The impact of misregistration on change detection

Abstract

The impact of misregistration on the detection of changes in land cover has been evaluated using spatially degraded Landsat MSS images, focusing on simulated images of the normalized difference vegetation index (NDVI). Single-date images from seven areas were misregistered against themselves, and the statistical properties of the differences were analyzed. In the absence of any actual changes to the land surface, the consequences of misregistration were very marked even for subpixel misregistrations. Pairs of images from different time periods were then misregistered. For four densely covered areas, an error equivalent to greater than 50% of the actual differences in the NDVI, as measured by the semivariance, was induced by a misregistration of only one pixel. To achieve an error of only 10%, registration accuracies of 0.2 pixels or less are required. For three more sparsely vegetated areas with semiarid climates, a registration accuracy of between 0.5 and 1.0 pixel was sufficient to achieve an error of 10% or less. The results indicate that high levels of registration are needed for reliable monitoring of global change.>