This Exelis blog provides an excellent overview on the topic of fusing lidar with hyperspectral data. This is not a trivial problem and in fact some are doubtful of the results in general, but for the right application this approach is definitely worth considering.
To start the author refers to a paper by Zhang that explains there are three common levels of data fusion (Zhang, 2010):
- Pixel-level fusion: Combines raw pixel data from multiple source images into a single image.
- Feature-level fusion: Extracts different objects from multiple data sources to yield feature maps for subsequent processing in change detection, image segmentation, etc.
- Decision-level fusion: Fuses the results of multiple algorithms to yield a final decision, using statistical or fuzzy logic methods.
The example provided explains how the technique is used to:
- Create more accurate classification images of urban features
- Identify individual tree species
- Estimate forest biomass
Worth a read.
