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Conceptual Frameworks for Spatial Analysis
Geospatial analysis provides a distinct perspective on the world, a unique lens through which to examine events, patterns, and processes that operate on or near the surface of our planet. It makes sense, then, to introduce the main elements of this perspective, the conceptual framework that provides the background to spatial analysis, as a preliminary to the main body of this Guide’s material. This chapter provides that introduction. It is divided into four main sections. The first, Basic Primitives, describes the basic components of this view of the world — the classes of things that a spatial analyst recognizes in the world, and the beginnings of a system of organization of geographic knowledge. The second section, Spatial Relationships, describes some of the structures that are built with these basic components and the relationships between them that interest geographers and others. The third section, Spatial Statistics, introduces the concepts of spatial statistics, including probability, that provide perhaps the most sophisticated elements of the conceptual framework. Finally, the fourth section, Spatial Data Infrastructure, discusses some of the basic components of the data infrastructure that increasingly provides the essential facilities for spatial analysis.
The domain of geospatial analysis is the surface of the Earth, extending upwards in the analysis of topography and the atmosphere, and downwards in the analysis of groundwater and geology. In scale it extends from the most local, when archaeologists record the locations of pieces of pottery to the nearest centimeter or property boundaries are surveyed to the nearest millimeter, to the global, in the analysis of sea surface temperatures or global warming. In time it extends backwards from the present into the analysis of historical population migrations, the discovery of patterns in archaeological sites, or the detailed mapping of the movement of continents, and into the future in attempts to predict the tracks of hurricanes, the melting of the Greenland ice-cap, or the likely growth of urban areas. Methods of spatial analysis are robust and capable of operating over a range of spatial and temporal scales.
Ultimately, geospatial analysis concerns what happens where, and makes use of geographic information that links features and phenomena on the Earth’s surface to their locations. This sounds very simple and straightforward, and it is not so much the basic information as the structures and arguments that can be built on it that provide the richness of spatial analysis. In principle there is no limit to the complexity of spatial analytic techniques that might find some application in the world, and might be used to tease out interesting insights and support practical actions and decisions. In reality, some techniques are simpler, more useful, or more insightful than others, and the contents of this Guide reflect that reality. This chapter is about the underlying concepts that are employed, whether it be in simple, intuitive techniques or in advanced, complex mathematical or computational ones.
Spatial analysis exists at the interface between the human and the computer, and both play important roles. The concepts that humans use to understand, navigate, and exploit the world around them are mirrored in the concepts of spatial analysis. So the discussion that follows will often appear to be following parallel tracks — the track of human intuition on the one hand, with all its vagueness and informality, and the track of the formal, precise world of spatial analysis on the other. The relationship between these two tracks forms one of the recurring themes of this Guide.