Fuzzy Sets Approach to Spatial Analysis and Planning, a Nontechnical Evaluation

Abstract

Uncertainty in spatial analysis and planning has conventionally been treated as a consequence of random occurrence of exact spatial events. The present paper, however, argues that fuzziness is actually a major contributory factor to most of the uncertain spatial behavior. Exactitude in representing, analyzing, and predicting human behaviors over space and time is difficult if not impossible to accomplish in a fuzzy environment characterized by ambiguous or incomplete information and inexact cognitive and decision-making processes. Fuzzy sets theory is proposed as an appropriate framework for a formal representation and analysis of inexact spatial concepts, structures, and processes, in place of a technical presentation, the versatility of fuzzy sets theory in spatial analysis and planning is discussed from a pedagogical point of view. Applications of the theory to the conceptualization of imprecise spatial concepts, analysis of uncertain spatial behavior, and spatial decision analysis and planning are examined. Directions for further research in these areas are proposed. Compared to conventional methods, fuzzy sets approach appears to be more natural and powerful in analyzing imprecision of human spatial behaviors. Policy analysis and planning with inexact information and value-based standards can also be effectively handled. Though the development and applications of fuzzy sets theory to spatial analysis and planning has been limited and fragmentary, its potential contributions to various areas of research such as behavioral geography, cartography, remote sensing, and soft spatial data analysis are perceivable. It may prove to be a promising direction for the reconstruction of existing theories and the formulation of new theories and models of uncertainty in spatial analysis and planning.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 24 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.