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Randomness and order in the topology of settlement systems
Economic Geography
|January 1, 1982
Summary
This study introduces a new method to analyze settlement systems using linear programming. The novel linkage similarity index offers advantages over traditional spatial autocorrelation measures for understanding settlement network topology.
Area of Science:
- Spatial analysis
- Urban planning
- Network theory
Background:
- Settlement systems are complex networks.
- Analyzing their structure is crucial for urban planning.
- Existing methods like Geary's contiguity coefficient have limitations.
Purpose of the Study:
- To develop a new linear programming methodology for analyzing settlement system structure.
- To introduce and evaluate a novel index of linkage similarity.
- To compare the new index with Geary's contiguity coefficient.
Main Methods:
- Linear programming applied to settlement link frequency distribution.
- Calculation of a system topology index.
- Comparison with Geary's contiguity coefficient for spatial autocorrelation.
- Analysis of four Canadian and two hypothetical settlement systems.
Main Results:
- The proposed linear programming method effectively analyzes settlement system topology.
- The new index of linkage similarity demonstrates advantages over Geary's contiguity coefficient.
- Both indices were applied to evaluate the topology of real and hypothetical settlement systems.
Conclusions:
- The linkage similarity index provides a valuable tool for understanding settlement system structure.
- This methodology offers a more nuanced approach compared to traditional spatial autocorrelation measures.
- The findings contribute to improved analysis of urban and regional settlement networks.