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 classific...

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Bibliographic Details
Main Authors: Marchisio, G, Pacifici, F, Padwick, C
Format: Conference Proceeding
Language:English
Subjects:
Accuracy
Artificial neural networks
Classification tree analysis
Data mining
land cover classification
machine learning
Materials
multispectral
Predictive models
spectral predictors
Vegetation mapping
WorldView-2
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Summary: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.
ISSN:2153-6996
2153-7003
DOI:10.1109/IGARSS.2010.5649771