|
The Boom en Beeld project aims at developing a methodology for change detection of tree objects in urban areas using imagery. This paper focuses on one aspect of this methodology, the prediction of the size of tree objects at a given time in the future. The most important factor is the prediction of the tree growth which estimates the future size of the tree. In the urban area, tree growth is strongly influenced by man made objects and activities. The developed tree growth model uses species specific tree characteristics like shape (column, round or ellipse), size classification (big, regular, small), growth speed (slow, regular or fast growing tree), life phase (young, mature, old) in combination with influences caused by the stand characteristics of the nearby surface coverings (paved, open or vegetated). The UrbTree model is a spatial driven growth model and can model differences in tree growth caused by the nature of the surface covering of the neighbouring area of the location of the trees by using spatial analyses techniques. The quality of the available geodata is an important factor in the modelling process, especially the amount of sealing imposed by the different kinds of paving must be taken into account. The amount of tree growth that can be calculated using the model over a five year period is still close to the bandwidth with which the actual tree growth can be detected on the separate images from two different time steps
|
