Abstract: Cognitive categories in the geographic realm appear to manifest certain special features as contrasted with categories for objects at surveyable scales. We have argued that these features reflect specific ontological characteristics of geographic objects. This paper presents hypotheses as to the nature of the features mentioned, reviews previous empirical work on geographic categories, and presents the results of pilot experiments that used English-speaking subjects to test our hypotheses. Our experiments show geographic categories to be similar to their non-geographic counterparts in the ways in which they generate instances of different relative frequencies at different levels. Other tests, however, provide preliminary evidence for the existence of important differences in subjects ’ categorizations of geographic and non-geographic objects, and suggest further experimental work especially with regard to the role in cognitive categorization of different types of objectboundaries at different scales.

This paper presents a modeling process in order to produce a realistic simulation of crowds in the ancient Greek agora of Argos. This place was a social theater in which two kinds of collective phenomena took place: interpersonal interactions (small group discussion and negotiation, etc.) and global collective phenomena, such as flowing and jamming. In this paper, we focus on the second type of collective human phenomena, called non-deliberative emergent crowd phenomena. This is a typical case of collective emergent selforganization. When a great number of individuals move within a confined environment and under a common fate, collective structures appear spontaneously: jamming with inner collapses, organized flowing with queues, curls, and vortices, propagation effects, etc. These are particularly relevant features to enhance the realism- more precisely the "truthfulness "- of models of this kind of collective phenomena. We assume that this truthfulness is strongly associated with the concept of emergence: evolutions are not predetermined by the individual characters, but emerge from the interaction of numerous characters. The evolutions are not repetitive, and evolve on the basis of small changes. This paper demonstrates that the physically-based interacting particles system is an adequate candidate to model emergent crowd effects: it associates a large number of elementary dynamic actors via elementary non-linear dynamic interactions. Our model of the scene is regulated as a large, dynamically coupled network of second order differential automata. We take advantage of symbolic non-photorealistic and efficient visualization to render the style of the person, rather than the person itself. As an artistic representation, NPR reinforces the symbolic acceptance of the scene by the observer, triggering an immediate and intuitive recognition of the scene as a plausible scene from ancient Greece.

This paper presents a formalized ontological framework for the analysis of multiscale classifications of geographic objects. We propose a set of logical principles that guide such geographic classifications. Then we demonstrate application of these principles on a practical example of the "National Hierarchical Framework of Ecological Units". The framework has a potential to be used to facilitate interoperability between such geographic classifications