SANET: A Toolbox for Spatial Analysis on a Network

This article shows a geographical information systems (GIS)-based toolbox for analyzing spatial phenomena that occur on a network (e.g., traffic accidents) or almost along a network (e.g., fast-food stores in a downtown). The toolbox contains 13 tools: random point generation on a network, the Voronoi diagram, the K -function and cross K -function methods, the unconditional and conditional nearest-neighbor distance methods, the Hull model, and preprocessing tools. The article also shows a few actual analyses carried out with these tools.     

Stable state conditions of population-dependent migration models under a zero natural growth rate

The author "attempts to examine the stable conditions of regional population under a zero natural growth rate in the context of a certain general class of [population-dependent] nonlinear migration models." Theorems regarding the stable state conditions of the migration models are presented. The parameters of the gravity migration model are then estimated empirically using data on Japanese inter-prefectural migration flows in 1966, 1970, and 1975. The possibility of achieving the stable state in Japan is discussed     

An Extended K Function Method for Analyzing Distributions of Polygons with GIS

The objective of this paper is to develop a K function method for analyzing distributions of polygon-like entities in the real world by extending Ripley’s K function method. Many empirical studies using the K function method assume that entities are represented by points. If entities are small enough in comparison with a study area, this approximation may be acceptable. If not, polygon-like entities may not be approximated by points. To deal with polygon-like entities, this paper develops a K function method for analyzing distributions of polygons. First, the paper shows a method for extending the local K function of points to that of polygons. Second, the paper compares the result obtained from the K function of polygons with that of the points representing the polygons and shows a distinctive difference. Third, the paper formulates the cross K function method of polygons to analyze the relationship between two distributions of polygons of different kinds. Fourth, the paper implements the methods in GIS. Last, the paper applies the cross K function method of polygons to actual distributions of buildings of different uses in Aoyama, Tokyo.