Gary J. Hunter

A simple positional accuracy measure for linear features

In this paper we propose a simple technique for assessing the positional accuracy of digitized linear features. The approach relies on a comparison with a representation of higher accuracy, and estimates the percentage of the total length of the low accuracy representation that is within a specified distance of the high accuracy representation. The approach deals successfully with three deficiencies of other methods: it is statistically based; is relatively insensitive to extreme outliers; and does not require matching of points between representations. It can be implemented using standard functions and a standard scripting language in any raster or vector GIS. We present the results of a test using data from the Digital Chart of the World.

Responding to the consequences of uncertainty in geographical data

The presence of uncertainty in geographical data has the potential to expose users to undesirable consequences in their decision making. Accordingly, our efforts to understand uncertainty seek to (a) avoid the use of data that are not suitable for their intended purpose (that is, data whose consequences are unacceptable), (b) to reduce any undesirable consequences to an acceptable level, and (c) to devise ways of living with undesirable data when the adverse consequences caused by poor data do not alter our ultimate decision choice. To assist this task, we propose an approach where the adverse consequences of uncertainty caused by the use of unsuitable geographical data are expressed in terms of risk. In this paper we first show that risk management offers geographical data users a range of options for responding to the adverse consequences of data uncertainty, and secondly we present and discuss the various risk response options.

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.

The development of a historical digital cadastral database

With an ever-increasing number of land information systems being developed, there is a growing demand by users for systems which support the use of temporal data for time-based studies. System managers, however, may have difficulty responding to these calls because of the lack of available research to guide them in their task. This paper examines the simple method of storing and processing temporal graphical data by the addition of time-encoding attributes to data elements as required. To illustrate the technique, a historical digital cadastral database has been created which al lows users to display and report on the cadastral parcellation of a region at any time in the past. The method can also be widely applied to other data to assist a broad range of space/time-related studies.

Communicating uncertainty in spatial databases

As applications of spatial databases become more sophisticated and diverse, an issue of growing concern is the inability to communicate to users the uncertainty of products derived from their systems. This is important not only because users should be able to compare the quality of database outputs against the quality requirements of their tasks (in order to determine product suitability), but also to protect the integrity of past, present, and future decisions that may be made through the use of such information. While there has already been considerable research undertaken to develop models of spatial data error and uncertainty, there is an additional requirement for the results of these models to be effectively conveyed to users. This paper reviews advances now being made in communicating the uncertainty of spatial databases which may soon assist users in overcoming this critical barrier.

Understanding error in spatial databases

Abstract This paper provides a three-part classification of error that establishes a relationship between sources of error, forms of error and final product error in spatial databases. It aims to inform users of both the types of error that may be inherent in data they acquire for their applications, and errors which may occur as the result of their own actions in managing and analysing data within a Geographic Information System (GIS). The framework for spatial database error presented also helps focus attention on areas where future research is needed to make spatial error more tractable for users.

Spatial Data Quality - Problems and Prospects

This paper reflects upon the topic of spatial data quality and the progress made in this field over the past 20-30 years. While international standards have been established, theoretical models of error developed, new visualization techniques introduced, and metadata now routinely documented for spatial datasets, difficulties nevertheless exist with the way data quality information is being described, communicated and applied in practice by users. These problems are identified and the paper suggests how the spatial information community might move forward to overcome these obstacles.

Making the Trade-Off between Decision Quality and Information Cost

mal decision-science methods to help us understand the qualA growing problem confronting users of remotely sensed imagery ity of our decisions, as opposed to the conventional standardsis whether the use of additional or different imagery to improve based approaches of the past where acceptable quality levels decision quality is actually justified by its cost. This paper dis- are pre-defined according to commonly used data accuracy cusses how to compare these competing factors so that an ac- standards. ceptable trade-off may be made between them. The proposed Once computed, the application of decision analytical method is based on probabilistic cost-benefit analysis. The measures of uncertainty importance is relatively straightforconcept of “value of information” is introduced in a practical ward, and the use of additional information should only be case study using remote sensing to verify farmers’ declarations employed if the expected benefits to arise from using that inforfor a crop subsidy program in the European Union. Application mation are higher than the associated costs. In turn, the best of the method requires that (1) the problem at hand can be method of information acquisition for the decision to be taken represented by a decision tree, (2) the desirability of each de- is the one that results in the largest positive difference between cision outcome can be expressed numerically, (3) the imagery the expected desirability of the decision outcome and the costs reveals information about the occurrence of events not under involved. This approach is valid for utility-based decision makthe decision maker’s control, and (4) the probabilities of these ing in which decisions are based on the valuation of outcomes events and the extent to which they are detectable in remotely (Morgan and Henrion, 1990, p. 25). sensed imagery can be assessed.

Non-current data and geographical information systems A case for data retention

Abstract Geographical information systems (GIS)provide rapid access to large volumes of current (up-to-date)data, but what will be the fate of non-current (superceded) data created by continuous updating within these systems? Could any of these latter records be of value to GIS users, either now or in the future? The variety of uses of non-current geographical data is investigated and it is demonstrated that some types of data possess residual value which merit their retention; long after they have ceased to be current. GIS managers should realise that non-current data often remain useful for land management purposes and have untapped market potential.

Towards a Methodology for the Evaluation of Multimedia Geographical Information Products

The design and production of multimedia and interactive maps could seem to have more in common with video and film production than digital map production and software development. The processes employed apply different methodologies to map making and the talents and skills of the personnel involved are different, diverse and, in many cases, unlike those needed for conventional mapping. The evaluation of multimedia geographical information products could be undertaken using a different manner than that employed for evaluating conventional. This paper discusses the unique evaluation requirements for multimedia mapping and GIS products which include multimedia. It then outlines how the methods used to evaluate multimedia publications might be used as a model for developing an evaluation procedure unique to this type of contemporary mapping commodity.