Object-based Detailed Vegetation Classification with Airborne High Spatial Resolution Remote Sensing Imagery

@article{Yu2006ObjectbasedDV,
  title={Object-based Detailed Vegetation Classification with Airborne High Spatial Resolution Remote Sensing Imagery},
  author={Qian Yu and Peng Gong and Nicholas E. Clinton and Gregory S. Biging and Maggi Kelly and Dave Schirokauer},
  journal={Photogrammetric Engineering and Remote Sensing},
  year={2006},
  volume={72},
  pages={799-811}
}
  • Qian YuP. Gong D. Schirokauer
  • Published 1 July 2006
  • Environmental Science, Mathematics
  • Photogrammetric Engineering and Remote Sensing
In this paper, we evaluate the capability of the high spatial resolution airborne Digital Airborne Imaging System (DAIS) imagery for detailed vegetation classification at the alliance level with the aid of ancillary topographic data. Image objects as minimum classification units were generated through the Fractal Net Evolution Approach (FNEA) segmentation using eCognition software. For each object, 52 features were calculated including spectral features, textures, topographic features, and… 

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