A spatial sampling design determines where sample locations are placed in a study area so that population parameters can be estimated with good precision. Spatially balanced designs draw samples with good spatial spread and provide precise results for commonly used estimators when surveying natural resources. In this article, we propose a new sampling strategy that incorporates ranking information from nearby locations into a spatially balanced sample. If the population exhibits spatial trends, our simple local ranking strategy can improve the precision of commonly used estimators. Numerical results on several test populations with different spatial structures show that local ranking can improve the performance of a spatially balanced design. To show that local ranking is simple and effective in practice, we provide an example application for the health and productivity assessment of a Shiraz vineyard in South Australia.

Supplementary materials accompanying this paper appear online.

空间抽样设计确定样本位置在研究区域中的位置，以便可以高精度地估计总体参数。空间平衡设计抽取具有良好空间分布的样本，并在调查自然资源时为常用的估计器提供精确的结果。在本文中，我们提出了一种新的采样策略，将来自附近位置的排名信息整合到空间平衡的样本中。如果人口表现出空间趋势，我们简单的局部排序策略可以提高常用估计器的精度。对具有不同空间结构的几个测试群体的数值结果表明，局部排序可以提高空间平衡设计的性能。为了表明局部排序在实践中简单有效，

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