Spatio-temporal Point Process models on a global scale and their application to global lightning occurrences

全球尺度时空点过程模型及其在全球闪电发生中的应用

• 批准号: 1613003
• 负责人: Mikyoung Jun
• 金额: $ 12万
• 依托单位: Texas A&M University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-08-15 至 2019-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1613003&HistoricalAwards=false
• 关键词: Spatio; temporal; Point; Process; models

With recent technological advances and increased network connectivity, many environmental, biological, and socio-economic datasets are collected on a global scale. However, many of the current statistical models and methods are not suitable for environmental applications where the data cover the surface of the sphere. The goal of this project is to develop spatial and spatio-temporal point process models on a global scale. The research is motivated by a study of global lightning occurrence, and the impact of climate change on global lightning occurrence patterns. The research will provide useful information for scientists, policy makers, and the general public. The proposed models will address the spatial inhomogeneity of the intensity functions as well as their nonstationarity, both of which are essential for environmental applications. In the spatio-temporal case, parametric covariance models for the stochastic intensity function that can represent complex spatio-temporal interactions will be studied, and univariate as well as multivariate point patterns that account for the cross-dependence between multiple point patterns will be considered.

随着最近的技术进步和网络连接的增加，许多环境，生物和社会经济数据集在全球范围内收集。 然而，目前的许多统计模型和方法不适合于数据覆盖球体表面的环境应用。 该项目的目标是开发全球范围内的空间和时空点过程模型。 这项研究的动机是研究全球闪电发生，以及气候变化对全球闪电发生模式的影响。 这项研究将为科学家、政策制定者和公众提供有用的信息。所提出的模型将解决强度函数的空间不均匀性以及它们的非平稳性，这两者对于环境应用都是必不可少的。在时空的情况下，参数协方差模型的随机强度函数，可以代表复杂的时空相互作用将进行研究，以及单变量以及多变量点模式，考虑多个点模式之间的交叉依赖。