Peter A. Burrough

Principles of geographical information systems for land resources assessment.

Geographical information systems Data structures for thematic maps Digital elevation models Data input, verification, storage, and output Methods of data analysis and spatial modelling Data quality, errors, and natural variation: sources of error Errors arising through processing The nature of boundaries Classification methods Methods of spatial interpolation Choosing a geographical information system Appendices Index.

Geographic Objects with Indeterminate Boundaries

Current geographical information systems GIS deal almost exclusively with well-defined, static geographical objects ranging from physical landscapes to towns and transport systems. Such objects, exactly located in space, can easily be handled by modern GIS, yet form only a small proportion of all the possible geographical objects.; This book challenges the assumption that the world is compsed of exactly defined and bounded geographic objects such as land parcels, rivers and countries. ignoring the essential complexity of the world, current GIS do not adequately address problems as diverse as the resolution of crime between national boundaries, or the interpretation of views of people from different cultures. This work, bringing together a range of specialists from fields such as linguistics, computer science, land surveying, cartography and soil science, examines current research into the challenges of dealing with geographical phenomena that cannot easily be forced into one of the two current standard data models.

High-resolution landform classification using fuzzy k -means

Previous attempts to devise automated methods of landscape classification have been frustrated by computational issues related to the size of the data set and the fact that most automated classification methods create discrete classes while ‘natural’ interpreted landscape units often have overlapping property sets. Methods of fuzzy k-means have been used by other workers to overcome the problem of class overlap but their usefulness maybe reduced when data sets are large and when the data include artefacts introduced by the derivation of landform attributes from gridded digital elevation models.This paper presents ways to overcome these limitations using spatial sampling methods, statistical modelling of the derived stream topology, and fuzzy k-means using the Distance metric. Using data from Alberta, Canada, and the French pre-Alps it is shown how these methods may easily create meaningful, spatially coherent land form classes from high resolution gridded DEMs.

Integrating dynamic environmental models in GIS: The development of a Dynamic Modelling language

An integrated, executable mathematical modelling language for environmental and ecological applications has been developed to create and run Dynamic Models in a GIS. The modelling language is embedded in the GIS, providing the ability to model complex space-time systems free from the technical burdens of database management and algorithm optimization. The spatial modelling language uses a structured script, which is illustrated here by an example of a model of plant dispersion.

Continuous classification in soil survey: spatial correlation, confusion and boundaries

This article traces the development of conceptual paradigms of soil classification and mapping from the pre-1960s model of crisp classes in attribute space linked to crisply delineated mapping units in geographical space, to modern approaches using fuzzy classification and geostatistical interpolation for simultaneously handling continuous variation in both attributes and location. Continuous classification yields a separate map of class membership values for every class the dominance of any class at each location can be expressed by a confusion index, CI. If spatial correlation is strong, zones of high CI are concentrated in narrow geographical transition zones between locally dominant classes: these zones can be refined to delineate automatically classspecific boundaries. If spatial correlation in membership values is weak then broad zones of large values of CI occur all over the map. Simulation modelling and two case studies demonstrate that contiguity in geographical space is more important for successful mapping than attribute class compactness. The studies show that soil information systems must take the spatial aspects of soil variation into account; further improvements in identifying and mapping significant soil groupings should be possible using numerical models of soil processes together with the methods presented here.

Using fractal dimensions for characterizing tortuosity of animal trails

ABSTRACT. The tortuosity of mite trails was characterized by their fractal dimension, which is the non‐Euclidean dimension varying between 1 (completely straight) and 2 (so tortuous that the complete two‐dimensional space is used). This index was shown to be a good, discriminative index for mite trails, which is a completely new use of the fractal dimension. The value of this index is compared with other tortuosity indices.

Concepts and paradigms in spatial information: are current geographical information systems truly generic?

Abstract This article considers the philosophical and experiential foundations of human perception of geographical phenomena and their abstraction and coding in geographical information systems. It examines the role of culture and language in describing geographical reality and explores the ways geographical data models reflect how people view the world. Differences between those who see the world as made of exact entities and smooth continuous surfaces, and those who prefer to view reality as dynamic and complex are explored in terms of five aspects of spatial data, namely (i) objects versus fields, (ii) single scale versus multiple scales, (iii) Boolean versus multi-valued logic, (iv) static versus dynamic descriptions, and (v) determinism versus uncertainty. These five aspects are further divided into nine factors of geographical data which indicate the differences in the way people perceive spatial data. Eight typical GIS applications and four generic methods of handling spatial data are examined in t...

Development of intelligent geographical information systems

Abstract The analysis of geographical information is compared with other production processes in which a user can only accept an end-product if it meets certain quality requirements. Whereas users are responsible for defining the levels of quality they need to use the results of the analyses of geographical information systems in their work, database managers, experts and modellers could greatly assist users to achieve the quality of results they seek by formalizing information on: (1) data collection, level of resolution and quality; (2) the use of the basic analytical functions of the geographical information system; and (3) the data requirements, sensitivity and error propagation in models. These meta-data could be incorporated in a knowledge base alongside the geographical information system where, together with procedures for on-line error propagation, a user could be advised on the best way to achieve a desired aim. If the analysis showed that the original constellation of data, methods and models c...

Error propagation in cartographic modelling using Boolean logic and continuous classification

Abstract When data on environmental attributes such as those of soil or groundwater are manipulated by logical cartographic modelling, the results are usually assumed to be exact. However, in reality the results will be in error because the values of input attributes cannot be determined exactly. This paper analyses how errors in such values propagate through Boolean and continuous modelling, involving the intersection of several maps. The error analysis is carried out using Monte Carlo methods on data interpolated by block kriging to a regular grid which yields predictions and prediction error standard deviations of attribute values for each pixel. The theory is illustrated by a case study concerning the selection of areas of medium textured, non-saline soil at an experimental farm in Alberta, Canada. The results suggest that Boolean methods of sieve mapping are much more prone to error propagation than the more robust continuous equivalents. More study of the effects of errors and of the choice of attri...

Mapping alpine vegetation using vegetation observations and topographic attributes

Local planning in mountain areas requires spatial information on site factors such as vegetation that is commonly lacking in rugged terrain. This study demonstrates a procedure for the efficient acquisition of a vegetation map using topographic attributes and nominal vegetation data sampled in the field. Topographic attributes were derived from a digital elevation model (DEM) and nominal vegetation data were reduced to normalised scores by detrended correspondence analysis (DCA). The procedure for mapping vegetation types addressed the relations between DCA scores and topographic attributes, spatial correlation of DCA scores and classification of predicted DCA scores based on a cluster analysis of DCA scores at observation locations. The modelled vegetation classes corresponded with the impression obtained in the field. We also showed that the final result is rather sensitive to which samples are included in the analysis.