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for the MODIS land product image format conversion and
coordinates transformation.
2.3 Spatial Data Preparation and Analyses
This study is conducted according to three major phases. The
three major phases comprises of data dissemination, data
reproduction and transformation and finally data analyses.
Figure 2 illustrate the processes involved in retrieving albedo.
MODIS LBl
MRT TOOLS:
CONVERSION AND
TRANSFORMATION
MODIS Li
MCDA2A?
LAXER STACKING
AND ADDITIONAL OFFSET
AND MULTIPLY FACTOR
LAYER STACKING
TO USE r-
FRACTION OF
DIFFUSE
SKYLIGHT VALUE
ATMOSPHERIC
CORRECTION: FLAASH, 55
CODE, MODTRAN
SUBSET FILL VALUE:
23.676, BSA AND WSA
TO USE: Whitz-sk» Albadg * [optical
dapth, solar zanith anelz. azrosol t-p2,
band) — Black-sk- Albado* {1 - Koptical
dapth, solar zsnith anzla, azrosol t-p2,
band)
TOUSE LIANG' S
MODEL
LAND SURFACE
ALBEDO :L53)
Figure 2. Albedo Retrieval Processes
The yearly and seasonal variations of land surface albedo for
the study are is derived according to the following steps:
1. The MODIS data (MCD43A3) were projected into
WGS84 and converted into GeoTIFF format and
Binary format using the MRT tools.
2. The Black Sky Albedo (BSA) and White Sky Albedo
(WSA) were then stacked into separate.
3. The fraction of diffuse skylight (s) is identified using
pre-determined lookup table and simulated
beforehand using the 6S code. The five parameters
needed to perform the simulation are as follows
(Wang et al. 2011; Zhao et al. 2001).
4. Geometrical Condition (value of solar zenith and
azimuthal angle, satellite zenith and azimuthal angle
and Julian Calendar of satellite revisit)
5. Atmospheric Model (tropical, mid latitude etc.) and
Aerosol Model Type (LUT AOT550)
6. Ground and Sensor Altitude (0 represents ground
surface and -1000 for sensor onboard satellite at
outside atmosphere)
7. Spectral bands (MODIS 500m 7 Bands data is pre-
defined in 6S Model)
8. Surface Reflectance Characteristics (homogeneous
and non-uniform surface)
9. The statistical of multi-temporal surface albedo were
calculated.
10. Visualization and Mapping
Based on BSA, WSA and the s (fraction of diffuse skylight)
determined in previous steps, the actual albedo can be
calculated according to (Zhang et al. 2010).
p =(1-s[6,7(2)}pair ^ s[8.c(A)]odif ()
where p -the actual albedo
s =the fraction of diffuse skylight
© = Solar Zenith Angle
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia
T = atmospheric optical depth
A = wavelength
pdir = the Black Sky Albedo
pdif =the White Sky Albedo
The s value in this study is based on the Fresnel Reflectance
coefficient light (Jerlov, 1976) which is set to 0.06
(Ambarwulan, 2010). The designs of analyses are based on
daily, yearly and according to Malaysia's Monsoon (Monthly)
variation. Malaysia seasonal breakdown are as Table 1.
Monsoon Period Characteristics
Northeast Nov- Winds 10-20 knots upto 30 Knots during
Mar cold surges period affecting east coast
region.
Heavy Rainfall
Inter- Apr- Frequent Period of Thunderstorm in
monsoon May afternoon and evening hour with heavy
Oct - rainfall causing flash flood.
Nov
Southwest May- Winds below 15 knots affecting west coast
Sept region.
Drier weather.
Table 1. Monsoon regimes in Malaysia. (MMD,(Shafie, 2009)).
3. ANALYSIS AND DISCUSSIONS
The analyses for this study are separated into three types of
series i.e. diurnally, yearly and according to monsoons. Tropical
country like Malaysia received extensive variation of weather
condition. Daily average will overshadow these effects as it will
suppress the highest and lowest condition. This will eliminate
the most remarkable and significance condition one can find.
The yearly analyses show the impact of land use and land cover
changes with respect to the yearly average albedo in Malaysia.
While the monsoon analyses enable us to recognise the albedo
behaviour and its pattern changes with respect to the local
climate condition and subsequently it's dynamic towards local
weather parameters. The following paragraphs will explain the
results of these analyses.
3.1 Result 1: The Time-series Analyses (Daily)
The average daily albedo of maximum and minimum value from
2000-2009 is 0.254144 and 0.002025 respectively. Though, the
highest daily albedo marked at 0.37566 at day 145 in 2005 and
the lowest daily albedo value is 0.00005 at day 41 in 2004. The
variation of daily albedo in terms of its maximum value shows
varies distribution over the years. As illustrated in Figure 3,
there is no certain linear trend of albedo for day 1 until day 361.
It can be inferred that this values are influences by the surface
properties, monsoon variation and also the diffusion of skylight.
This graph is plotted using real reflectance values not the daily
average values.
8 Days Time-Series Albedo 2000 - 2009
ann OQ 0 eee 200 1 o 2002 mme 200 3 2004
2007 2008 2009
oa
0.35
a3
0.25
0.2 f
015}
Albedo
0.05 |
o
1 17 33 49 65 B1 9/ 113129 115 167 177 293 209 225211 25 / 273 289 305 321 337 353
Day of Year
Figure 3. Daily Albedo 2000 - 2009
