Regularities exist in datasets describing spatially distributed physical phenomena. Human experts often understand alize the regularities as abstract spatial objects evolving coherently and interacting with each other in the domain e describe a novel computational approach for identifying and extracting these abstract spatial objects through the construction of ahierarchy of spatial relations. We demonstrate the approach with an application to finding pressure trough features in weather data sets.