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Last Post 02 Dec 2012 08:17 PM by  anon
classifying multiple datasets
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anon



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02 Dec 2012 08:17 PM
    I need some help in classifying multiple datasets in a single classification. I want to use Worldview 2, 4-band imagery (2 m res on MSS bands) as well as geophysical data (radiometric data at 50m res) as well as topographic data such as aspect slope and elevation (derived from a DEM). I can create classification results for each layer separately; but how do I integrate all the information into a single analysis? Presumably I need to resample all the data to the same resolution (2 m) as a starting point, but what do I do next? And how do I assign a weight each layer in the classification?

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    03 Dec 2012 01:29 PM
    You might want to consider using the Decision Tree classifier. This would allow you to set relevant parameters for each input and generate a binary result for your area of interest.

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    03 Dec 2012 09:07 PM
    Thank you I will do that. Once I have had a go I will get back to you with any issues. I gather this process progressively applies each rule and the binary output from one step becomes the input for the next. Are there any tips for new players with this? Such as start with the simple layers and then leave the rich data until last (etc)...? Thanks again
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