StatsPD@Waite meeting: Using Linear Assignments in Spatial Sampling

Every month, the professional development meetings of statisticians and data scientists at Waite, known as StatsPD@Waite, bring together specialists in various aspects of data sciences in agriculture from Waite, Roseworthy and Adelaide.

Date: Tue, 9 June 2026, 10:00-11:00 AM (Adelaide)

Location: Hybrid – Zoom meeting & SET WT Waite Building 204 Meeting Room

Contact: biometryhub@adelaide.edu.au

Presenter: Blair Roberston, Associate Professor, School of Mathematics and Statistics, University of Canterbury, New Zealand

Using Linear Assignments in Spatial Sampling

A spatial sampling design determines where sample locations are placed in a study area so that population parameters can be estimated with relatively high precision. Usually, the population mean, or total, is estimated, but other characteristics may also be of interest. An effective strategy for sampling natural resources is to spread sample locations evenly over the resource because nearby locations tend to have more similar response values than distant ones. Spatially balanced designs have good spatial spread and give precise results for commonly used estimators when surveying natural resources. Doubly balanced designs have two balancing properties: approximately balanced on auxiliary variables and spatially balanced. In this talk, we present a linear assignment strategy for drawing spatially balanced and doubly balanced samples.