A spatial scene is a set of objects along with their spatial and

non-spatial attributions and their mutual spatial relationships. In this study

we propose a spatial scene-matching model considering the object area

attribution

topology

and orientation relationships. We first build a scene semantic description model by combining the "gradual change" model and attributed relationship graph (ARGs). We then construct our scene-matching model that evaluates the scene similarity by the self-proposed similarity measures. This method objectively describes semantics of spatial

especially geographic scenes

and performances well on spatial scene matching. It has a good prospect in intelligent retrieval of spatial data.