Title of article :
Tropical mangrove species discrimination using hyperspectral data: A laboratory study
Author/Authors :
Chaichoke Vaiphasa، نويسنده , , Suwit Ongsomwang، نويسنده , , Willem F. de Boer and Tanasak Vaiphasa، نويسنده , , Andrew K. Skidmore، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2005
Abstract :
The aim of this study is to test whether spectra of crown canopy leaves of various tropical mangrove species measured under
laboratory conditions contain sufficient spectral information for discriminating mangroves at the species level. This laboratory-level
study is one of the most important prerequisites to the future use of airborne and satellite hyperspectral sensors for mangrove
studies. First, spectral responses of 16 Thai tropical mangrove species (2151 spectral bands between 350 nm and 2500 nm) were
recorded from the leaves, using a spectrometer under laboratory conditions. Next, the mangrove spectra were statistically tested
using one-way ANOVA to see whether they significantly differ at every spectral location. Finally, the spectral separability between
each pair of mangrove species was quantified using the JeffrieseMatusita (JeM) distance measure. It turned out that the 16
mangrove species under study were statistically different at most spectral locations, with a 95% confidence level ( p!0.05). The
total number of spectral bands that had p-values less than 0.05 was 1941, of which 477 bands had a 99% confidence level ( p!0.01).
Moreover, the JeM distance indices calculated for all pairs of the mangrove species illustrated that the mangroves were spectrally
separable except the pairs that comprised the members of Rhizophoraceae. Although the difficulties of discriminating the members
of Rhizophoraceae are expected, the overall result encourages further investigations into the use of on-board hyperspectral sensors
to see whether mangrove species can be separated when the difficulties of the field conditions are taken into account.
Keywords :
data reduction , Mangroves , Spectroscopic techniques , Signal processing , spectral discriminant analysis , Thailand , Chumporn , Sawi Bay
Journal title :
Estuarine, Coastal and Shelf Science
Journal title :
Estuarine, Coastal and Shelf Science