The Illinois Resource Information System: Early Innovations in Geographic Information System Design

Marc P. Armstrong

The Illinois Resource Information System (IRIS) was designed and implemented in the early 1970s by computer scientists at the University of Illinois. These researchers did not continue to work in the emerging field of Geographic Information Systems (GIS), and as a consequence, IRIS innovations were not reported in the GIS literature. IRIS operated across the then-new ARPANet, making it the first networked GIS. The system also had an interactive query language with a rich syntax. Retrievals in IRIS were optimized to promote high levels of interactivity. The development of IRIS had elements in common with the first supercomputer (ILLIAC IV), which was designed at the University of Illinois during that time period. A student who worked on the IRIS project also produced the first doctoral dissertation with “Geographic Information Systems” in its title.

A New Algorithm for Continuous Area Cartogram Construction with Triangulation of Regions and Restriction on Bearing Changes of Edges

Ryo Inoue and Eihan Shimizu

A continuous area cartogram is a transformed map in which regions are resized relative to their data. It is considered an effective visualization tool for statistical data, and many solutions have been proposed. However, most of these solutions are not mathematically clear or user friendly; further, they do not provide visually elegant area cartograms. An essential condition for the construction of a visually elegant area cartogram is that the resultant region shape should resemble the corresponding regions on geographical maps. Since it is impossible to determine the shape of a region based only on the information of size, area cartogram construction is an ill-posed problem that requires regularization. In this study, we propose a construction algorithm that involves triangulation of regions and regularization through restrictions on the bearing changes of the edges in order to obtain visually clear results. First, we formulate a construction using nonlinear least squares. Then, by linearizing, we derive a simple formula to create area cartograms. The application of our algorithm to the USA population datasets reveals that our algorithm has mathematical clarity and is user friendly. Keywords: Continuous area cartogram, map transformation, visualization, triangulation

Using Semi-variance Image Texture Statistics to Model Population Densities

Shuo-sheng Wu, Xiaomin Qiu, and Le Wang

This study presents a method to model population densities by using image texture statistics of semi-variance. In a case study of the City of Austin, Texas, we first selected sample census blocks of the same land use to build population models by land use. Regression analyses were conducted to infer the relationship between block population densities and image texture statistics of the semi-variance. We then applied the population models to an area of 251 blocks to estimate populations for within-blocks land-use areas while maintaining census block populations. To assess the proposed method, the same analysis was performed while census block-group populations were maintained, and the aggregated block populations were compared with original census block populations. We also tested a conventional land-use-based dasymetric mapping method with pre-calculated population densities for land uses. The results show that our approach, which is based on initial land-use stratification and further image-texture statistical modeling of population, has higher accuracy statistics than the conventional land-use-based dasymetric mapping method.

Keywords: Dasymetric mapping, population density, population disaggregation

A GIS Analysis of the Relationship between Criminal Offenses and Parks in Kansas City, Kansas

Nicole DeMotto and Caroline P. Davies

Most urban green space research focuses on the social benefits of parks and recreational areas. However, in areas with high levels of resource deprivation and physical disorder, parks may function as criminal marketplaces. Parks in such areas may cease to provide net benefits to the surrounding community and instead serve as a vector for criminal activity. Parks in eastern Kansas City, Kansas, are examined in terms of the probability of criminal marketplaces and beneficial social contribution. Variables for resource deprivation and social disorder are calculated for the study area and compared to national aggregates to identify which parks may behave as criminal marketplaces. In such cases, parks should exhibit an inverse relationship between distance from a park and number of criminal offenses per acre. Evaluating the incidence of crime near parks using geographic information systems (GIS) buffer analysis, proximity analysis, and spatial statistics demonstrates that parks in areas of extreme resource deprivation do not serve beneficial social roles, and some parks contradict conventional criminal justice and urban economic theory. Keywords:  Urban green space, parks, criminal offenses, criminal marketplace, Kansas City

Can Error Explain Map Differences Over Time?

Robert Gilmore Pontius Jr and Christopher D Lippitt

This paper presents methods to test whether map error can explain the observed differences between two points in time among categories of land cover in maps. Such differences may be due to two reasons: error in the maps and change on the ground. Our methods use matrix algebra: (1) to determine whether error can explain specific types of observed categorical transitions between two maps, (2) to represent visually the differences between the maps that error cannot explain, and (3) to examine how the results are sensitive to possible variation in map error. The methods complement conventional accuracy assessment because they rely on standard confusion matrices that use either a random or a stratified sampling design. We illustrate the methods with maps from 1971 and 1999, which show seven land-cover categories for central Massachusetts. The methods detect four transitions from agriculture, range, forest, and barren in 1971 to built in 1999, which a 15 percent error cannot explain. Sensitivity analysis reveals that if the accuracy of the maps were less than 77 percent, then error could explain virtually all of the observed differences between the maps. The paper discusses the assumptions behind the methods and articulates priorities for future research.

Keywords:  Accuracy, hypothesis, change, land, matrix, uncertainty