In the field of cartography, there is occasionally a need to create a distribution of dots on a map. These dots should give an impression of the density of some countable object set. This type of map is called a "Dot Distribution Map".Up to the current time, if the dots are to represent reality at all, they have to be placed by hand by a cartographer using a digitizing tablet or other input device. This is due to the fact that a census of a region gives only a total, yet it is known that the densities vary within that region. A cartographer can look at all the data available about a region and then can make judgements about how the densities will change within the region. He then can place dots which represent his interpretation of reality.This thesis states that there exists an algorithm which would assign dots to a map based upon the common belief that the density will gradate smoothly from one region with one census value to another region with a different census value.The approach taken was to relate the Map regions to polygons and to then subdivide the polygons into triangles. These triangles would then be subdivided into six children recursively and the data stored in a hex-tree. This is the current level of development. the next steps will be:Generate a surface above the 2-D map based upon the known input data of counts for the various regions.From the centroid for each existing leaf on the Hex-Tree, find the corresponding Zi value from the surface information. From each of these leaves, recursively subdivide the triangle further until the number of dots indicated by the Zt. value can be placed on the map. / Department of Computer Science

Call number: LD2668 .P7 1975 K85

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The process of automated cartographic generalization is critically reviewed, and methods developed for implementation and analysis are discussed. The manner in which automated generalization relates to manual cartographic methods and feature representation is analyzed. It is suggested that the nature of representation of linear features on maps be considered in the analysis of effectiveness of automated generalization. The development of a computer platform for evaluating linear generalization algorithms is described and three studies which make use of the platform are discussed. An analysis of the performance of five simplification algorithms is compared to performance of a random simplification algorithm. It was found that in most cases tested, the five simplification algorithms performed better than random. An analysis of the stability of fractal dimension estimated on simplified lines was conducted and it is suggested that the fractal dimension is a poor guide for linear simplification due the instability in measurement. An examination of the effect of generalization on linear features as represented by contoured topography and paired stream bank lines was performed. Through the use of measurements of slope on contour lines and width on stream lines, it was determined that automated generalization has an effect on linear feature representations. Guidelines for application of linear generalization algorithms are suggested and needs and direction for future research are discussed. / Master of Science

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The main scope of this project is to rebuild and deploy web applications that will help share historical artifacts related to the Santa Ana watershed. This project is designed to give a consistent user interface and add extra tools to enhance the functionality of existing applications at the Water Resources Institute (WRI) at California State University San Bernardino (CSUSB). The purpose of this project is to migrate all applications to a single server and update the applications using ArcGIS Server 9.2. Also to give a consistent look to the applications and to make them user friendly.