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Neurocomputation in Remote Sensing Data Analysis

Proceedings of Concerted Action COMPARES (Connectionist Methods for Pre-Processing and Analysis of Remote Sensing Data)

  • Conference proceedings
  • © 1997

Overview

Editors:
  1. Ioannis Kanellopoulos

    1. Environmental Mapping and Modelling Unit, Joint Research Centre, Commission of the European Communities Space Applications Institute, Ispra (Varese), Italy

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  2. Graeme G. Wilkinson

    1. School of Computer Science and Electronic Systems, Kingston University, Kingston Upon Thames, UK

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  3. Fabio Roli

    1. Electrical and Electronic Engineering Department, University of Cagliari, Cagliari, Italy

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  4. James Austin

    1. Department of Computer Science Advanced Computer Architecture Group, University of York, York, UK

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  • Application of neural networks in remote sensing - Combination of advanced computing techniques and operational remote sensing needs - Presentation of state of the art techniques used across Europe for remote sensing data analysis, with a considerable range of applications - Comprehensive assessment of the potential role of neural computation in the processing of data from earth observation satellites.

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Table of contents (30 papers)

  1. Front Matter

    Pages i-ix
    Download chapter PDF

  2. Introduction

    • Ioannis Kanellopoulos, Graeme G. Wilkinson, Fabio Roli, James Austin
    Pages 1-2

  3. Open Questions in Neurocomputing for Earth Observation

    • Graeme G. Wilkinson
    Pages 3-13

  4. A Comparison of the Characterisation of Agricultural Land Using Singular Value Decomposition and Neural Networks

    • S. Danaher, G. Herries, T. Selige, M. Mac Sรบirtรกn
    Pages 14-27

  5. Land Cover Mapping from Remotely Sensed Data with a Neural Network: Accommodating Fuzziness

    • Giles M. Foody
    Pages 28-37

  6. Geological Mapping Using Multi-Sensor Data: A Comparison of Methods

    • Paul M. Mather, Brandt Tso, Magaly Koch
    Pages 38-46

  7. Application of Neural Networks and Order Statistics Filters to Speckle Noise Reduction in Remote Sensing Imaging

    • E. Kofidis, S. Theodoridis, C. Kotropoulos, I. Pitas
    Pages 47-56

  8. Neural Nets and Multichannel Image Processing Applications

    • Vassilis Gaganis, Michael Zervakis, Manolis Christodoulou
    Pages 57-70

  9. Neural Networks for Classification of Ice Type Concentration from ERS-1 SAR Images

    • Jan Depenau
    Pages 71-78

  10. A Neural Network Approach to Spectral Mixture Analysis

    • Theo E. Schouten, Maurice S. klein Gebbinck
    Pages 79-85

  11. Comparison Between Systems of Image Interpretation

    • Jean-Pierre Cocquerez, Sylvie Philipp, Philippe Gaussier
    Pages 86-96

  12. Feature Extraction for Neural Network Classifiers

    • Jon A. Benediktsson, Johannes R. Sveinsson
    Pages 97-104

  13. Spectral Pattern Recognition by a Two-Layer Perceptron: Effects of Training Set Size

    • Petra Staufer, Manfred M. Fischer
    Pages 105-116

  14. Comparison and Combination of Statistical and Neural Network Algorithms for Remote-Sensing Image Classification

    • Fabio Roli, Giorgio Giacinto, Gianni Vernazza
    Pages 117-124

  15. Integrating the Alisa Classifier with Knowledge-Based Methods for Cadastral-Map Interpretation

    • Eleni Stroulia, Rudolf Kober
    Pages 125-133

  16. A Hybrid Method for Preprocessing and Classification of SPOT Images

    • Shan Yu, Konrad Weigl
    Pages 134-141

  17. Testing some Connectionist Approaches for Thematic Mapping of Rural Areas

    • Leopoldo Cortez, Fernando Durรฃo, Vitorino Ramos
    Pages 142-150

  18. Using Artificial Recurrent Neural Nets to Identify Spectral and Spatial Patterns for Satellite Imagery Classification of Urban Areas

    • Sara Silva, Mario Caetano
    Pages 151-159

  19. Dynamic Segmentation of Satellite Images Using Pulsed Coupled Neural Networks

    • X. Clastres, M. Samuelides, G. L. Tarr
    Pages 160-167

  20. Non-Linear Diffusion as a Neuron-Like Paradigm for Low-Level Vision

    • M. Proesmans, L. J. Van Gool, P. Vanroose
    Pages 168-175
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Keywords

About this book

Since 1994 the European Commission has been supporting activities under the Environment and Climate programme of research and technological deยญ velopment, with the aim of developing cost-effective applications of satellite Earth observation (EO) for both environmental monitoring and research. This action has included support to methodological research, aimed at the development and evaluation of new techniques forming part ofthe chain of processing needed to transform data into useful information. Wherever appropriate, the Commission has emphasised the coordination of ongoing research funded at the national level, through the mechanism of concerted actions. Concerted actions are flexible and efficient means to marshal efforts at the European level for a certain period. They are proposed by groups of researchers active in a given field who have identified the added value to be gained by European cooperation, whilst continuing to pursue their own individual projects. In view of the rapid developments in the field of neural network over the last 10 years, together with the growing interest ofthe Earth observation community in this approach as a tool for data interpretation, the Commission decided in 1995 to support the concerted action COMPARES, following a proposal from a group of acknowledged European experts.

Editors and Affiliations

  • Environmental Mapping and Modelling Unit, Joint Research Centre, Commission of the European Communities Space Applications Institute, Ispra (Varese), Italy

    Ioannis Kanellopoulos

  • School of Computer Science and Electronic Systems, Kingston University, Kingston Upon Thames, UK

    Graeme G. Wilkinson

  • Electrical and Electronic Engineering Department, University of Cagliari, Cagliari, Italy

    Fabio Roli

  • Department of Computer Science Advanced Computer Architecture Group, University of York, York, UK

    James Austin

Bibliographic Information

  • Book Title: Neurocomputation in Remote Sensing Data Analysis

  • Book Subtitle: Proceedings of Concerted Action COMPARES (Connectionist Methods for Pre-Processing and Analysis of Remote Sensing Data)

  • Editors: Ioannis Kanellopoulos, Graeme G. Wilkinson, Fabio Roli, James Austin

  • DOI: https://doi.org/10.1007/978-3-642-59041-2

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer-Verlag Berlin ยท Heidelberg 1997

  • Hardcover ISBN: 978-3-540-63316-7Published: 18 September 1997

  • Softcover ISBN: 978-3-642-63828-2Published: 22 December 2012

  • eBook ISBN: 978-3-642-59041-2Published: 06 December 2012

  • Edition Number: 1

  • Number of Pages: IX, 284

  • Topics: Artificial Intelligence, Economic Geology, Regional/Spatial Science, Pattern Recognition, Geography, general, Earth Sciences, general

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