NDLI: Application of supervised neural network approaches to remotely sensed optical imagery

Content Provider	IEEE Xplore Digital Library
Author	Herries, G.M. Selige, T.
Copyright Year	1998
Description	Author affiliation: Inst. of Biomeath. & Biometrics, GSF-Nat. Res. Res. Centre for Environ. & Health, Neuherberg, Germany (Herries, G.M.)
Abstract	This paper presents a new method based on the application of modular neural networks to agricultural land use classification and compares the advantages and disadvantages over a single complex neural network approach. Neural networks (NN) have been found to have good generalisation properties and their use is becoming increasingly prevalent in the field of remote sensing. However, there are a number of remote sensing problems where neural networks do not necessarily provide an optimum solution, these include mixed pixel analysis, subclass characterisation and parameter extraction for use in biophysical models. Typically the application of NN techniques to remote sensing involves using one NN to classify a large number of land-cover classes. The authors have previously found this approach to be inefficient and inaccurate, a modular approach is therefore implemented which is more flexible. This paper applies these techniques to optical imagery. The area used for this work is a research farm in Bavaria, Germany, which comprises of a highly dynamic terrain with small field units. High resolution land-use maps and yield data have been produced for the research farm, using GPS equipment attached to crop harvesters. These maps enable accurate selection of test classes and are used to validate the results produced by the various techniques.
Starting Page	403
Ending Page	405
File Size	278595
Page Count	3
File Format	PDF
ISBN	0780344030
DOI	10.1109/IGARSS.1998.702919
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1998-07-06
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neural networks Optical computing Optical fiber networks Optical sensors Remote sensing Spatial resolution Satellites Biomedical optical imaging Optical network units Hyperspectral sensors
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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