The University of Southampton
University of Southampton Institutional Repository

Super-resolution land cover mapping from remotely-sensed imagery using a Hopfield neural network

Tatem, A.J., Lewis, H.G., Atkinson, P.M. and Nixon, M.S. (2002) Super-resolution land cover mapping from remotely-sensed imagery using a Hopfield neural network In, Foody, Giles M. and Atkinson, Peter M. (eds.) Uncertainty in Remote Sensing and GIS. Chichester, UK, John Wiley & Sons pp. 77-98.

Record type: Book Section


Remote sensing and geographical information science (GIS) have advanced considerably in recent years. However, the potential of remote sensing and GIS within the environmental sciences is limited by uncertainty, especially in connection with the data sets and methods used. In many studies, the issue of uncertainty has been incompletely addressed. The situation has arisen in part from a lack of appreciation of uncertainty and the problems it can cause as well as of the techniques that may be used to accommodate it. This book provides general overviews on uncertainty in remote sensing and GIS that illustrate the range of uncertainties that may occur, in addition to describing the means of measuring uncertainty and the impacts of uncertainty on analyses and interpretations made. Uncertainty in Remote Sensing and GIS provides readers with comprehensive coverage of this largely undocumented subject: * Relevant to a broad variety of disciplines including geography, environmental science, electrical engineering and statistics * Covers range of material from base overviews to specific applications * Focuses on issues connected with uncertainty at various points along typical data analysis chains used in remote sensing and GIS Written by an international team of researchers drawn from a variety of disciplines, Uncertainty in Remote Sensing and GIS provides focussed discussions on topics of considerable importance to a broad research and user community. The book is invaluable reading for researchers, advanced students and practitioners who want to understand the nature of uncertainty in remote sensing and GIS, its limitations and methods of accommodating it.
Table of Contents:
List of Contributors. Foreword.
Uncertainty in Remote Sensing and GIS: Fundamentals (P. M. Atkinson and G. M. Foody).
Uncertainty in Remote Sensing (C. E. Woodcock).
Toward a Comprehensive View of Uncertainty in Remote Sensing Analysis (J. L. Dungan).
On the Ambiguity Induced by a Remote Sensor's PSF (J. F. Manslow and M. S. Nixon) .
Pixel Unmixing at the Sub-pixel Scale Based on Land Cover Class Probabilities: Application to Urban Areas (Q. Zhan, M. Molenaar and A. Lucieer).
Super-resolution Land Cover Mapping from Remotely-Sensed Imagery using a Hopfield Neural Network (A. J. Tatem, H. G. Lewis, P. M. Atkinson and M. S. Nixon).
Uncertainty in Land Cover Mapping from Remotely Sensed Data using Textural Algorithms and Artificial Neural Networks (A. M. Jakomulska and J. P. Radomski).
Remote Monitoring of the Impact of ENSO-related Drought on Sabah Rainforest using NOAA AVHRR Middle Infrared Reflectance: Exploring Emissivity Uncertainty (D. S. Boyd, P. C. Phipps, W. J. Duane and G. M. Foody).
Land Cover Map 2000 and Meta-data at the Land Parcel Level (G. M. Smith and R. M. F uller).
Analysing Uncertainty Propagation in GIS: Why is it not that Simple? (G. B.M. Heuvelink).
Managing uncertainty in a Geospatial Model of Biodiversity (A. J. Warren, M. J. Collins, E. A. Johnson and P. F. Ehlers).
The Effects of Uncertainty in Deposition Data on Predicting Exceedances of Acidity Critical Loads for Sensitive UK Ecosystems (E. Heywood, J. R. Hall and R. A. Wadsworth).
Vertical and Horizontal Spatial Variation of Geostatistical Prediction (A. Wameling).
Geostatistical Prediction and Simulation of the Lateral and Vertical Extent of Soil Horizons (B. Warr, I. O. A. Odeh and M. A. Oliver).
Increasing the Accuracy of Predictions of Monthly Precipitation in Great Britain using Kriging with an External Drift (C. D. Lloyd).
Conditional Simulation Applied to Uncertainty Assessment in DTMs (J. Sénégas, M. Schmitt and P. Nonin).
Current Status of Uncertainty Issues in Remote Sensing and GIS (G. M. Foody and P. M. Atkinson).

Full text not available from this repository.

More information

Published date: December 2002


Local EPrints ID: 22560
ISBN: 0470844086
PURE UUID: e9372130-055e-4870-88ea-600b7e804037

Catalogue record

Date deposited: 26 Apr 2006
Last modified: 17 Jul 2017 16:21

Export record


Author: A.J. Tatem
Author: H.G. Lewis
Author: P.M. Atkinson
Author: M.S. Nixon
Editor: Giles M. Foody
Editor: Peter M. Atkinson

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton:

ePrints Soton supports OAI 2.0 with a base URL of

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.