The use of an artificial neural network for detecting significant changes between remotely sensed images over regions of high variability

An Artificial Neural Network (ANN) has been developed for the task of change detection in an area of high spatio-temporal heterogeneity along a climatic gradient between humid and arid climate regions. Four recognition classes, "positive change", "negative change", "false change", and "no change" have been learned by a backpropagation 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.