The breadth of spatial analytics relied on in geography is remarkable. These methods are used to gain insight, typically in the context of planning, management, decision making, and policymaking. The challenge is invariably establishing meaning in obtained findings, providing insights and knowledge. This is done, however, in very different ways depending on the spatial analytic approach, with statistical notions of significance a prevailing tool in assessment. This article reviews significance assessment approaches in the application of spatial analytics. Noteworthy in this review is that many approaches can be considered through the lens of sampling. In some cases, the underlying sample is a few or as small as one. There are methods, however, that are based on sampling that is comprehensive, involving an implicit or explicit enumeration of all possible outcomes. This suggests that significance assessment using certain methods accounts for the entire range of possibilities, whereas other methods draw inference from scant sampling. In addition to the sampling perspective, extrapolation as well as indirect accuracy and anecdotal measures of assessment are not uncommon. The comparative review of spatial analytic methods suggests that significance is assessed in many different ways, making meaning interpretation challenging.

地理学所依赖的空间分析的广度是显着的。这些方法用于获得洞察力，通常是在规划、管理、决策和政策制定的背景下。挑战总是在获得的发现中建立意义，提供见解和知识。然而，这取决于空间分析方法，以非常不同的方式完成，显着性统计概念是评估中的主要工具。本文回顾了空间分析应用中的重要性评估方法。在这篇评论中值得注意的是，可以通过抽样的角度考虑许多方法。在某些情况下，基础样本很少或只有一个。然而，有些方法基于全面的抽样，涉及所有可能结果的隐式或显式枚举。这表明使用某些方法的显着性评估解释了整个可能性范围，而其他方法则从少量抽样中得出推断。除了抽样观点外，外推法以及间接准确性和轶事评估措施并不少见。空间分析方法的比较审查表明，重要性以许多不同的方式进行评估，这使得意义解释具有挑战性。外推法以及间接准确性和轶事评估措施并不少见。空间分析方法的比较审查表明，重要性以许多不同的方式进行评估，这使得意义解释具有挑战性。外推法以及间接准确性和轶事评估措施并不少见。空间分析方法的比较审查表明，重要性以许多不同的方式进行评估，这使得意义解释具有挑战性。