Deconstruction of fractals and its implications for cartographic education

The research reported here was designed for two reasons: firstly, to involve anyone with an interest in cartographic visualization to participate in eliciting cartographic knowledge and to provide them with the opportunity to contribute their practical knowledge and opinions; and secondly, to inform the design of algorithms for line generalization. In the past, there has been some resistance to such mining and codification of expert knowledge. However, many cartographers now welcome highly interactive computer graphics, computer mapping, and virtual reality systems as providing them with new opportunities for launching cartography into a new creative age. Despite nearly thirty years of research on line generalization algorithms, the available algorithms are somewhat simplistic. This research, undertaken under the auspices of the BCS Design Group, explored the behavioural tendencies of cartographers engaged in line filtering. The results show that a carefully contrived, even if obviously artificial, exercise on the deconstruction of lines into meaningless forms can prompt cartographers to observe, record, and discuss their own cognitive processing

The Visvalingam algorithm: metrics, measures and heuristics

This paper provides the background necessary for a clear understanding of forthcoming papers relating to the Visvalingam algorithm for line generalisation, for example on the testing and usage of its implementations. It distinguishes the algorithm from implementation-specific issues to explain why it is possible to get inconsistent but equally valid output from different implementations. By tracing relevant developments within the now-disbanded Cartographic Information Systems Research Group (CISRG) of the University of Hull, it explains why a) a partial metric-driven implementation was, and still is, sufficient for many projects but not for others; b) why the Effective Area (EA) is a measure derived from a metric; c) why this measure (EA) may serve as a heuristic indicator for in-line feature segmentation and model-based generalisation; and, d) how metrics may be combined to change the order of point elimination. The issues discussed in this paper also apply to the use of other metrics. It is hoped that the background and guidance provided in this paper will enable others to participate in further research based on the algorithm

A computer science perspective on the bendsimplification algorithm

The primary aim of this study was to evaluate whether the use of bends provides a better basis than point elimination for research on line structuring. These investigations were undertaken using Arc/Info 7.1.1. Comparative experimental results suggest that the algorithm may not be as widely applicable as the much simpler geometric filters, such as the Douglas-Peucker or Visvalingam algorithms. The paper therefore provides a brief review of these three algorithms. A more detailed conceptual and empirical evaluation of the bendsimplification system follows, highlighting some problems with implementing the system in Arc/Info. The paper then questions the value of over-coupling model- and image-oriented generalization processes within the black-box bendsimplification system. It suggests the type of parameters which could enhance the utility and usability of the Bendsimplify option within the Arc/Info (and perhaps also within the ArcView) environment and provides some pointers for further research. With respect to the main aim of the research, the evidence suggests that bendsimplification is less useful for line segmentation than Visvalingam's algorithm. Further research is needed to assess the value of the iterative bend elimination operator within bendsimplification

Simplification and generalization of large scale data for roads : a comparison of two filtering algorithms

This paper reports the results of an in-depth study which investigated two algorithms for line simplification and caricatural generalization (namely, those developed by Douglas and Peucker, and Visvalingam, respectively) in the context of a wider program of research on scale-free mapping. The use of large-scale data for man-designed objects, such as roads, has led to a better understanding of the properties of these algorithms and of their value within the spectrum of scale-free mapping. The Douglas-Peucker algorithm is better at minimal simplification. The large-scale data for roads makes it apparent that Visvalingam's technique is not only capable of removing entire scale-related features, but that it does so in a manner which preserves the shape of retained features. This technique offers some prospects for the construction of scale-free databases since it offers some scope for achieving balanced generalizations of an entire map, consisting of several complex lines. The results also suggest that it may be easier to formulate concepts and strategies for automatic segmentation of in-line features using large-scale road data and Visvalingam's algorithm. In addition, the abstraction of center lines may be facilitated by the inclusion of additional filtering rules with Visvalingam's algorithm

Effectiveness of silhouette rendering algorithms in terrain visualisation

Silhouette Rendering Algorithms have been successfully used in various applications such as communicating shape and cartoon rendering.This paper explores how effective silhouette rendering algorithms could be used in terrain visualisation. This approach has been implemented in a 3D modelling system to create a new method of displaying and viewing terrain data in an artistic style. Real terrain data has been used to test the effectiveness of the algorithm.The resulting terrain images are closer to human drawn illustration than to shaded images