Data Fusion

LidarColorByClassThis 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.

This entry was posted in airborne LiDAR, Data, remote sensing, Research, Software and tagged , , , . Bookmark the permalink.

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