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Considering Uncertainty in Archaeological Predictive Modelling: A Case Study in Southern Rhineland-Palatinate (Germany)

机译:考虑到考古预测建模的不确定性 - 南莱茵河 - 普法尔茨(德国)为例

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Most archaeological predictive models lack significance because fuzzincss of data and uncertainty in knowledge about human behaviour and natural processes are hardly ever considered. One approach to cope with such uncertainties is utilization of methods, which base on approaches of the probability theory like Bayes Theorem or Dempster-Shafer-Theory. In our case study we analyze an area of 50 km2 in southern Rhineland Palatinate (Germany) near the Celtic oppidum "Hunnenring" by use of Dempster-Shafer's theory of evidence for predicting spatial probability distribution of archaeological sites. This technique incorporates uncertainty by assigning various weights of evidence to defined variables, in that way estimating the probability for supporting a specific hypothesis (in our case the hypothesis presence or absence of a site). Selection of variables for our model relies both on assumptions about settlement patterns and on statistically tested relationships between known archaeological sites and environmental factors. The modelling process is conducted in a Geographic Information System (GIS) by generating raster-based likelihood surfaces with a cell resolution of 10 m for the six selected variables 'distance to water', 'distance to road network', 'distance to graves', 'slope', 'landforms' and 'geology'. The corresponding likelihood surfaces are aggregated to a final weight of evidence surface, which results in a likelihood value for every single cell of being a site or a non-site. Finally the result is tested against a database of known archaeological sites for evaluating the gain of the model. To address the high potential of soil erosion processes of the low mountain parts of our study area a model was developed which allocates erosion and deposition zones to those areas. The combination of this model with the predictive model yields a more differentiated estimation, especially with regard to the suspected potential of archaeological remains being conserved until present.
机译:大多数考古预测模型缺乏重要意义,因为有关人类行为和自然过程的知识的虚拟性和不确定性几乎没有考虑过。应对这些不确定性的一种方法是利用方法,这些方法基于贝叶斯定理或Dempster-Shafer-理论等概率理论的方法。在我们的案例研究中,我们通过使用Dempster-Shafer的证据理论,分析凯尔特对比“Hunnenring”的凯尔特对比“德国”南部的50平方公里的区域。该技术通过将各种证据分配到定义的变量来掺入不确定性,以这种方式估计支持特定假设的概率(在我们的情况下,假设存在或不存在部位)。我们模型的变量选择依赖于关于结算模式的假设以及已知考古地点与环境因素之间的统计测试关系。通过将基于光栅的似然表面(GIS)产生的电池分辨率为10米的六个选定变量与水“,”与道路网的距离“,'与Graves距离的距离)进行建模过程。 ,'斜坡','地貌'和'地质'。相应的似然表面被聚集到证据表面的最终重量,这导致作为站点或非站点的每个单元的似然值。最后,该结果是针对已知考古站点的数据库测试,用于评估模型的增益。为了解决我们研究区域的低山地部分土壤侵蚀过程的高潜力,开发了一种模型,将侵蚀和沉积区分配给这些区域。这种模型与预测模型的组合产生了更分散的估计,特别是关于考古学的疑似潜力,直至存在。

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