In this paper, in order to evaluate the capability of several data, acquired by different sensors, some object-oriented classification tests have been carried out. In particular, the results obtained with two RGB ortophotos, acquired with traditional methodology, have been compared with the ones obtained with two QuickBird images and with the ones obtained by ADS40 pushbroom sensor. The object classification is based on two next steps: The classification to objects is based on two next steps: the decomposition of the whole image in dimension objects bigger than the pixel, procedure called segmentation, and the next classification with Fuzzy logic. This approach provides more reliable results with respect to the classification based on the pixels as it associates homogeneous objects on the basis of the information contained both in the objects themselves and their mutual relations. At last, the results obtained in the three cases have been compared through statistical methods necessary to evaluate the quality of the produced classifications. The comparison has been carried out through the comparing of the confusion matrixes produced on the basis of some samples extracted from the origin images. The used methodology is very useful for the monitoring and identification of landscape changes; in particular, in order to individuate the changes due to the anthropic pressure, a orthophoto, produced in 1979 by traditional techniques and two QuickBird images, acquired in 2002 and 2006 respectively and relative to the very naturalistic area have been elaborated.
|Numero di pagine||5|
|Stato di pubblicazione||Published - 2008|