On the relative predictive value of the new spectral bands in the WorldWiew-2 sensor

We apply a comparative data mining framework to the multispectral classification of WorldView-2 (WV2) imagery. Our goal is two-fold. First, we want to identify land covers for which the combination of extended spectral coverage and high spatial resolution provide a distinctive advantage in classification accuracy. Second, we perform predictor analyses to determine which combinations of bands are more effective in resolving individual targets. This experimental approach provides a basis for building a spectral atlas that can offer guidance on the optimal combination of WV2 spectral bands for different application areas.