Urban growth induces urban spatial expansion in many cities in China. There is a great need for up-to-date information
for effective urban decision-making and sustainable development. Many researches have demonstrated that satellite
images, especial high resolution images, are very suitable for urban growth studies. However, change detection technique
is the key to keep current with the rapid urban growth rate, taking advantage of tremendous amounts of satellite data. In
this paper, a multi-scale object-oriented change detection approach integrating GIS and remote sensing is introduced.
Firstly, a subset of image is cropped based on existing parcel boundaries stored in GIS database, then a multi-scale
watershed transform is carried out to obtain the image objects. The image objects are classified into different land cover
types by supervised classification based on their spectral, geometry and texture attributes. Finally a rule-based system is
set up to judge every parcel one by one whether or not change happened comparing to existing GIS land use types. In
order to verify the application validity of the presented methodology, the rural-urban fringe of Shanghai in China with
the support of QuickBird date and GIS is tested, the result shown that it is effective to detect illegal land use parcel.