Steve Wise

Exploring multiple viewshed analysis using terrain features and optimisation techniques

The calculation of viewsheds is a routine operation in geographic information systems and is used in a wide range of applications. Many of these involve the siting of features, such as radio masts, which are part of a network and yet the selection of sites is normally done separately for each feature. The selection of a series of locations which collectively maximise the visual coverage of an area is a combinatorial problem and as such cannot be directly solved except for trivial cases. In this paper, two strategies for tackling this problem are explored. The first is to restrict the search to key topographic points in the landscape such as peaks, pits and passes. The second is to use heuristics which have been applied to other maximal coverage spatial problems such as location-allocation. The results show that the use of these two strategies results in a reduction of the computing time necessary by two orders of magnitude, but at the cost of a loss of 10% in the area viewed. Three different heuristics were used, of which Simulated Annealing produced the best results. However the improvement over a much simpler fast-descent swap heuristic was very slight, but at the cost of greatly increased running times.

Problems of bias in mapping linear landforms from satellite imagery

Remotely sensed images are an important data source for the mapping of glacial landforms and the reconstruction of past glacial environments. However the results produced can differ depending on a wide range of factors related to the type of sensors used and the characteristics of the landforms being mapped. This paper uses a range of satellite imagery to explore the three main sources of variation in the mapped results: relative size, azimuth biasing and landform signal strength. Recommendations include the use of imagery illuminated with low solar elevation, although an awareness of the selective bias introduced by solar azimuth is necessary. Landsat ETM+ imagery meets the requirements for glacial landform mapping and is the recommended data source. However users may well have to consider alternative data in the form of SPOT, Landsat TM or Landsat MSS images. Digital elevation models should also be considered a valuable data source.

Effect of differing DEM creation methods on the results from a hydrological model

It is known that digital elevation models (DEMs) can vary in quality depending on their method of creation. Six DEMs derived from digitised contours from the British Ordnance Survey were compared. The DEMs were used to run TOPMODEL for a small catchment in Devon. There were differences between the DEMs in the prediction of the catchment area and the spatial pattern of topographic index values, although these differences were reduced by smoothing the DEMs. Because runoff in the area is dominated by subsurface flow, many of the model predictions were not sensitive to differences between the DEMs. However, predictions of surface runoff differed by over 200%, and caused variations of up to 25% in the prediction of hourly flow values. The predicted spatial pattern of surface runoff was strongly affected by the presence of interpolation artefacts in the DEM, with completely unrealistic predictions in the case of the worst quality DEMs.

Exploratory Spatial Data Analysis

The paper describes SAGE, a software system that can undertake exploratory spatial data analysis (ESDA) held in the ARC/INFO geographical information system. The aims of ESDA are described and a simple data model is defined associating the elements of ‘rough’ and ‘smooth’ with different attribute properties. The distinction is drawn between global and local statistics. SAGEs region building and adjacency matrix modules are described. These allow the user to evaluate the sensitivity of results to the choice of areal partition and measure of interarea adjacency. A range of ESDA techniques are described and examples given. The interaction between the table, map and graph drawing windows in SAGE is illustrated together with the range of data queries that can be implemented based on attribute values and locational criteria. The paper concludes with a brief assessment of the contribution of SAGE to the development of spatial data analysis.

Regionalisation Tools for the Exploratory Spatial Analysis of Health Data

This paper considers issues associated with the construction of regions as part of a programme of exploratory spatial data analysis in the case of what Cressie (1991) refers to as “lattice data”. Lattice data arise where a study area has been partitioned into a set of zones or regions attached to each of which is a vector that describes the set of attributes for that zone. The focus of this paper will be the analysis of health data so the attributes in question may be health related but may also include demographic, socio-economic and environmental attributes.

Scanning thematic maps for input to geographic information systems

Abstract The development of a simple algorithm for deriving raster data from scanned thematic maps is described. Such maps usually contain extra information in addition to the thematic information—identification symbols and cartographic details—which need to be removed before the information can be used in a Geographic Information System. The method described here requires the user to identify those pixel values which represent unwanted information. The program then attempts to replace these with the thematic data values in the neighboring pixels. The method has been implemented as a module for the IDRISI raster GIS which runs on IBM PCs. The FORTRAN source is included, together with an explanation of some of the design decisions taken in writing it. Initial results from the method seem promising, although further work is required to determine the optimum method of scanning to use, and the types of maps for which the method is most suited.