Using a Genetic Algorithm as an Optimal Band Selector in the Mid and Thermal Infrared (2.5–14 μm) to Discriminate Vegetation Species

@inproceedings{Ullah2012UsingAG,
  title={Using a Genetic Algorithm as an Optimal Band Selector in the Mid and Thermal Infrared (2.5–14 μm) to Discriminate Vegetation Species},
  author={Saleem Ullah and Thomas A. Groen and Martin Schlerf and Andrew K. Skidmore and Willem Nieuwenhuis and Chaichoke Vaiphasa},
  booktitle={Sensors},
  year={2012}
}
Genetic variation between various plant species determines differences in their physio-chemical makeup and ultimately in their hyperspectral emissivity signatures. The hyperspectral emissivity signatures, on the one hand, account for the subtle physio-chemical changes in the vegetation, but on the other hand, highlight the problem of high dimensionality. The aim of this paper is to investigate the performance of genetic algorithms coupled with the spectral angle mapper (SAM) to identify a… CONTINUE READING

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References

Publications referenced by this paper.
Showing 1-10 of 47 references

Identifying plant species using mid-wave infrared (2.5–6.0 μm) and thermal infrared (8–140 μm) emissivity spectra

  • S. Ullah, M. Schlerf, A. K. Skidmore, C. Hecker
  • Remote Sens. Environ
  • 2012
Highly Influential
4 Excerpts

A hyperspectral band selector for plant species discrimination

  • C. Vaiphasa, A. K. Skidmore, W. F. de Boer, T. Vaiphasa
  • ISPRS J. Photogram. Remote Sens. 2007,
  • 2007
Highly Influential
4 Excerpts

Spectral reflectance and emissivity features of broad leaf plants: Prospects for remote sensing in the thermal infrared (8.0–14.0 μm)

  • B. Ribeiro da Luz, J. K. Crowley
  • Remote Sens. Environ
  • 2007
Highly Influential
5 Excerpts

Modeling directional-hemispherical reflectance and transmittance of fresh and dry leaves from 0.4 μm to 5.7 μm with the PROSPECT-VISIR model

  • F. Gerber, R. Marion, A. Olioso, S. Jacquemoud, B. R. da Luz, S. Fabre
  • Remote Sens. Environ
  • 2011
2 Excerpts

Classification of hyperspectral remote sensing image based on genetic algorithm and SVM. In Remote Sensing and Modeling of Ecosystems for Sustainability

  • M. D. Zhou, J. O. Shu, Z. G. Chen
  • Spie-Int Soc Optical Engineering:
  • 2010
1 Excerpt

Identification of plant species by using high spatial and spectral resolution thermal infrared (8.0–13.5 μm) imagery

  • B. Ribeiro da Luz, J. K. Crowley
  • Remote Sens. Environ
  • 2010
3 Excerpts

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