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 language||American English|
|Title of host publication||Geoscience and Remote Sensing Symposium, 2002. IGARSS'02. 2002 IEEE International|
|State||Published - 2002|