Design, measurement and modelling in spatio-temporal analysis

时空分析中的设计、测量和建模

• 批准号: RGPIN-2016-03776
• 负责人: Zidek, James
• 金额: $ 3.35万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=614621
• 关键词: Design; measurement; modelling; spatio; temporal

The burgeoning World population, newly predicted under present conditions to continue growing to as much as 15billion by the year 2100, is leading to increasing concerns about elevated levels of environment risk. More incidents e.g. high temperature episodes and the increased consumption of fossil fuels e.g. coal are expected. This dark future portends an increased need to effectively monitor environmental processes over space and time along with accurate methods for predicting these processes where they cannot be monitored in space and in the future, to support the management and mitigation of these risks through effective policy and regulation. Statisticians have a major role to play in this future, particularly in quantifying the uncertainties that abound. The proposed research will continue the applicant’s long-term research program on the optimum design of spatio - temporal process monitoring networks and the use of the resulting data for modelling these processes for spatial prediction and future values. In particular, since existing network stations tend to be sited at preferentially selected geographical locations, we will continue seeking methods to reduce errors in statistical estimates induced by locating stations in that way. The research will also explore a promising objective method for siting them, one that insures they are well distributed over space. The remainder of the research concerns the use of data from these networks, possibly with adjustments for the effects of preferential siting, to create good spatio - temporal models. We will continue current research and seek models for temperature fields that extend their geographical domains of applicability - current work has focused the Pacific Northwest region of North America, beyond what has been considered to date. The results of this work will be used in the development of a new method for short term forecasting - this will combine an ensemble of computer models with temperature data, all in the direction of mitigating the adverse health effects of high temperatures. We will also seek to improve the efficiency of current temperature monitoring networks. But climate change is affecting not just the human species. Other research will concern marine mammals since their numbers in some regions are being depleted for reasons not yet understood. Now the research will continue work already begun on modelling the paths of fur seals between GPS sitings to better estimate their energy consumption (thus indicating how much food they need) as well as learn about the habitats they seek. The effect of climate change on these habitats will be the ultimate goal of the research on the impacts of increasing human populations and their impacts on the climate.

据最新预测，在目前情况下，到 2100 年，世界人口将继续增长到 150 亿，这导致人们越来越担心更多的环境风险，例如高温事件和煤炭等化石燃料的消耗增加。预计这种黑暗的未来预示着越来越需要有效地监测空间和时间上的环境过程，以及在空间和未来无法监测的情况下预测这些过程的准确方法，以支持管理和缓解。通过有效的政策和监管，统计学家可以在未来发挥重要作用，特别是在量化大量的不确定性方面。 所提议的研究将继续申请人关于时空过程监测网络的优化设计以及使用所得数据对这些过程进行建模以进行空间预测和未来值的长期研究计划，特别是因为现有的网络站倾向于。优先选择的地理位置，我们将继续寻找方法来减少以这种方式定位站点所引起的统计估计误差，该研究还将探索一种有前途的客观方法来安置它们，确保它们在空间上均匀分布。 研究的其余部分涉及使用来自这些网络的数据，可能会调整优先位置的影响，以创建良好的时空模型。我们将继续当前的研究，并寻求扩展其适用性地理范围的温度场模型。 - 目前的工作重点是北美太平洋西北地区，超出了迄今为止所考虑的范围。这项工作的结果将用于开发一种新的短期预测方法 - 这将结合计算机模型的集合。温度数据，全部朝着缓解的方向我们还将寻求提高当前温度监测网络的效率。 但气候变化不仅影响人类，还涉及海洋哺乳动物，因为某些地区的海洋哺乳动物数量正在减少，原因尚不清楚。现在，这项研究将继续对海狗在 GPS 定位之间的路径进行建模。更好地估计它们的能源消耗（从而表明它们需要多少食物）以及了解它们寻求的栖息地。气候变化对这些栖息地的影响将是研究人口增长及其影响的最终目标。对气候的影响。