paper, we develop a series of PPMs to improve the accuracy of this model in predicting the location of archaeological deposits in southwest Madagascar. We illustrate how PPMs, traditional ecological knowledge, remote sensing, and fieldwork can be used iteratively to improve the accuracy of predictive models and enhance interpretations of the archaeological record. We use an explicit behavioral ecology theoretical framework to formulate and test hypotheses utilizing spatial modeling methods. Our modeling process can be replicated by archaeologists around the world to assist in fieldwork logistics and planning.
影响因子：
3.1
作者：
Bevan, Andrew;Conolly, James
通讯作者：
Conolly, James
影响因子：
2.2
作者：
Jazwa, Christopher S.;Kennett, Douglas J.;Joslin, Terry L.
通讯作者：
Joslin, Terry L.
影响因子：
3.2
作者：
W. Appels;C. Graham;J. Freer;J. McDonnell
通讯作者：
W. Appels;C. Graham;J. Freer;J. McDonnell