A hyperspectral band selector for plant species discrimination

By Chaichoke Vaiphasa, Andrew K. Skidmore, W. F. Boer, Tanasak Vaiphasa. 2007

155 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Ecology, Media Technology

View Paper: https://www.semanticscholar.org/paper/b8eb0e88cab9d23e926c354893a8412443d66f1f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

1. M. Anuar
2. Helmi Zulhaidi Mohd Shafri
3. Idris Abu Seman
4. N. M. Noor

In Media Technology

1. M. Anuar
2. Helmi Zulhaidi Mohd Shafri
3. Idris Abu Seman
4. N. M. Noor

Citations in the corpus

• Spectral discrimination of healthy and Ganoderma-infected oil palms from hyperspectral data (2011, methodology): “…component analysis (PCA) and genetic algorithms (GAs) to identify wavebands that reveal significant differences between different vegetation types or within vegetation types (Osborne et al. 1997, Schmidt and Skidmore 2002, Fung et al. 2003, Zhang et al. 2003, Li et al. 2007, Vaiphasa et al. 2007).”
• Vegetation classification method with biochemical composition estimated from remote sensing data (2011, methodology): “Many band selection methods have been developed to overcome this problem (Kavzoglu and Mather 2002, Ulfarsson et al. 2003, Vaiphasa et al. 2007), but they are always only suitable for specific studies.”