Robert G. Cromley

Coupling land use allocation models with raster GIS

Abstract. As geographic information systems (GIS) have moved from information storage and retrieval operations towards more decision support functions, there is a need for more integration of spatial analytical modules that can assist in locational decisions. This paper presents a methodology for coupling land use allocation models with a raster GIS. For raster systems, the integration of any decision module has been limited by the size of raster datasets that may contain hundreds of thousands of pixels. Therefore, decision heuristics have been used rather than exact methods such as mathematical programming models. For the problem of land use allocation, the special structure of the generalized assignment problem is used here to handle large scale datasets. The advantage of the mathematical programming approach is the additional information associated with the dual variables and opportunity costs that can be used in subsequent sensitivity analyses.

Singly- and Doubly-Constrained Methods of Areal Interpolation for Vector-based GIS

Traditionally, areal interpolation has referred to techniques for transferring attribute values from one partitioning of space to a different partition of space but this is only one of several situations that create the need for estimating unknown data values for areal units. This paper presents a categorization of four areal interpolation problems that includes the “missing” data problem, the traditional “alternative geography” problem, the overlay of a choropelth and an area-class data layer, and the overlay of two choropleth data layers and demonstrates the relationship between the last three problems and general spatial interaction modelling. The “alternative geography” and overlay of choropleth and area-class data layers mirrors a singly constrained spatial interaction model while the overlay of two choropleth layers is analogous to a doubly constrained interaction model. Iterative proportional fitting techniques with and without ancillary data are developed to solve these three classes of problems.

A comparison of optimal classification strategies for choroplethic displays of spatially aggregated data

Abstract A debate has ensued from the question of whether the attribute values of spatially aggregated data need to be classified prior to the display operator for representation as a choropleth map. Some recent studies have concluded that choropleth maps using Jenks optimal classification scheme are more easily interpretated than either unclassed maps or more traditional classification methods. This paper presents a range of optimal classification strategies for displaying spatially aggregated data including techniques designed to enhance value identification.

Hierarchical Methods of Line Simplification

An important preprocessing operator in a digital mapping system is line simplification. A line-simplification operator generalizes digital, geographic base files to ensure that the amount of information to be displayed played matches the geographic scale at which it is displayed. Many different simplification algorithms have been proposed to accomplish this task. Each algorithm has an implicit objective regarding which points to retain when caricaturizing a line. Each caricature is dependent on a tolerance level specified at the outset. This paper proposes a hierarchical approach to line simplification. Hierarchical classification methods are frequently used to group objects by their thematic attributes. A similar method is now used for the parallel problem of line simplification. The advantage of this approach is that a set of line caricatures corresponding to alternate tolerance levels can be calculated and compactly stored in tree or list structures.

Land‐Use Allocation in the Absence of Complete Market Values

This paper describes a method of land-allocation that can be used byplanners and other land managers in the face of market failure. The method integrates theland-allocation approach used in geographic information systems with that used in a generalizedassignment problem. Suitability scores, instead of market prices, are used in assigning competingland uses to individual parcels (pixels) of land. The method is illustrated using a hypotheticalexample involving three competing land uses within a region.

Using geographically weighted regression to solve the areal interpolation problem

Areal interpolation is used to transfer attribute information from the initial set of source units with known values to the target units with unknown values before subsequent spatial analysis can occur. The areal units with unknown attribute information can be either at a finer scale or misaligned with respect to the source data layer. This article presents and describes a geographically weighted regression (GWR) method for solving areal interpolation problems for nested areal units and misaligned areal units. Population data, selected as the attribute information, are interpolated from census tracts to block groups (a finer scale) and pseudo-tracts (misaligned from tracts but at the same approximate scale). Root mean square error, adjusted root mean square error, and mean absolute error are calculated to evaluate the performance of the interpolation methods. The land cover data derived from Landsat Thematic Mapper Satellite Imagery with a 30×30 m spatial resolution are applied to as the ancillary data to describe the underlying distribution of population. To evaluate the utility of GWR as an areal interpolation method, the simple areal weighting method, a dasymetric method, and different ordinary least squares regression methods are used in this article as comparison methods. Results suggest that GWR is a better interpolator for the misaligned data problem than for the finer scale data problem. The latter is a result of issues associated with the scaling step to ensure the pycnophylatic property required in areal interpolation.

Merger and acquisition fields for large United States cities 1955–1970

Green M. B. and Cromley R. G. (1984) Merger and acquisition fields for large United States cities, 1955–1970, Reg. Studies 18, 291–301. Theories of merger and acquisition activity implicitly assume a national scale of locations for acquisition candidates. In fact, however, acquisitions and mergers are made within a regional scale. The acquisition patterns of New York City, Los Angeles, and Chicago demonstrate this. The extent of these acquisition fields are examined both cartographically and through the use of competing destinations spatial interaction models. It is shown that the spatial extent of these acquisition fields has increased over the period 1955–70.

The Pattern and Impact of the Filter Down Process in Nonmetropolitan Kentucky

An important facet of the changing pattern of economic activity in the United States has been the decentralization of branch plant operations to nonmetropolitan areas. Standardization of production processes in metropolitan areas permits the extension of operations into smaller communities to maintain continued cost savings for the parent firm. The research examines the role of transportation, industrial sites, labor supplies, and labor competition as determinants of the spatial development of branch firms in nonmetropolitan Kentucky. The analysis also focuses on (1) branch employment changes between 1970 and 1980 disaggregated by town size, (2) changes in the sectoral distribution of plants between 1950 and 1980, and (3) the current distribution of branch plants within SIC categories. The results suggest that community infrastructure rather than labor supply alone is important in accounting for employment levels. In addition, short-term employment changes are more a function of external as opposed to int...

THE HORIZONTAL MERGER: ITS MOTIVES AND SPATIAL EMPLOYMENT IMPACTS

This paper examines the importance of horizontal mergers as a form of investment activity that has spatial ramifications. The complexity and motivations of horizontal mergers and the following rationalization process are illustrated by a case study of a firm in the pulp and paper industry. In addition, pre-merger and post-merger employment levels of individual plants in a number of manufacturing sectors are compared for the period 1972–1978. Every industry and region of the United States experienced an increase in employment in the period immediately following the horizontal merger. The rationalization process is seen as having a positive impact on employment levels in the short run.

Choropleth map legend design for visualizing community health disparities

BackgroundDisparities in health outcomes across communities are a central concern in public health and epidemiology. Health disparities research often links differences in health outcomes to other social factors like income. Choropleth maps of health outcome rates show the geographical distribution of health outcomes. This paper illustrates the use of cumulative frequency map legends for visualizing how the health events are distributed in relation to social characteristics of community populations. The approach uses two graphs in the cumulative frequency legend to highlight the difference between the raw count of the health events and the raw count of the social characteristic like low income in the geographical areas of the map. The approach is applied to mapping publicly available data on low birth weight by town in Connecticut and Lyme disease incidence by town in Connecticut in relation to income. The steps involved in creating these legends are described in detail so that health analysts can adopt this approach.ResultsThe different health problems, low birth weight and Lyme disease, have different cumulative frequency signatures. Graphing poverty population on the cumulative frequency legends revealed that the poverty population is distributed differently with respect to the two different health problems mapped here.ConclusionCumulative frequency legends can be useful supplements for choropleth maps. These legends can be constructed using readily available software. They contain all of the information found in standard choropleth map legends, and they can be used with any choropleth map classification scheme. Cumulative frequency legends effectively communicate the proportion of areas, the proportion of health events, and/or the proportion of the denominator population in which the health events occurred that falls within each class interval. They illuminate the context of disease through graphing associations with other variables.