Information Theory provides a fundamental basis for analysis, and for a variety of subsequent methodological approaches, in relation to uncertainty quantification. The transversal character of concepts and derived results justifies its omnipresence in scientific research, in almost every area of knowledge, particularly in Physics, Communications, Geosciences, Life Sciences, etc. Information-theoretic aspects underlie modern developments on complexity and risk. A proper use and exploitation of structural characteristics inherent to spatial data motivates, according to the purpose, special considerations in this context.

In this paper, some relevant approaches introduced regarding the informational analysis of spatial data, related aspects concerning complexity analysis, and, in particular, implications in relation to the structural assessment of multifractal point patterns, are reviewed under a conceptually connective evolutionary perspective.

信息论为不确定性定量分析和各种后续方法论方法提供了基础。概念和衍生结果的横向特性证明了它在几乎所有知识领域的科学研究中的无处不在，尤其是在物理，通信，地球科学，生命科学等领域。信息理论方面是复杂性和风险的现代发展的基础。根据目的，在此情况下，正确使用和利用空间数据固有的结构特征会引起特殊考虑。

在本文中，从概念上关联的进化角度对一些引入的有关空间数据信息分析的相关方法，有关复杂性分析的相关方面，尤其是与多分形点模式的结构评估有关的含义进行了综述。