Adaptive sampling in space and time

空间和时间的自适应采样

• 批准号: 327306-2006
• 负责人: Thompson, Steven
• 金额: $ 1.82万
• 依托单位: Simon Fraser University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2006
• 资助国家: 加拿大
• 起止时间: 2006-01-01 至 2007-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=334393
• 关键词: Adaptive; sampling; space; time

The proposed research develops theory and methods of adaptive sampling in space and time.  Adaptive sampling designs are those in which the selection of the sample units depends on values of variables of interest observed during the course of the survey.  Adaptive designs can offer substantial increases in efficiency for spatially clustered, rare, and networked populations. One area of the proposed research investigates and develops adaptive sampling designs in which the sampling units may move during the course of the survey.  For sampling spatially distributed populations, a sampling unit is typically conceived to be a fixed point or subset of the region of interest.  For populations distributed in space and time, however, it makes sense to consider sampling paths on which units move through space over time.  In this case, a sampling unit is a path, manifold, or subregion in space/time.  For example, to monitor for surprise releases of acute air pollutant clouds with a limited number of sensor units, it is most efficient to have units moving in paths that are predominantly perpendicular to the wind.  Similar path considerations may apply to surveys of migratory animals using boats or aircraft.  More complex dynamic sampling plans apply to designs for monitoring the progress of epidemics through social networks.  Adaptive moving designs in which the paths can change or new paths be added in response to observed values will be investigated. Other areas of the proposed research programme include adaptive interventions or experiments in natural and human populations, theory of adaptive designs, and new adaptive designs to take advantage of special population structures.  The proposed research has important applications to the health and environmental sciences and other fields.

所提出的研究发展了空间和时间自适应采样的理论和方法。  自适应抽样设计是指样本单位的选择取决于调查过程中观察到的感兴趣变量的值。  自适应设计可以大幅提高空间聚集、稀有和网络化人群的效率。拟议研究的一个领域是调查和开发自适应抽样设计，其中抽样单位可以在调查过程中移动。  为了对空间分布的群体进行采样，采样单元通常被认为是感兴趣区域的固定点或子集。  然而，对于分布在空间和时间上的群体来说，考虑单位随时间在空间中移动的采样路径是有意义的。  在这种情况下，采样单元是空间/时间中的路径、流形或子区域。  例如，要使用有限数量的传感器单元监测急性空气污染物云的意外释放，最有效的方法是让单元沿主要垂直于风的路径移动。  类似的路径考虑可能适用于使用船只或飞机对迁徙动物进行调查。  更复杂的动态采样计划适用于通过社交网络监测流行病进展的设计。  将研究自适应移动设计，其中路径可以改变或添加新路径以响应观测值。拟议研究计划的其他领域包括自然群体和人类群体的适应性干预或实验、适应性设计理论以及利用特殊群体结构的新适应性设计。  拟议的研究在健康和环境科学及其他领域具有重要的应用。