Hyperspectral Data for Tropical Mangrove Species Discrimination
2. METHODS
2.1 Acquisition of hyperspectral data
2.1.1 Mangrove leaf preparation Mangrove leaves of 16 Thai tropical mangrove species
were collected using a line-transect method from mangrove trees (higher than 2.5 m) in the
natural mangrove forest of Ao Sawi (Sawi Bay), Chumporn province, in the south of Thailand
(10º 15’N, 99º 7’E). There were ten transects randomly placed throughout the area so as to
collect tree samples from every mangrove zones (e.g. pioneer, intermediate, and upper zones).
The leaves were picked off the trees just before spectral measurement in order to preserve the
original leaf quality. Specifically, on 6 February 2001 a few major branches of every randomly
sampled tree were cut off and transported to the laboratory, and the following day the leaves
were picked for spectral measurement.
2.1.2 Leaf spectral measurements The freshly picked leaves of each species were randomly
divided into 30 piles of the same size (20 to 30 leaves). For each spectral measurement, each
pile of leaves was spread on top of a black metal plate painted with ultra-flat black paint until
the background metal plate could not be seen. Each measurement was performed under
laboratory conditions (i.e. dark room, 25ºC) in order to avoid ambient light sources unrelated to
the true spectral signal of the leaves. As a result, 30 spectra were measured for each mangrove
species (Table 1).
Table 1 (Left): Thirty
spectra of mangrove
leaves were collected per
mangrove species, using a
spectroradiometer
Each measurement was conducted using a FieldSpec ® Pro FR spectroradiometer (Analytical
Spectral Device, Inc.). This spectroradiometer is equipped with three spectrometers (i.e. VNIR,
SWIR1, and SWIR2), covering 350 nm to 2500 nm, with sampling intervals of 1.4 nm between
350 nm and 1050 nm, and 2 nm between 1000 nm and 2500 nm. The spectral resolution of the
spectrometers was 3 nm for the wavelength interval 350 nm to 1000 nm, and 10 nm for the
wavelength interval 1000 nm to 2500 nm. The sensor, equipped with a field of view of 25°, was
mounted on a tripod and positioned 0.5 m above the leaf plate at the nadir position. A halogen
lamp fixed at the same position was used to illuminate the sample plate. The bi-directional
reflectance distribution function (BRDF) of each sample is corrected by rotation method. The
radiance was converted to reflectance, using a spectralon reference panel for every measurement
as well as the correction of the spectrometer internal current (dark current).
2.2 Experimental setup
2.2.1 Statistical test First of all, we tested whether the mangrove spectra of the 16 species
(Table 1) were statistically different at every spectral band, that is to say, the null hypothesis Ho:
µ1=µ2= … =µ16 versus the alternative hypothesis Ha: µ1 .µ2 .µ16, where µi was the mean
reflectance value of the i th species (i.e. i = 1, 2,…, 16). The test was carried out using one-way
ANOVA at every spectral location between 350 nm and 2500 nm (a total of 2151 spectral bands)
with a 95% confidence limit =0.05).
2.2.2 Spectral separability Although the statistical test demonstrated whether the mangrove
species were significantly different or not at the spectral locations, it could not quantify the
likelihood of each pair of the mangrove species being spectrally separated from one another.
This pair-wise information is necessary for a detailed investigation of species separability.
Therefore, we applied the J-M distance measure to quantify this for each mangrove pair. The
distance measure reported a separability value between 0 and 2 for every mangrove pair. The
pairs that possessed a value close to 2 were highly separable, and vice versa. Details of the
distance measure are given by Richards (1994).
Because the J-M distance measure is a parametric method, it was necessary to reduce the
number of spectral features (bands) prior to the calculation. It was not possible to calculate the J-M
distance using all 2151 bands because of the singularity problem of matrix inversion (i.e. the
number of spectral samples per mangrove species is too small). In this study, we applied a
wrapper feature selection approach (please see John et al., 1994; Kavzoglu and Mather, 2002;
Kohavi and John, 1997; Siedlecki and Sklansky, 1989; Vaiphasa, 2003; Yu et al., 2002) to
reduce the number of spectral features.
In our experiment, we applied the algorithm to select (i) the best 2-band combination, (ii) the
best 3-band combination, (iii) the best 4-band combination, (iv) the best 6-band combination, (v)
the best 8-band combination, and (vi) the best 10-band combination out of the total of 2151
bands. For every selection, the algorithm was initialized with the following parameters:
crossover rate = 50%, mutation rate = 1%, fitness score threshold = 80%. The maximum number
of iterations was 1000.
