A development of spatiotemporal queries to analyze the simulation outcomes from a voxel automata model

The raster and vector spatial data models are the most commonly used in geographic information systems (GIS) practice but are insufficient for the representation of dynamic spatiotemporal phenomena that operates in multiple dimensions. Although numerous improvements to the spatial data models have been proposed and various prototype implementations have been developed in order to address this limitation, the problem has persisted. One of the proposals for spatial data representation is the geoatom data model which is a theoretical concept used for conceptualizing geographic information as it pertains to the four-dimensional (4D) space-time continuum. The objective of this study is to develop and apply the spatiotemporal queries in order to analyze and explore the evolution of the 4D geospatial process. The geo-atom data model and voxel automata have been used for the simulation of a dynamic 4D process of snow cover retreat in order to test the developed theoretical concepts. The developed queries for spatio-temporal analysis are volume, surface area, rate of change and temporal ordering. The data used have spatial, temporal and attribute components and represent the voxels units generated from the simulation of the process. Obtained results are the outcomes of various spatio-temporal queries that permit the analysis of the snow retreat process in 4D. This study contributes to conceptual and applied advancements in the field of 4D GIS and multidimensional analysis, and is relevant to geography, earth and environmental sciences, the disciplines where the phenomena need to be studied in 4D.