Logo - springer
Slogan - springer

Earth Sciences & Geography - Geography | Neural Nets: Applications in Geography

Neural Nets: Applications in Geography

Series: GeoJournal Library, Vol. 29

Hewitson, B., Crane, R.G. (Eds.)

Softcover reprint of the original 1st ed. 1994, XI, 196 p.

Available Formats:

Springer eBooks may be purchased by end-customers only and are sold without copy protection (DRM free). Instead, all eBooks include personalized watermarks. This means you can read the Springer eBooks across numerous devices such as Laptops, eReaders, and tablets.

You can pay for Springer eBooks with Visa, Mastercard, American Express or Paypal.

After the purchase you can directly download the eBook file or read it online in our Springer eBook Reader. Furthermore your eBook will be stored in your MySpringer account. So you can always re-download your eBooks.


(net) price for USA

ISBN 978-94-011-1122-5

digitally watermarked, no DRM

Included Format: PDF

download immediately after purchase

learn more about Springer eBooks

add to marked items


Softcover (also known as softback) version.

You can pay for Springer Books with Visa, Mastercard, American Express or Paypal.

Standard shipping is free of charge for individual customers.


(net) price for USA

ISBN 978-94-010-4490-5

free shipping for individuals worldwide

usually dispatched within 3 to 5 business days

add to marked items

  • About this book

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.

Content Level » Research

Keywords » Census - cluster analysis - networks - remote sensing - satellite

Related subjects » Complexity - Geography - Social Sciences

Table of contents 

Preface. 1. Looks and Uses; B.C. Hewitson, R.G. Crane. 2. Neural Networks and Their Applications; E.E. Clothiaux, C.M. Bachmann. 3. Neuroclassification of Spatial Data; S. Openshaw. 4. Self Organizing Maps -- Application to Census Data; K. Winter, B.C. Hewitson. 5. Predicting Snowfall from Synoptic Circulation: a Comparison of Linear Regression and Neural Network Methodologies; D.L. McGinnis. 6. Neural Computing and the AIDS Pandemic: the Case of Ohio; P.G. Gould. 7. Precipitation Controls in Southern Mexico; B.C. Hewitson, R.G. Crane. 8. Classification of Arctic Cloud and Sea Ice Features in Multi-Spectral Satellite Data; J.R. Key. Appendix I: Neural Network Resources. Appendix II: Fortran 77 Listing for Kohonen Self Organizing Map.

Popular Content within this publication 



Read this Book on Springerlink

Services for this book

New Book Alert

Get alerted on new Springer publications in the subject area of Geography (general).