ABSTRACT
In conventional terms, geographers regard spatial analysis as a broad and comprehensive undertaking that entails the use of well-established analytical/visualization tools and procedures to analyze and synthesize locationally referenced data. The approaches are rigorous and are drawn from statistical, mathematical, and geographical principles to conduct a systematic examination of spatial patterns and processes, including the exploration of interactions between space and time. Studying the locational and distributional arrangement of objects, people, events, and processes in space, and the underlying factors that account for these arrangements are some of the analytical goals of a geospatial data scientist. The work requires a place-based mindset with emphasis on uncovering spatial patterns and spatial linkages, and examining spatial behaviors and complex interactions within and across locations that result in these distributional patterns.
