Adaptive geovisualization has been marked as a research front that addresses design issues of a user-centered geovisualization system. By constantly keeping trace of user actions, a highly adaptive geovisualization system is able to predict the behavior of its end user and accordingly provide him with the visualization that suits best his personal taste and need. An adaptive geovisualization system does not either hide its own behaviors from its end users. Such a mutual transparency is made possible by the mechanism of self-description and self-evaluation coupled with the capability of self-organization and self-navigation based on user models. This paper clarifies some major concepts and techniques of adaptive geovisualization, pinpoints the existing bottlenecks, analyses the main components of an adaptive geovisualization system, and put forward some research directions. Among others, the authors have discussed topics such as adaptive GUI design, dynamic structuring and re-structuring of databases, adaptive design of geo-query functions (intelligent geo-database navigation), adaptive symbolilzation etc.
This paper gives an overview of the existing interactive information systems for mobile users. Based on a study of the general characteristics of mobile information acquisition, the author stresses the necessity to design the self-explaining system which has to balance various design constraints concerning the hardware configuration, the user interface and the content presentation. A number of rules guiding the self-explaining design for the mobile human-machine interaction are outlined according to two essential criteria--the immediate usability and the user adaptation. However, these introduced rules are helpful only so far as to exclude bad designs. For this reason, an outlook is given on future researches that address the issues such as formalization of frequently reoccurring use cases, development of action-driven design solutions and pattern-oriented optimization of human-machine interaction.
In every map, irrespective of its theme, objects are represented at a reduced scale. Map contents do not decrease proportionally to the reduction of the map size. Usually an increasing density of the map contents occurs at smaller scales. That is where the generalization plays an important role. Generalization is the process of creating a legible map at a given scale from a more detailed geographical dataset. It is done in such a manner that the character or essence of the original features is retained at successively smaller scales. Though the purposes and benefits of generalization are manifold it is indeed a complex decision-making process which must be intelligently steered by goals and rules from the geographical application domain such that the generalized representation conveys knowledge consistent with the reality. In recent past, lot of work has been done in 2D generalization (Beard, 1991; Weibel, 1995; Bealla, 1995; Ruas and Plazanet, 1996; Sarjakoski and Kilpel?inen, 1999) which defines a set of operations to be performed with the goal to achieve the similar results to those from manual generalization. But 3D generalization is altogether perceived differently. A given 3D urban area mostly consists of roads and buildings. These buildings are of different styles and features. Further the city area may be viewed from different angles and at different heights. So generalization in general and aggregation in particular must deal with all these issues. In this paper, an effort has been made to address these issues.
Qualitative modelling of spatial relationships has often been considered as a context-independent task that aims at a reasoning model in generic form. Despite the primary interest in these models, there is still a sufficiently large scope for context-dependent reasoning in space and time. This paper proposes a qualitative spatial reasoning model, oriented to the modelling and simulation of several cars acting in a multi-lane circuit, which can be considered as an illustrative example of a constrained frame of reference. The modelling objects of interest are individual cars whose cardinal relationships to external cars and actions are modelled. This dynamic system is analysed, and a set of interrelationships is identified at different levels of abstraction, together with inference rules that model the displacement of several cars in a circuit. The potential of this model is illustrated and calibrated using an agent-based prototype.
GISs are moving away from a system for experts to a more widely-used tool for answering spatial-related questions. The dawn of new technologies on the horizon, such as telecommunication, mobile Internet, and handheld computing devices, offers new chances to the everyday use of geoinformation. However, the existing approaches to mobile visualisation of geoinformation mostly have a commercial background and are rather technology-centred. This quite narrow view ignores many relevant problems and does not fully profit from the new possibilities a mobile cartography could provide. Taking the existing problems into account the paper sketches a general conceptual framework for geoinformation use in a mobile environment. Specific user tasks and requests in a mobile environment are identified, which is followed by an outline of possible methods to personalise a GIS for better mobile assistance. Putting emphasis on the importance of analytical functions for mobile cartography, the process of adaptive and dynamic generation of visualisations for mobile users on the basis of vector data (e.g. SVG) is illustrated and the key research fields involved are pointed out.
A typical requirement in digital society is the rapid distribution and effective application of digital products. Geographical data bases are far more complex than other ones in that both attribute and spatial data have to be stored and handled under the same framework. On the other hand, the number of end users of digital cartographic data is explosively increasing, ranging from professional map makers to vehicle drivers and individual tourists. Thus arises a question: how can a data supplier give the “best” service to each user? In nature it involves such difficult problems as cartographic generalization and map simplification. In this paper, the author argues that the visual knowledge or perception experience can be effectively exploited and used to guide the process of data simplification. We have developed a prototype system with a subset of the vector road database covering Munich city.
The paper deals with 3D cartography. Using the program 3D studio max (Autodesk) a flight over an alpine region (“Watzmann-Massif”) is animated. In addition to a description of the project some thoughts and ideas especially about generalisation degree are discussed.
This paper reports a spatial data mining prototype system developed at the Technical University of Munich in cooperation with NavTech. The system serves the purpose of value-adding the road database maintained by NavTech. In the original database, each road element is described by more than 110 attributes. A number of algorithms on the basis of entropy theory, rough-set modeling have been implemented to rank the individual attributes and detect the dependencies among attributes based on their values in an arbitrarily selected region. Other algorithms are developed on the basis of road geometry and devoted to the quantitative description of spatial patterns such as routes and urban structures. With the knowledge of relative importance of the individual attributes, users are given the flexibility to buy a local road database with truncated attribute list. By observing the ranking list and correlation matrix calculated for different regions, information that reflects the regional differences of a road network can be extracted. Likewise, the changes in ranking list and correlation matrix of the same region after removing or adding a route imply the relative importance of this particular route.
Virtual reality (VR) technology, coupled with GIS technology and functions, has created a geo-virtual environment (GeoVE) and attracted human awareness of geo-cognition. GeoVE can help understand geo-environment and phenomena, and innovates the ways of spatial concept formation. Recently, many applications have appeared to suggest its substantial potential for simulating environment and exploring human cognitive aspects. However, the validation of environment simulation and enhancement of human geo-cognition, in terms of their degree of realism and reliability, has so far lagged behind.
Along with the advances in computer sciences in recent years, visualization has been developed to embrace new functions. The electronic map in a spatial information visualization system is an electronic tool of human spatial cognition and has more advantages in supporting human spatial cognition than a printed map. Investigations on the ability of human spatial cognition are increasingly drawing attention of cartographers. In this background, map spatial cognition research is attached importance to cartographers again. Cognition-based visualization systems are intelligent systems that serve human spatial cognition efficiently. Developing adaptive multi-perspective visualization systems of spatial information as one kind of these systems is a main goal of our research. This paper discusses the necessity and the characteristics of map spatial cognition research. The cognitive issues involved in spatial information visualization and major contents of cognitive research in the design of adaptive visualization system are presented. Finally, the experimental methods of electronic map visual cognition are introduced.
Automated cartographic generalization has been an intensive research topic in cartography for decades. Some problems associated with this topic could be resolved to a certain extent using fractal analysis and fractal dimension. This paper investigates the fundamental theories and operational methods of generalization. Among others, methods of calculating fractal dimensions of curves and even complicated 3-dimensional geographic objects are explained. Fractal dimensions can be used as an objective criterion for both scaling the natural geographic objects and economical computer storage. More important is that the generalization algorithms based on fractal dimensions can be performed automatically.
This paper explores a new approach towards the distributed e-map service with CORBA. The architecture of a distributed e-map service model is described. This model mainly contains a distributed map database, a database connection layer, an application service layer and a client layer. For the sake of convenient transmission of map data, a combination of CORBA and GML method is introduced. Furthermore, in order to keep the loading balance among distributed servers, object migration is implemented among servers and security is considered.