Tree crown change detection using an object fuzzy based approach

We develop a change detection model of tree crowns in urban areas addressing the gradual transition of vegetation in space and the fuzziness of tree crowns in remote sensing images. In the model, crown memberships are estimated for two images using soft classifiers. Next, Gaussian surface fitting is applied on the crown membership images to obtain tree crown objects parameters. Tree crowns are then modeled as both: elliptical two dimensional objects and as fuzzy regions. Bi-temporal changes are established by assessing differences in overlap of the modeled objects. The change model was successfully tested in a residential area of The Netherlands using a Quick- Bird and an aerial image of 2006 and 2009 respectively.