Lancaster EPrints

Introduction : neural networks in remote sensing

Atkinson, Peter M. and Tatnall, A. R. L. (1997) Introduction : neural networks in remote sensing. International Journal of Remote Sensing, 18 (4). pp. 699-709. ISSN 0143-1161

Full text not available from this repository.

Abstract

Over the past decade there have been considerable increases in both the quantity of remotely sensed data available and the use of neural networks. These increases have largely taken place in parallel, and it is only recently that several researchers have begun to apply neural networks to remotely sensed data. This paper introduces this special issue which is concerned specifically with the use of neural networks in remote sensing. The feed-forward back-propagation multi-layer perceptron (MLP) is the type of neural network most commonly encountered in remote sensing and is used in many of the papers in this special issue. The basic structure of the MLP algorithm is described in some detail while some other types of neural network are mentioned. The most common applications of neural networks in remote sensing are considered, particularly those concerned with the classification of land and clouds, and recent developments in these areas are described. Finally, the application of neural networks to multi-source data and fuzzy classification are considered.

Item Type: Article
Journal or Publication Title: International Journal of Remote Sensing
Additional Information: M1 - 4
Subjects:
Departments: Faculty of Science and Technology
ID Code: 77195
Deposited By: ep_importer_pure
Deposited On: 16 Dec 2015 14:48
Refereed?: Yes
Published?: Published
Last Modified: 19 Sep 2017 04:45
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/77195

Actions (login required)

View Item