Kei-ichi Okunuki

The SANET Toolbox: New Methods for Network Spatial Analysis

This paper describes new methods, called network spatial methods, for analysing spatial phenomena that occur on a network or alongside a network (referred to as network spatial phenomena). First, the paper reviews network spatial phenomena discussed in the related literature. Second, the paper shows the uniform network transformation, which is used in the study of non-uniform distributions on a network, such as the densities of traffic and population. Third, the paper outlines a class of network spatial methods, including nearest neighbor distance methods, K-function methods, cell count methods, clumping methods, the Voronoi diagrams and spatial interpolation methods. Fourth, the paper shows three commonly used computational methods to facilitate network spatial analysis. Fifth, the paper describes the functions of a GIS-based software package, called SANET, that perform network spatial methods. Sixth, the paper compares network spatial methods with the corresponding planar spatial methods by applying both methods to the same data set. This comparison clearly demonstrates how different conclusions can result. The conclusion summarizes the major findings.

A Computational Method for Estimating the Demand of Retail Stores on a Street Network and its Implementation in GIS

This paper describes a computational method for estimating the demand of retail stores on a street network using GIS. First, the ‘network Huff model’ is formulated on a network with the shortest-path distance as an extension of the ordinary Huff model (which assumes a continuous plane with Euclidean distance). Second, using this model, a formula for estimating the demand is derived. This estimation formula is similar to that with the ordinary Huff model, but it has an advantage in that the formula exactly computes the demand on a network. Third, a practical method for computing the formula is developed. Finally, a method of implementing this computational method in a GIS environment is shown.

Solving the Huff-Based Competitive Location Model on a Network with Link-Based Demand

This paper shows a computational method for optimizing the location of a store on a network in a competitive environment, assuming that consumers probabilistically choose stores following the Huff model (1963) and that the store can be located on a continuum of a network. This method gives the exact optimal solution with the computational order of nN2 log nN where nN is the number of nodes of the network.

A computational method for optimizing the hierarchy and spatial configuration of successively inclusive facilities on a continuous plane

Abstract This paper shows a computational method for optimizing a system of successively inclusive hierarchical facilities (a system in which the services provided by a certain rank of facilities include all services provided by lower rank facilities) on a continuous plane. The system is optimized with respect to not only the configuration of ranked facilities, but also its hierarchical structure (i.e. the composition of the number of ranks and the numbers of ranked facilities). The optimization procedure has two steps. The first step optimizes a system of exclusive hierarchical facilities by an analytical method. Using this optimal solution, the second step optimizes a system of successively inclusive hierarchical facilities by a computational search method. Numerical experiments show that the proposed method tends to reach a near optimal solution within a few iterations.

Sketch map analysis using GIS buffer operation

We developed a method to analyze sketch maps by GIS, and applied it to an actual case study. We found that analysis using buffer operation was more effective for sketch map analyses than other methods, such as the entire road length method and area method. After modeling the buffer method, an experimental study of the micro-genetic cognitive process was conducted on sketch maps from Japanese students and Brazilian residents in Japan.

Urban analysis with GIS

This paper discusses how GIS (Geographic Information System) can contribute to the research field of urban analysis. The purpose of urban analysis is to explain the processes of spatial distributions in urban areas. For this purpose, urban analysts often need to manipulate large amounts of spatial data. This is the reason why urban analysis cannot advance without GIS. Analysts can visualize urban affairs using GIS and find the processes of spatial distributions. For example, in this paper, land use distributions in Nagoya City, Japan are visually analyzed with ArcView GIS. This analysis demonstrates that GIS can contribute to urban analysis. After this analysis, future work is discussed based on the reviews of recent studies on urban analysis using GIS.

A Toolbox for Spatial Analysis on a Network

Some of you who heard my presentation in the last GIScience meeting might think this tile looks similar to the last title. Actually it looks similar but not exactly the same. The last time, the title was TOWARD a toolbox for spatial analysis on a network. Two years have passed since then, and our project has progressed, but we have not yet completed this project. Today I am going to present the latest outcome of this project. This project has been conducted by Okunuki, Funamoto, Ishitomi and me. Today, I, Okabe, will talk.

Urban and rural geographies of aging: a local spatial correlation analysis of aging population measures

The spatial distribution of aging populations is commonly measured with either the aging population ratio or the aging population density. Used in isolation, however, these measures may fail to detect aging communities in certain types of urban or rural setting. This study uses both indices simultaneously to identify types and locations of aging communities more accurately. We investigate the spatial distribution of these communities using a standard correlation analysis and bivariate local spatial statistic analysis. Empirical analysis of geospatial data of the Aichi Prefecture in Japan suggests that using both indices allows us to capture different types of aging communities in diverse contexts (e.g. depopulated rural areas, pockets of aging communities in urban areas, and growing concentrations of aging population in the suburbs). The analysis uses data sets aggregated at different areal scales, confirming the generally stable nature of the outcome, despite some scale sensitivity.

Geography of urban ageing and rural ageing: a local spatial correlation analysis of the ageing population ratio in relation to the ageing population density

The spatial distribution of aging populations is commonly measured with either the aging population ratio or the aging population density. Used in isolation, however, these measures may fail to detect aging communities in certain types of urban or rural setting. This study uses both indices simultaneously to identify types and locations of aging communities more accurately. We investigate the spatial distribution of these communities using a standard correlation analysis and bivariate local spatial statistic analysis. Empirical analysis of geospatial data of the Aichi Prefecture in Japan suggests that using both indices allows us to capture different types of aging communities in diverse contexts (e.g. depopulated rural areas, pockets of aging communities in urban areas, and growing concentrations of aging population in the suburbs). The analysis uses data sets aggregated at different areal scales, confirming the generally stable nature of the outcome, despite some scale sensitivity.