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Human conceptions of spaces: Implications for GIS

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The way people conceptualize space is an important consideration for the design of GIS, because a better match with people's thinking is expected to lead to easier‐to‐use information systems. Everyday space, the basis to GIS, has been characterized in the literature as being either small‐scale (from table‐top to room‐size spaces) or large‐scale (inside‐of‐building spaces to city‐size spaces). While this dichotomy of space is grounded in the view from psychology that people's perception of space, spatial cognition, and spatial behaviour are experience‐based, it is in contrast to current GIS, which enable us to interact with large‐scale spaces as though they were small‐scale or manipulable. We analyse different approaches to characterizing spaces and propose a unified view in which space is based on the physical properties of manipulability, locomotion, and size of space. Within the structure of our framework, we distinguish six types of spaces: manipulable object space (smaller than the human body), non‐manipulable object space (greater than the human body, but less than the size of a building), environmental space (from inside‐of‐building spaces to city‐size spaces), geographic space (state, country, and continent‐size spaces), panoramic space (spaces perceived via scanning the landscape), and map space. Such a categorization is an important part of Naive Geography, a set of theories on how people intuitively or spontaneously conceptualize geographic space and time, because it has implications for various theoretical and methodological questions concerning the design and use of spatial information tools. Of particular concern is the design of effective spatial information tools that lead to better communication.

Document Type: Original Article


Affiliations: 1: Department of Geography, University of Minnesota — Duluth, Duluth, Minnesota 55812, USA. 2: National Center for Geographic Information and Analysis, Department of Spatial Information Science and Engineering, Department of Computer Science, 5711 Boardman Hall, University of Maine, Orono, Maine 04469–5711, USA.

Publication date: December 1, 1997


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