Causal inference in spatial statistics

Finding cause–effect relationships behind observed phenomena remains a challenge in spatial analysis. In recent years, much progress in causal inference has been made in statistics, economics, epidemiology and computer sciences, but limited progress has been made in spatial statistics due to the nonrandom, nonrepeatability and synchronism of spatial data. In this paper, we investigate the problem. We first refine the issues of causal inference, then discuss the causal inference issue in spatial statistics, next review the causal inference methods in other disciplines and analyze their potential to be used with cross-sectional data, and finally we look forward prospect of causal inference in spatial statistics.