One point per cluster spatially balanced sampling

Blair Robertson and Chris Price

Computational Statistics & Data Analysis, 2024, vol. 191, issue C

Abstract: 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. Spatially balanced designs have good spatial spread and give precise results for commonly used estimators when surveying natural resources. A new design is proposed which draws spatially balanced samples from stratified and unstratified populations. The method is two-fold. First, the population is partitioned into n compact geographic clusters. Then, a one point per cluster sample is drawn using a linear assignment strategy that optimises the spatial spread of the sample. Numerical results on several simulated populations show that the method generates well-spread samples and compares favourably with existing designs. An example application is also provided, where soil organic matter concentrations are estimated over a study area in Voorst, Netherlands.

Keywords: Environmental sampling; Constrained k-means; Linear assignments (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:191:y:2024:i:c:s0167947323001998

DOI: 10.1016/j.csda.2023.107888

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