Kirsi Virrantaus

Developing GIS-supported location-based services

Mobile networking is developing and proliferating at a high speed. Many estimates say that the number of mobile telecom subscribers will exceed 1 billion in the year 2003. Among the terminals deployed, there will be hundreds of millions of Internet-enabled ones making Mobile Internet a reality for the big masses. The terminals and/or the mobile networks are now able to determine the position of the terminal on the earth with more and more precision. This is the basis for the new class of services called Location-Based Services (LBS). The paper discusses this new emerging application area that some people consider the central novel application class of Mobile Internet. The main topic of the paper is the question, how Geographic Information Systems (GIS) and the data hosted currently by them could be used in the context of LBS. We analyze their properties and relate them with the needs of LBS. We also present our LBS pilot system that is using XML-based vector formal for city maps and runs on Java-enabled mobile terminals, PDAs and smartphones.

Identifying Critical Locations in a Spatial Network with Graph Theory

Effective management of infrastructural networks in the case of a crisis requires a prior analysis of the vulnerability of spatial networks and identification of critical locations where an interdiction would cause damage and disruption. This article presents a mathematical method for modelling the vulnerability risk of network elements which can be used for identification of critical locations in a spatial network. The method combines dual graph modelling with connectivity analysis and topological measures and has been tested on the street network of the Helsinki Metropolitan Area in Finland. Based on the results of this test the vulnerability risk of the network elements was experimentally defined. Further developments are currently under consideration for eventually developing a risk model not only for one but for a group of co-located spatial networks.

A spatio-temporal population model to support risk assessment and damage analysis for decision-making

The aim of this research is to develop and implement a simple spatio‐temporal model of population location that might improve risk assessment and damage analysis for decision‐making in both the Finnish Fire and Rescue Services and the Finnish Defence Forces. The motivation for the research is that present risk models do not take into account the temporal variation in population location during different times of the day. We use spatio‐temporal modelling methods to model the population dynamics, and visualization techniques to represent the model outcomes. In addition, we apply the developed model to a damage‐analysis application. The case study site is located in the centre of Helsinki. The model uses a basic population and workplace dataset maintained by the Helsinki Metropolitan Area Council. By means of this model, we intend to advance risk assessment, which considers the consequences of accidents. This model has the potential to help decision‐makers evaluate their plans in several application areas—such as achieving better preparedness by having more reliable evacuation plans and resource allocation. In addition to the application‐related technological research, a more generic framework about decision‐making supported by spatio‐temporal knowledge and visualization is presented.

Analysis of Vulnerability of Road Networks on the Basis of Graph Topology and Related Attribute Information

The safety of people and the security of the vital functions of society are among the core tasks of governments. Various networks, especially transportation networks, are important for human life. Therefore, the government should place greater emphasis on preparedness planning and mitigation actions. Much research has been done to analyse the vulnerability of road networks and most of the methods were based on analysing the topological structure of the network using only topological attributes. This paper introduces a multi-attribute value theory which can combine all the attributes’ values, not only topological but also non-topological, and weight them according to a decision maker’s preference in order to produce an overall value. This overall value is used to compute the vulnerability of a road network. A road has a higher overall value is considered more vulnerable and more effort needs to be put into preparedness in crisis management. In this paper, a decision making software package Web-HIPRE is also introduced and illustrated.

Knowledge and Reasoning in Spatial Analysis

Reasoning is an essential part of any analysis process. Especially in visual analytics, the quality of the results depends heavily on the knowledge and reasoning skills of the analyst. In this study, we consider how to make the results transparent by visualizing the reasoning and the knowledge, so that persons from outside can trace and verify them. The focus of this study is in spatial analysis and a case study was carried out on a process of off-road mobility analysis. In the case study, linked views of a map and a PCP were identified as reasoning artifacts. The knowledge used by the analyst was formed by these artifacts and the tangible pieces of information identified in them, along with the mental models of the analyst′s mind. To make the results transparent, the tangible pieces of information were marked with sketches and the mental models were presented in causal graphs because it was found that causality was central to the reasoning process in the case study. The causal graph allows the reasoning of the analyst to be studied, as well as traced back to its origin.

The role of GI-supported methods in crisis management

Abstract Crisis and disaster management has become an important research field in GIS during recent years. Risk assessment and situation picture-related work are particularly important areas of interest. There are distinct phases in different crises; these can be roughly divided into mitigation, preparedness, response, and recovery. In this paper a general classification of methods in each phase is given with examples on recent or ongoing research projects. The framework is based on literature and experiences from crisis and disaster-related exercises. Three case studies are based on those exercises. The goal is to clarify the role and usability of various GI-supported methods in the crisis management process by outlining a theoretical framework and presenting examples of the developed methods. Continuously increasing amount of spatially related geographic information is a huge potential to the GI analysis and modeling methods; the concept of digital earth is the underlying mainstream that gives lots of promise to the research and development work in this field.

Indoor and Outdoor Mobile Navigation by Using a Combination of Floor Plans and Street Maps

Positioning and map technology integrated to smart mobile devices allows the users to locate themselves and find routes between locations. Such route finding typically works only outdoors due to reliance on the GPS system and lack of indoor map data. This work introduces a prototype for combined indoor and outdoor mobile navigation system for a university campus. An important part of the prototype implementation is the conversion of CAD floor plans to GIS data that can be used together with existing outdoor maps for locating and for finding shortest routes between locations. This work describes a semi-automatic conversion process that produces indoor map data, which is combined with OpenStreetMap and Bing map data for route finding and displaying a hybrid map. The prototype application, which uses this data, has been implemented on the iPad. The prototype uses GPS for outdoor positioning and QR codes for indoor positioning. The work is currently in process, and future prospects of the prototype are discussed.

Visualization of Spatial Data Structures on Different Levels of Abstraction

Spatial data structures are used to manipulate location data. The visualization of such structures faces many challenges that are not relevant in the visualization of one-dimensional data. The visualized data can be represented using several different types of visual metaphors. These metaphors can be divided into several different levels of abstraction depending on the purpose of the visualization. This paper proposes a division of data structure visualization into four levels of abstraction, and shows how these abstractions can be taken into account in the visualization of spatial data structures.

Using Explorative Spatial Analysis to Improve Fire and Rescue Services

Within this paper we examine the use of explorative spatial analysis methods to enhance the calculation and representation of an emergency risk assessment for the Finnish fire and rescue services in the metropolitan area of the Finnish capital Helsinki (including Espoo, Vantaa and Kauniainen). Some of these methods are available in existing GIS (Geographic Information System) software. Within the strategic levels of planning and management, improvements in the identification of high or low risk areas can assist the emergency preparedness planning and resource evaluation. To enhance the determination of a risk area we visualize the spatial distribution of phenomena like population distribution, building types, workspace distribution etc. and their relevance to the emergency services. In this paper we examine the relation between population density distribution and incident density. To visualize potential variables indicating risk areas we use the third dimension. The results of the paper show that by developing explorative visualizations one can enhance the process of finding and integrating these variables into risk analysis. Within this paper we suggest innovative types of maps as tools for decision makers, which can be used to attract the public to participate in planning procedures.

3D personal navigation in smart phone using geocoded images

Three-dimensional personal navigation in smart phones develops in a fantastic speed nowadays. This topic has already attracts many attentions both from the scientific and industrial field. Such kind of 3D navigation application is mostly fulfilled by importing 3D models constructed in a computer into a mobile phone. However, comparing the computer platform, the mobile devices typically have the several limitations such as a weaker CPU, less memory and other hardware restrictions. All these limitations severely restrict the performance of the 3D personal navigation. The paper proposes a novel solution which is based on geocoded images rather than the 3D models to mitigate these technical restrictions in a smart phone platform and achieves a better performance and smoother human-computer interaction. We design a program base on S60 platform running on a Nokia 6710 handset. A five layers configuration is applied in this program. An arc-direction-distance geocoding method is adopted for the file nomination. Several lab and field tests were carried out to compare various aspects between the geocoded image based solution with 3D model based solution and evaluate the performance of the proposed solution. In addition, this solution provides an optional way to decrease the labor cost and working time by building up a similar solution using photos instead of complex 3D model construction.