All digital data contain error and many are uncertain. Digital models of elevation surfaces consist of files containing large numbers of measurements representing the height of the surface of the earth, and therefore a proportion of those measurements are very likely to be subject to some level of error and uncertainty. The collection and handling of such data and their associated uncertainties has been a subject of considerable research, which has focused largely upon the description of the effects of interpolation and resolution uncertainties, as well as modelling the occurrence of errors. However, digital models of elevation derived from new technologies employing active methods of laser and radar ranging are becoming more widespread, and past research will need to be re-evaluated in the near future to accommodate such new data products. In this paper we review the source and nature of errors in digital models of elevation, and in the derivatives of such models. We examine the correction of errors and assessment of fitness for use, and finally we identify some priorities for future research.
Virtual Field Trips (VFTs) have a valuable role in supporting and enhancing real eldwork and empowering students who are disadvantaged nancially or physically. The development of good VFT and VFT tools is still in its infancy and full 'virtuality' is still many years away. This article traces the evolution of virtual eld trips, outlining their advantages and disadvantages and provides a brief overview of the materials and approaches currently becoming available.
The landscape in which people live is made up of many features, which are named and have importance for cultural reasons. Prominent among these are the naming of upland features such as mountains, but mountains are an enigmatic phenomenon which do not bear precise and repeatable definition. They have a vague spatial extent, and recent research has modelled such classes as spatial fuzzy sets. We take a specifically multiresolution approach to the definition of the fuzzy set membership of morphometric classes of landscape. We explore this idea with respect to the identification of culturally recognized landscape features of the English Lake District. Discussion focuses on peaks and passes, and the results show that the landscape elements identified in the analysis correspond to well-known landmarks included in a place name database for the area, although many more are found in the analysis than are named in the available database. Further analysis shows that a richer interrogation of the landscape can be achieved with Geographical Information Systems when using this method than using standard approaches. key words fuzzy sets landforms morphometry multi-scale analysis mountains the Lake District
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