Hyperspectral Data for Tropical Mangrove Species Discrimination
Chaichoke Vaiphasa
Department of Natural Resources
International Institute for Geo-Information Science and Earth Observation (ITC),
P.O. Box 6, 7500 AA, Enschede, The Netherlands.
Email: chaichoke@hotmail.com,
vaiphasa@itc.nl
Suwit Ongsomwang
Ministry of Natural Resources and Environment (MONRE),
Rama 6 Rd., Bangkok 10400, Thailand.
Email: LHChang@nspo.org.tw
ABSTRACT The aim of this study was to test the performance of hyperspectral data in
discriminating mangroves at the species level. First, spectral responses between 350 nm and
2500 nm of 16 Thai tropical mangrove species were recorded from the leaves, using a field
spectrometer under laboratory conditions. Next, the mangrove spectra were statistically tested to
see whether they significantly differed at every spectral location. Finally, the spectral
separability between each pair of mangrove species was quantified using the J-M distance
measure. The results demonstrated that the mangrove species were spectrally separable, and we
therefore anticipate the use of hyperspectral sensors for mangrove species classification.
1. INTRODUCTION
The limited spectral bands of a traditional sensor such as Landsat TM offer a clear example of
how opportunities to exploit spectral responses linked to the physical-chemical properties of
plants are lost (Curran, 1989, Elvidge, 1987, 1990, Himmelsbach et al., 1988, Kumar et al.,
2001, Williams and Norris, 1987). This problem can be resolved using more delicate methods
such as hyperspectral technology. Additionally, there is already a couple of evidence to show
that using hyperspectral data helps to improve the study of mangroves at a finer level. Demuro
and Chisholm (2003) give a good example of how a hyperspectral sensor (HYPERION) handles
the task of discriminating 8-class mangrove communities in Australia - a task considered
difficult for any multispectral sensors (Green et al., 2000). Moreover, the AVIRIS sensor
performed just as well in mapping the mangrove communities of the Everglades, Florida
(Hirano et al., 2003). So far no conclusion has been reached as to whether or not hyperspectral
information can be used to study mangroves at the species level (i.e. for species discrimination).
Consequently, this study aims to test and quantify the capability of hyperspectral data based on
laboratory mangrove spectra recorded from 16 Thai tropical mangrove species.
