The paper studies concept and approach of decomposable Markov network(DMN).Unlike previous studies on DMN

our method directly employs the construct of DMN as the evidence of inference or for problem solving

and enlarges application range of DMN's concept and approach.It analyses DMN's role and importance in spatial data mining

and deeply investigates several score metrics used in constructing DMN between multi-bands remote sensing images

so as to interpret the result of fusion in them

and realizes optimal fusion of bands.Another example of the factual video images with traffic rule violation is also investigated by novel concept of DMN's graininess.Several graininess(nodes) are used to construct DMN between video images for detecting abnormality in them.Hence

the vehicle of traffic peccancy is located and traced.The result of video image simulation shown that our method is feasible and effective.The researches indicate that the DMN may reveal abstract adjacent relations existed in spatial data;and the network itself has capabilities of showing knowledge.