Neural Nets: Applications in Geography

  • Bruce C. Hewitson
  • Robert G. Crane

Part of the The GeoJournal Library book series (GEJL, volume 29)

Table of contents

  1. Front Matter
    Pages i-xi
  2. Bruce C. Hewitson, Robert G. Crane
    Pages 1-9
  3. Eugene E. Clothiaux, Charles M. Bachmann
    Pages 11-52
  4. Stan Openshaw
    Pages 53-70
  5. Kevin Winter, Bruce C. Hewitson
    Pages 71-77
  6. Bruce C. Hewitson, Robert G. Crane
    Pages 121-143
  7. Back Matter
    Pages 181-196

About this book

Introduction

Neural nets offer a fascinating new strategy for spatial analysis, and their application holds enormous potential for the geographic sciences. However, the number of studies that have utilized these techniques is limited. This lack of interest can be attributed, in part, to lack of exposure, to the use of extensive and often confusing jargon, and to the misapprehension that, without an underlying statistical model, the explanatory power of the neural net is very low. Neural Nets: Applications for Geography attacks all three issues; the text demonstrates a wide variety of neural net applications in geography in a simple manner, with minimal jargon.
The volume presents an introduction to neural nets that describes some of the basic concepts, as well as providing a more mathematical treatise for those wishing further details on neural net architecture. The bulk of the text, however, is devoted to descriptions of neural net applications in such broad-ranging fields as census analysis, predicting the spread of AIDS, describing synoptic controls on mountain snowfall, examining the relationships between atmospheric circulation and tropical rainfall, and the remote sensing of polar cloud and sea ice characteristics.
The text illustrates neural nets employed in modes analogous to multiple regression analysis, cluster analysis, and maximum likelihood classification. Not only are the neural nets shown to be equal or superior to these more conventional methods, particularly where the relationships have a strong nonlinear component, but they are also shown to contain significant explanatory power. Several chapters demonstrate that the nets themselves can be decomposed to illuminate causative linkages between different events in both the physical and human environments.

Keywords

Census cluster analysis networks remote sensing satellite

Editors and affiliations

  • Bruce C. Hewitson
    • 1
  • Robert G. Crane
    • 2
  1. 1.Department of Environmental and Geographical ScienceUniversity of Cape TownSouth Africa
  2. 2.Department of Geography and the Earth System Science CenterPennsylvania State UniversityUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-94-011-1122-5
  • Copyright Information Kluwer Academic Publishers 1994
  • Publisher Name Springer, Dordrecht
  • eBook Packages Springer Book Archive
  • Print ISBN 978-94-010-4490-5
  • Online ISBN 978-94-011-1122-5
  • Series Print ISSN 0924-5499
  • About this book