Model

A model is an abstraction of the real world. Models are developed and used in geography to simplify the enormous complexity of the earth's surface and to look for analogues for geographic processes in the[Page 306] work of other disciplines. The most basic geographic model is a map—a simplification of the world that allows people to navigate around their neighborhoods and cities without getting lost in a sea of detail. Maps enable geographers to portray on paper or on a computer screen the physical and social processes they wish to study. Any individual map involves hundreds of choices about what to include and not to include, how to symbolize a particular feature, the scale most appropriate for the problem at hand, and the map projection to be used. Any individual map is the mapmaker's best judgment about how to simplify or model the real world. Similarly, any individual model represents what the model builder believes to be the essential features of the processes in which he or she is interested.

A classic 1967 volume edited by British geographers Richard Chorley and Peter Haggett, Models in Geography, linked model building and pattern seeking in geography to the growing scientific orientation of the discipline, a prevalent trend at that time. They argued that a good model is simple enough to be understood by its users, representative enough to be used in a wide variety of circumstances, and complex enough to capture the essence of the phenomenon under investigation. Models can be static depictions of the spatial structure of a system at one point in time or dynamic representations of systemic change over time. From a research perspective, they are bridges between the empirical world of what we observe and the theoretical world of prediction and explanation.

Models often are represented in statistical and mathematical terms. For example, the gravity model from physics was used extensively to represent spatial flows such as migration, trade, and commuting. According to the rules of the gravity model, spatial interaction increases with the population of the origin and destination and decreases with growing distance between them. Of course, we know that many other characteristics of places determine flows among them, but model builders identify population and intervening distances as essential features of movement systems. Optimization models evaluate the trade-offs people make among conflicting goals, for example, among efficiency, equity, and environmental protection. Facility siting often uses this type of modeling to evaluate the trade-offs involved in any particular spatial configuration of hospitals, child care centers, welfare offices, and (potentially) hydrogen refueling stations. Human geographers also have relied on graphic models to represent the spatial organization of agricultural and urban land uses, the geography of development, the diffusion of innovations, and spatial organization of the settlement system.

Statistical and computational models are experiencing a resurgence in human geography due to the enormous power and popularity of geographic information systems (GIS). Statistical models use statistical concepts to represent real-world elements and their interactions. Computational models use the computer as an integral part of the modeling process, and the outputs often are visual and highly interactive. Computational models often involve “what if” simulations, and their outputs often are visual and interactive in nature. The two are combined to produce dynamic landscape model simulations that formalize thinking about what is and is not important about the landscape, articulate how the landscape behaves in response to various stimuli, develop plans for how the landscape is used, and produce time–space simulations regarding potential futures of the landscape.

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