Monitoring urban vegetation is one of the major environmental applications in remote sensing today.As the main data sources for urban vegetation high resolution imagery provides a good basis for recognizing and monitoring small scale structure changes. Going far beyond the methodical limits of pixel based and manual interpretation approaches

multi resolution image segmentation and object oriented image analysis approaches are used for extracting information from airborne remote sensing data.This paper presents a snapshot of work to detect vegetation information in Daqing city using this new patented technique. It allows the segmentation of an image into highly homogeneous image objects in any chosen resolution and the generation of a network of image objects. The process does not classify single pixel but rather image object.Not only spectral information but also spatial

physical and contextual characteristics of image objects are used for classification.Classification is conducted by fuzzy logic

and image objects are evaluated using membership function classifiers.Membership functions are used to produce class description

which consists of a set of fuzzy expressions from appropriate sample objects.The result of vegetation information extraction is promising and the precision of classification is higher than other conventional processes.It is obvious that this new image analysis approach offers a satisfying solution to extract information quickly and efficiently.