CaGIS vol. 28, no.2

Representing Complex Geographic Phenomena in GIS

May Yuan

Conventionally, spatial data models have been designed according to object- or field-based conceptualizations of reality. Conceptualization of complex geographic phenomena that have both object- and field-like properties, such as wildfire and precipitation, has not yet been incorporated into GIS data models. To this end, a new conceptual framework is proposed in this research for organizing data about such complex geographic phenomena in a GIS as a hierarchy of events, processes, and states. In this framework, discrete objects are used to show how events and processes progress in space and time, and fields are used to model how states of geographic themes vary in a space-time frame. Precipitation is used to demonstrate the construction and application of the proposed framework with digital precipitation data from April 15 to May 22, 1998, for the state of Oklahoma, U.S.A. With the proposed framework, two sets of algorithms have been developed. One set automatically assembles precipitation events and processes from the data and stores the precipitation data in the hierarchy of events, processes, and states, so that attributes about events, processes, and states are readily available for information query. The other set of algorithms computes information about the spatio-temporal behavior and interaction of events and processes. The proposed approach greatly enhances support for complex spatio-temporal queries on the behavior and relationships of events and processes

Improving the Quality of Mass Produced Maps

Jeff Simley

Quality is critical in cartography because key decisions are often made based on the information the map communicates. The mass production of digital cartographic information to support geographic information science has now added a new dimension to the problem of cartographic quality, as problems once limited to small volumes can now proliferate in mass production programs. These problems can also affect the economics of map production by diverting a sizeable portion of production cost to pay for rework on maps with poor quality. Such problems are common to general industry-in response, the quality engineering profession has developed a number of successful methods to overcome these problems. Two important methods are the reduction of error through statistical analysis and addressing the quality environment in which people work. Once initial and obvious quality problems have been solved, outside influences periodically appear that cause adverse variations in quality and consequently increase production costs. Such errors can be difficult to detect before the customer is affected. However, a number of statistical techniques can be employed to detect variation so that the problem is eliminated before significant damage is caused. Additionally, the environment in which the workforce operates must be conducive to quality. Managers have a powerful responsibility to create this environment. Two sets of guidelines, known as Deming's Fourteen Points and ISO-9000, provide models for this environment.

KEYWORDS: Cartographic production, quality engineering, geospatial data, normal variation, process capability, control chart, quality environment, ISO-9000.

Modifications of Tanaka's Illuminated Contour Method

Patrick Kennelly and A. Jon Kimerling

Visualization of topography can be greatly facilitated by the illuminated contour method. This method, popularized in a hand-drafted map by Tanaka, uses a gray background with black and white contours. A direction of illumination is assumed, and white contours represent illuminated topography, while black contours represent non-illuminated or shaded areas. Additionally, thickness of contours varies with the cosine of the angle between the azimuth of maximum slope (i.e., aspect) and the azimuth of illumination. We modified Tanaka's method by basing thickness of contour lines on twice the cosine of the angle between the surface normal and the illumination vector. The cosine of this angle is most commonly used in analytical hill shading. In addition, we present maps with changes in other visual variables and offer our evaluations. Lines with gray tones instead of black and white lines do not improve the illumination effect. We believe variations in the colors of contours and background with elevation can visually enforce information regarding topography. Our use of colors for aspect and variations in the width of contours for slope adds information to the map but does not assist with visualization of topography.

KEYWORDS: Illuminated contours, Tanaka method, relief contour method, analytical hill shading, aspect-slope map, MKS-ASPECTTM, geographic visualization

Dasymetric Mapping and Areal Interpolation: Implementation and Evaluation

Cory L. Eicher and Cynthia A. Brewer

Dasymetric maps display statistical data in meaningful spatial zones. Such maps can be preferable to choropleth maps that show data by enumeration zones, because dasymetric zones more accurately represent underlying data distributions. Though dasymetric mapping has existed for well over a century, the methods for producing these maps have not been thoroughly examined. In contrast, research on areal interpolation has been more thorough and has examined methods of transferring data from one set of map zones to another, an issue that is applicable to dasymetric mapping. Inspired by this work, we tested five dasymetric mapping methods, including methods derived from work on areal interpolation. Dasymetric maps of six socio-economic variables were produced for a study area of 159 counties in the eastern U.S. using county choropleth data and ancillary land-use data. Both polygonal (vector) and grid (raster) dasymetric methods were tested. We evaluated map accuracy using both statistical analyses and visual presentations of error. A repeated-measures analysis of variance showed that the traditional limiting variable method had significantly lower error than the other four methods. In addition, polygon methods had lower error than their grid-based counterparts, though the difference was not statistically significant. Error maps largely supported the conclusions from the statistical analysis, while also presenting patterns of error that were not obvious from the statistics.

KEYWORDS: Dasymetric mapping, areal interpolation, mapping census data, map error