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

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3 Author(s)
I. Feldberg ; Dept. of Math. & Comput. Sci., Bar-Ilan Univ., Ramat-Gan, Israel ; N. S. Netanyahu ; M. Shoshany

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.

Published in:

Geoscience and Remote Sensing Symposium, 2002. IGARSS '02. 2002 IEEE International  (Volume:2 )

Date of Conference:

24-28 June 2002