Apply pattern recognition output to another dataset

I have a DEM dataset that I have worked up into values such as slope, aspect, curvature, &c. At some points I have feature observations of the ground cover (bare, grass, trees). I now have a training dataset with the elevation, slope, aspect, curvature, &c. and a binary output with each ground cover as a separate column: [0,0,1;1,0,0;0,0,1;0,1,0] Means {'trees';'bare';'trees';'grass'}. I have run the pattern recognition tool from the neural network toolbox and the confusion matrix looks promising (>80% correct). How do I now apply the model developed to the whole DEM dataset?

[KSSV]

You need to export the net from the model you run......this will be a function with inputs..which you have used as training and gives output as your target...you shall use this exported net or function.

[Tristan Graham]

Thanks KSSV. Once I had my other data in the right format it worked very smoothly. Is there a way to clearly see how it is manipulating the input data? I would like to do some tests using different input combinations / spatial selections &c. and see how it affects the output.

[KSSV]

If your input data changes i.e if you change the combination.....you should train again and get new net.