Visualization in spatial modeling

This chapter deals with issues arising from a central theme in contemporary computer modeling - visualization. We first tie visualization to varieties of modeling along the continuum from iconic to symbolic and then focus on the notion that our models are so intrinsically complex that there are many different types of visualization that might be developed in their understanding and implementation. This focuses the debate on the very way of 'doing science' in that patterns and processes of any complexity can be better understood through visualizing the data, the simulations, and the outcomes that such models generate. As we have grown more sensitive to the problem of complexity in all systems, we are more aware that the twin goals of parsimony and verifiability which have dominated scientific theory since the 'Enlightenment' are up for grabs: good theories and models must 'look right' despite what our statistics and causal logics tell us. Visualization is the cutting edge of this new way of thinking about science but its styles vary enormously with context. Here we define three varieties: visualization of complicated systems to make things simple or at least explicable, which is the role of pedagogy; visualization to explore unanticipated outcomes and to refine processes that interact in unanticipated ways; and visualization to enable end users with no prior understanding of the science but a deep understanding of the problem to engage in using models for prediction, prescription, and control. We illustrate these themes with a model of an agricultural market which is the basis of modern urban economics - the von Thünen model of land rent and density; a model of urban development based on interacting spatial and temporal processes of land development - the DUEM model; and a pedestrian model of human movement at the fine scale where control of such movements to meet standards of public safety is intrinsically part of the model about which the controllers know intimately. © Springer-Verlag Berlin Heidelberg 2006

Planning Support Systems: Progress, Predictions, and Speculations on the Shape of Things to Come

In this paper, we review the brief history of planning support systems, sketching the way both the fields of planning and the software that supports and informs various planning tasks have fragmented and diversified. This is due to many forces which range from changing conceptions of what planning is for and who should be involved, to the rapid dissemination of computers and their software, set against the general quest to build ever more generalized software products applicable to as many activities as possible. We identify two main drivers – the move to visualization which dominates our very interaction with the computer and the move to disseminate and share software data and ideas across the web. We attempt a brief and somewhat unsatisfactory classification of tools for PSS in terms of the planning process and the software that has evolved, but this does serve to point up the state-ofthe- art and to focus our attention on the near and medium term future. We illustrate many of these issues with three exemplars: first a land usetransportation model (LUTM) as part of a concern for climate change, second a visualization of cities in their third dimension which is driving an interest in what places look like and in London, a concern for high buildings, and finally various web-based services we are developing to share spatial data which in turn suggests ways in which stakeholders can begin to define urban issues collaboratively. All these are elements in the larger scheme of things – in the development of online collaboratories for planning support. Our review far from comprehensive and our examples are simply indicative, not definitive. We conclude with some brief suggestions for the future

A Phase Field Model for Continuous Clustering on Vector Fields

A new method for the simplification of flow fields is presented. It is based on continuous clustering. A well-known physical clustering model, the Cahn Hilliard model, which describes phase separation, is modified to reflect the properties of the data to be visualized. Clusters are defined implicitly as connected components of the positivity set of a density function. An evolution equation for this function is obtained as a suitable gradient flow of an underlying anisotropic energy functional. Here, time serves as the scale parameter. The evolution is characterized by a successive coarsening of patterns-the actual clustering-during which the underlying simulation data specifies preferable pattern boundaries. We introduce specific physical quantities in the simulation to control the shape, orientation and distribution of the clusters as a function of the underlying flow field. In addition, the model is expanded, involving elastic effects. In the early stages of the evolution shear layer type representation of the flow field can thereby be generated, whereas, for later stages, the distribution of clusters can be influenced. Furthermore, we incorporate upwind ideas to give the clusters an oriented drop-shaped appearance. Here, we discuss the applicability of this new type of approach mainly for flow fields, where the cluster energy penalizes cross streamline boundaries. However, the method also carries provisions for other fields as well. The clusters can be displayed directly as a flow texture. Alternatively, the clusters can be visualized by iconic representations, which are positioned by using a skeletonization algorithm.

Advanced content-based semantic scene analysis and information retrieval: the SCHEMA project

The aim of the SCHEMA Network of Excellence is to bring together a critical mass of universities, research centers, industrial partners and end users, in order to design a reference system for content-based semantic scene analysis, interpretation and understanding. Relevant research areas include: content-based multimedia analysis and automatic annotation of semantic multimedia content, combined textual and multimedia information retrieval, semantic -web, MPEG-7 and MPEG-21 standards, user interfaces and human factors. In this paper, recent advances in content-based analysis, indexing and retrieval of digital media within the SCHEMA Network are presented. These advances will be integrated in the SCHEMA module-based, expandable reference system

Interaction between high-level and low-level image analysis for semantic video object extraction

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