首页> 外文期刊>International Journal of Geographical Information Science >Evaluation of the variation in semantic contents of class sets on modelling dynamics of land-use changes
【24h】

Evaluation of the variation in semantic contents of class sets on modelling dynamics of land-use changes

机译:基于土地利用变化建模动态的类集语义内容变化评估

获取原文
获取原文并翻译 | 示例
           

摘要

Understanding the scale of interaction and the scale of different environmental and social processes is of paramount importance to define and explain the interaction of human-environment systems. There are three dimensions of scale: space, time and the organisational hierarchy as constructed by the observer. The latter is synonymous with the variation in semantic contents of data expressed as differences in categorisation. This dimension of scale has received little attention. In this article the relationship between the semantic contents of data and modelling dynamics is explored using two land-cover data sets for Romania, one based on the Land-Cover Classification System and the other as used in the EURURALIS study. Three levels of semantic contents of the LCCS data and the single semantic level present in the EURURALIS data are used to establish empirical relations between the land-cover class and its explaining factors. The analysis results show that the variations in semantic contents of data within one data set and between two data sets lead to different sets of spatial determinants for land cover. We did not recognise patterns when establishing the organisational hierarchy. Future policy and decision-making depend to a great extent on which organisational hierarchy is present in the data set used to formulate a policy or to make an informed decision. This would mean that if the same results would be found in other data sets using different models not only multi-scale but also multi-semantic analysis are needed in order to make meaningful predictions of spatially explicit land change.
机译:了解相互作用的规模以及不同环境和社会过程的规模对于定义和解释人类环境系统的相互作用至关重要。规模具有三个维度:观察者构建的空间,时间和组织层次结构。后者与表示为分类差异的数据语义内容的变化同义。规模的这一维度很少受到关注。本文使用罗马尼亚的两个土地覆盖数据集(一个基于土地覆盖分类系统,另一个用于EURURALIS研究中)探索了数据的语义内容与建模动力学之间的关系。 LCCS数据的语义内容的三个级别和EURURALIS数据中存在的单个语义级别用于建立土地覆盖类别及其解释因素之间的经验关系。分析结果表明,一个数据集内以及两个数据集之间的数据语义内容的变化导致土地覆被的空间决定因素集不同。建立组织层次结构时,我们没有意识到模式。未来的政策和决策在很大程度上取决于用于制定政策或做出明智决策的数据集中的组织层次结构。这意味着,如果在使用不同模型的其他数据集中可以找到相同的结果,则不仅需要进行多尺度分析,而且还需要进行多语义分析,以便对空间上明确的土地变化做出有意义的预测。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号