Calculating Change Curves for Multitemporal Satellite Imagery: Mount St. Helens 1980–1995

We developed and tested a method for analyzing multitemporal satellite imagery using change curves. The method is flexible and allows an analyst to extract specific change parameters from the curves depending on the research question of interest. Eight Landsat TM images of the Mount St. Helens, Washington, blast zone from 1984 to 1995 were geometrically and radiometrically corrected. They were then transformed to estimates of green vegetation cover. Unsupervised clustering was performed on the set of eight transformed images and polynomial curves were fit to the cluster means. From these fitted curves, parameters of interest were extracted and returned to GIS layers, including number of years to reach 10% cover, the greatest rate of cover increase during the study period, and time-integrated cover. Statistical analysis indicated that the curves did a good job of representing the change trajectories of unclustered pixels. We demonstrated the use of change curve analysis by analyzing the importance in the revegetation of Mount St. Helens of the different types of disturbance resulting from the volcanic eruption. The change curve analysis is useful in a variety of applications where the data are continuous, more than two dates of data are available, and the underlying question of interest relates to trends in the data.