The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008 
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Park, Southern Taiwan. The annual mean temperature at the 
study area was 22.9°C and annual rainfall was 2,592.4 mm 
during 1997-2005. In Nanjenshan Nature Reserve, forest 
vegetation distribution is influenced by three major terrains; 
windward, valley and leeward (Hsieh and Hsieh, 1990). In this 
area the winter precipitation and the intensity of northeast 
winds were found to correlate with the differentiation of forest 
types. Those in the northeast district are evergreen since the 
wind is rather moist. The thorny scrubs and deciduous scrubs 
appear in the southwest district due to severe dry winds. The 
high species diversity of Renting National Park is largely 
attributed to the heterogeneous environment (Su and Su, 1988). 
2.2 Plant Materials 
Measurement of leaf spectral reflectance was obtained by 
randomly harvesting leaves from 4 species from the three types 
of terrain. From each terrain type, 1 sampling site from the 
leeward area and 2 sampling sites from the windward and 
valley areas, respectively, were selected. Fifty sample leaves 
taken from the top of the canopies of each species and was 
carried out in late April of 2005. Leaf samples were stored in 
plastic bags and kept cool for further analysis. 
2.3 Measurement of Leaf Chlorophyll Content and 
Spectral Reflectance 
In this research, the biochemical analysis of chlorophyll 
followed the method of Yang et al. (1998). Leaf spectra were 
obtained from all the sampling leaves of 4 species which are in 
same ages and same size of the same tree species. Leaf 
specimens were collected from 3 different terrains pots per 
treatment randomly. We obtained a sample size Daphniphyllum 
glaucescens of n=35. This was Michelia formosana samples 
short of an expected n=34, Illicium dunnianum that is n=32 and 
Machilus kusanoi n=26 for the different species and terrains, 
respectively. Leaf spectral measurement was conducted using a 
GER1500 (Spectra Vista Corporation, NY, USA). 
Measurements were taken between 09:30 AM and 14:30 PM. 
Conditions varied from cloud-free to overcast skies but care 
was taken to avoid measurement when clouds were passing 
overhead or darkened. 
where the wavelengths for NDVI and SR were 705 and 750 nm, 
respectively, and are based on the chlorophyll index developed 
by Gitelson and Merzlyak (1994). R 70 5 and R 750 are the leaf 
sample spectral reflectance from the GER1500. Based on the 
results of Sims and Gamon (2002), they modified these two 
indices which tend to increase reflectance across the whole 
visible spectrum of a wide range of species. They chose R445 
as a measure of surface reflectance and indicated that R is a 
445 
good reference for all but the lowest chlorophyll content leaves. 
The modified indices of NDVI and SR are as follows (Eqs. 3 
and 4): 
mMX,. =— 
705 R 750 +R 705 -2R U5 
(3) 
^•750 ^445 
D _ D 
iV 705 - n ’445 
(4) 
The derivative analysis of spectra reflectance was used 
primarily to locate the position and height of the inflection point 
of the red edge. The first derivative was calculated using a first- 
difference transformation of the reflectance spectrum obtained 
from the polynomial fit. In this case, the red-edge peak in the 
derivative spectra was composed of a peak maximum usually 
between 680 and 750 nm and calculated by the Peakfit curves 
statistical software (Version 4.12, Systat Software Inc. San Jose, 
USA). The first derivative was calculated using a first- 
difference transformation of the reflectance spectrum (Dawson 
and Curran, 1998) as follows (Eqs. 5): 
(Rj.(j+1) R ÀU) )/M (5) 
where FDR is the first derivative reflectance at a wavelength i, 
midpoint between wavebands j and j+1, RA,(j) is the reflectance 
at the j waveband, RA.(j+l) is the reflectance at the j+1 
waveband, and AX is the difference in wavelengths between j 
and j+1. 
3. RESULT AND DISCUSSION 
2.4 Data Analysis 
All statistical analyses were conducted using the STATISTICA 
statistical software (Version 6.1, StatSoft Inc. Tulsa, Oklahoma, 
USA, 2002). Coefficients of determination (R 2 ) were calculated 
for relationships between various chlorophyll content from the 
result of biochemical analysis treated as independent variables 
and vegetation indices and REP were collected from GERÌ500 
treated as dependent variable. To test and verify the relationship 
of chlorophyll content between vegetation indices and REP, 
regression analyses were used in the first data analysis step. The 
vegetation indices NDVI (Eqn. 1) and simple ratio (SR) (Eqn. 2) 
were used to calculate the vegetative indices obtained from 
spectral reflectance measurements: 
SR 
70S 
_ Riso 
Ryos 
(1) 
(2) 
Results of the data collection and analyses of chlorophyll 
content and leaf reflectance measurements are described here, 
showing the relationships found between derivative reflectance 
spectra (REP), vegetation indices and chlorophyll content 
measurements. 
3.1 Spectral Reflectance of Four Species 
In order to estimate chlorophyll content of tree leaves using 
spectral reflectance, hyperspectral remote sensing provided new 
approach for measuring chlorophyll content of plants because 
of its hyperspectral analytical rate, variety of wavelengths, 
continuance of wavelengths, and abundance of data. On the 
aspect of original spectral reflectance, most studies have proven 
that there is some correlation between spectral variants and 
pigment content. In addition, some predecessors have 
discovered that when plants are in different conditions in terms 
of nitrogen supply, nutrition level or hereditary factors, the 
leaves’ contents of chlorophyll and carotenoid are different, and 
the pigments’ contents of different leaves is also closely related 
with the environment in which the plant grows. In Fig. 1 we 
found that using the first derivatives spectra curve to find REP