A neural network-based technique for change detection of linear features and its application to a Mediterranean region

I Feldberg, N. S. Netanyahu, M. Shoshany

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

An artificial neural network (ANN) for change detection from multi-temporal satellite images, which was reported in I. Feldberg (2001), has been further developed and tested, as part of a study of an area of high spatio-temporal heterogeneity along a climatic gradient between humid and and climate regions. Four recognition classes, "positive change", "negative change", "false change", and "no change" were learned by a backpropagation feedforward ANN and then applied to Landsat images that were acquired over the study area in 1992 and 1997. A comparison with existing classification techniques indicates, in many instances, significantly improved performance due to the ANN developed.
Original languageAmerican English
Title of host publicationGeoscience and Remote Sensing Symposium, 2002. IGARSS'02. 2002 IEEE International
PublisherIEEE
StatePublished - 2002

Bibliographical note

Place of conference:Toronto, Canada

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