TELKOM
NIKA
, Vol.11, No
.1, Janua
ry 2013, pp. 144
~15
0
ISSN: 2302-4
046
144
Re
cei
v
ed Se
ptem
ber 29, 2012; Revi
se
d No
vem
ber
23, 2012; Accepted Decem
ber 1, 201
2
HABs M
onitor: A Tool for Detecting HABs in East China
Sea
Chen Z
e
ng*, Huiping Xu, Hexia Zh
ang
State Ke
y
L
a
b
o
rator
y
of Mari
ne Geol
og
y, T
ong
ji Un
iversit
y
No. 123
9 Sip
i
n
g
Roa
d
, Shan
g
hai, Ch
ina
200
092,
*corres
pon
di
ng
author, e-mai
l
: 07zen
gch
en@
tongj
i.ed
u.cn
A
b
st
r
a
ct
T
h
is pa
per
des
igns
an
d d
e
vel
ops a
too
l
for
detectin
g
HAB
S
from ENVI+
I
DL+
A
rcEng
i
ne.
W
i
th
a
friend
ly a
n
d
art
i
stic int
e
rface
o
ffered by
thir
d
party co
nt
rol, t
h
is to
ol
provi
d
e
s
a fu
nctio
n
of
HABs
mo
nitori
n
g
in East C
h
in
a
Sea vi
a Re
mote Sens
ing I
m
a
ges i
n
vers
i
on.
T
h
roug
h row
s
of buttons
on t
he
me
nu b
a
r, thi
s
tool al
low
s
cal
c
ulati
ng sp
ectrum r
e
flectanc
e
,
brow
si
ng fiel
d w
o
rk data, interpo
l
atin
g in
situ measur
e
m
en
t
data, retriev
i
n
g
w
a
ter property
para
m
eters, a
nd d
e
tect
in
g H
ABs positi
on
b
y
the thresh
ol
d
of chlor
o
p
h
yll-
and se
a surfa
c
e temperat
ur
e. Data man
a
g
e
m
e
n
t mo
du
l
e
progr
a
m
me
d
in Structured
Query Lan
gu
age
(SQL
) i
n
o
u
r
to
o
l
sim
p
l
i
f
i
e
s th
e
d
a
t
a
p
r
o
c
ess a
n
d
sto
r
e
s
a
la
rge
amou
n
t
o
f
i
n
fo
rm
ati
o
n
.
Th
i
s
p
aper
ela
borates th
e
origi
n
a
l
des
ign,
function
al
mod
u
les, an
d
multi
data so
urces that gives
a ge
n
e
ral vi
ew
tow
a
rd
this tool.
Key Word
:
HABs
monitor; ENVI+
I
DL; E
a
st Chi
na Se
a;
Copyrig
h
t
©
2013
Univer
sitas Ahmad
Dahlan. All rights res
e
rv
ed.
1. Introduc
tion
The Harmful
algal blo
o
m
s
(HABs) (also terme
d
a
s
red tide
s) ha
ve been d
e
te
cted to
happ
en frequ
ently in
comp
lex Ca
se
-2
Water,
su
ch
as East
Chi
na
Sea (ES
C
) th
ese
years [1-2].
It was al
rea
d
y
rep
o
rted
th
at ESC h
a
s
much
mo
re
hi
ghly HAB
s
o
c
curre
n
ce
rate
s tha
n
oth
e
r three
margi
nal se
a
s
along
Chin
a mainlan
d
, durin
g 2002 t
o
2008. And HABs are also con
s
ide
r
e
d
to
have ca
used
tremen
dou
s d
a
mage i
n
the
coa
s
tal metr
o
polis, Sha
ngh
ai, espe
cially
in aqua
cultu
r
e
indu
stry in
20
03 [2]. Ma
ny
article
s
re
port
ed that
A. tamare
nse bl
oo
ms frequ
ently hap
pen
in th
e
East Chin
a Sea in the nea
rly deca
d
e
s
[1, 4-6]. Acco
rding to the st
atistics duri
n
g 1986 to 19
93,
the ESC 3
0
.5
°N-32°
N, 1
2
2
.
25°E-1
23.25
°E be
cam
e
th
e mo
st po
pul
ar a
r
ea
for HABs, wh
ere
the
occurre
n
ce n
u
mbe
r
re
ach
e
s to a
bout 9
1
times, an
d i
s
called
HABs hot
spot in t
he Yangt
ze
River
Estuary a
nd i
t
s adja
c
e
n
t sea. A larg
e
numbe
r of
e
c
onomi
c
lo
sse
s
b
r
ing
HABs an in
crea
sin
g
ly
seri
ou
s probl
em all aro
und
the world.
In order to
mi
tigate the
HA
Bs’ o
c
curre
n
ce, whi
c
h
i
s
ve
ry e
s
sential t
o
dete
c
t, mo
n
i
tor a
nd
forecast, ou
r
tool use
s
current availabl
e
remote
sen
s
ing tech
nolo
g
y
to trace the
i
r develop
me
n
t
and movem
e
nt while tra
d
itional ship-ba
s
ed field
sam
p
ling an
d an
alysis a
r
e ve
ry limited in both
spa
c
e an
d temporal frequ
ency [7]. Nowad
a
ys, satel
lite ocean
col
o
r se
nsors, such a
s
mode
rate-
resolution im
aging
spe
c
troradi
omete
r
(MO
D
IS),
are thought to
be an idea
l instrum
ent for
estimating gl
obal
p
h
ytopla
n
kton bioma
s
s,
espe
cia
lly
in epi
sodi
c bl
ooms, b
e
cau
s
e they p
r
ovi
d
e
relatively hig
h
fre
quen
cy
informatio
n i
n
mea
s
u
r
in
g
ban
ds from
visible
to n
ear-infra
re
d (NIR)
spe
c
tral
ran
g
e
. These ba
nds
and a
d
e
quate
spatial
resolution m
a
ke it po
ssibl
e
to detect a
n
d
trace
HABs from spa
c
e.
The adva
n
ce
in comp
uter operation a
nd
inform
atio
n storage b
u
ilds ba
si
s for high-
cap
a
city
data
pro
c
e
ss. Co
mbined with daily
sa
tellite
MODIS data
explorin
g ov
er the ESC, t
h
is
can ma
ke
s u
p
a tool to monitor an
d su
rvey the
HABs occu
rre
nce. This articl
e aims to desi
g
n
and
reali
z
e
d
a comp
reh
e
n
s
ive tool, i
n
cl
uding
thre
e
data
sou
r
ce
(Re
m
ote S
e
n
s
ing
(RS) da
ta,
field wo
rk sp
ectru
m
data,
and
ocean
situ me
asure
m
ent data
)
,
data p
r
o
c
e
s
s model
s b
e
twee
n
them, HABs
detectio
n
and
monitorin
g
re
port.
Evaluation Warning : The document was created with Spire.PDF for Python.
145
TEL
K
2. G
e
butto
extra
imag
e
Logi
c
desi
g
outp
u
oper
a
F
from
calib
r
mak
e
sea
surf
a
data
aver
a
inne
r
and
S
Dist
a
con
c
e
is gl
o
A
dmi
inver
s
α
pa
r
sc
re
e
seq
u
e
HAB
s
acco
u
K
OM
NIKA
V
e
neral d
esi
g
The tool
n to re
alizi
n
ction
an
d cl
a
e
an
d nu
me
r
The fra
m
c
Laye
r
and
g
n and
mut
u
u
t forms
.
D
a
ting pe
rfor
m
F
igure 1. Th
e
Our tool
d
sp
atial g
eo-
d
Image
p
r
ation, g
e
o
m
e
s ready
for
t
In situ
m
su
rface sa
n
ce
t
u
rbi
d
it
y
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a
ng
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fr
o
m
a
ge
va
lue
,
c
o
r
-p
rog
r
a
m
m
e
S
ST, we
rev
e
a
nce Wei
ght
e
Paramet
e
e
ntration
ba
s
o
bal wat
e
r
p
nis
t
ration (N
The co
m
s
i
on re
sults,
r
amete
r
s.
Outpu
t
m
e
n-pictu
r
e f
o
e
nc
es
. An
d
s
comp
rehe
n
In order
u
nt the
a
c
tu
a
ol. 11, No
. 1
g
n of the
to
o
for detectin
n
g MODI
S
a
ssification
a
r
i
c
al re
po
rt,
t
m
ew
or
k
o
f
th
D
a
ta
Laye
r
u
al interactio
ata Layer s
t
m
an
ce.
e
framework
disp
d
ispl
ays ES
C
d
ataba
se i
n
f
o
p
roc
essing
m
et
ri
c co
rr
ec
t
t
he followi
ng
m
eas
ureme
n
n
d con
c
en
tr
a
(SSTU) dat
a
m
30
0 to 10
0
o
mpute
s
refl
e
d algo
rit
h
m.
e
al
s it
s
ch
an
e
d (ID
W
), Kr
i
e
r inv
e
rsi
o
s
ed on
ch
ar
a
p
ara
m
eter i
n
ASA), spec
i
f
m
p
r
e
h
ensiv
e
forecasti
ng
m
odu
le
st
o
r
e
o
rm
at an
d
a
n
mo
nitori
ng
r
n
sive mo
del
a
to realize
a
a
l produ
ctio
n
, Janua
ry 2
0
o
l
g HA
Bs in
E
image pre
p
r
a
ccordi
ng t
o
t
he tool bec
o
e to
ol
is th
r
r
(Fig
ure 1
)
.
n. Logic
L
a
t
ore
s
all of
t
of
tool: the
a
l
a
ys the g
e
n
e
C
administr
a
o
rmatio
n.
modu
le
c
a
t
ion, b
o
w co
paramete
r
i
n
t d
a
ta proc
e
a
tion (SSS)
a
, s
e
a surf
a
0
0 nm at in
t
ecta
nce, ga
With reg
a
r
d
ge of
gra
d
i
e
i
king, Spline
,
o
n module
a
ct
eri
s
t
i
c b
a
n
n
version m
o
f
ically abo
ut
e
HA
Bs in
v
th
e pr
o
p
e
r
p
e
s all of
the
i
n
imation for
m
r
ep
ort su
mm
a
lgorithm.
a
uto
m
atic d
e
n
n
eed
s, thi
s
0
13 : 144 –
1
E
SC ac
com
r
oc
es
s
i
n
g
,
w
o
thre
sh
old
a
o
mes a
n
ope
ee
-laye
r
a
r
c
.
Pre
s
entat
a
yer contai
n
s
t
he input a
n
a
rro
ws d
edi
c
a
e
ral functio
n
a
tive divis
i
on
a
rri
es on
fu
rrectio
n
an
d
nversio
n
s.
e
ssin
g
mo
d
data, chl
o
r
a
ce
t
e
mpe
r
a
t
t
erval of ev
e
ins no
rmali
z
d
to spatial
d
nt via variou
,
Trend, Via
r
emb
r
ace
s
n
d fit c
oeffici
del p
ubli
s
h
e
chl-
α
and
S
S
v
ersion m
o
p
o
s
ition of
H
A
m
age
s abo
v
m
at, which
a
r
iz
es
the
H
e
tec
t
ion of
w
s
tool
al
so
o
f
1
50
pli
s
he
d maj
o
w
ater qualit
y
a
nalysi
s
. By
n-an
d-sh
ut,
u
c
h
i
te
c
t
ur
es
,
w
i
on Laye
r
c
h
s
data p
r
o
c
e
n
d output d
a
a
te the main
s an
d ope
r
a
t
an
d coastli
n
n
dame
n
tal
o
image
clip
p
d
ule
manipul
r
ophyll-
α
co
n
t
ure (SST)
d
e
ry 3 nm, to
w
a
tion and s
e
d
istribution d
a
s interpolati
o
r
ogra
m.
two ki
nds
ents fro
m
in
e
d from
Nat
S
T.
o
del
is on
A
Bs through
v
e
the
up
per
conve
n
ient
H
ABs pos
i
tio
n
w
h
e
ther the
f
fers
oth
e
r
s
c
o
r func
tions
y
param
e
te
r
HABs
wate
r
u
ser-frie
ndl
y
w
hich a
r
e
P
r
h
ara
c
t
e
ri
ze
s
e
ss
ing flow,
a
ta
,
w
h
i
c
h
o
b
pr
oce
s
s
o
f
t
t
ions.
n
e a
s
its ba
s
o
pe
r
a
tion
s
a
p
in
g
.
T
h
os
e
ates work
fi
e
n
centration
d
ata. Spe
c
t
r
w
ard whi
c
h
e
l
e
ct
s cha
r
a
c
a
t
a
su
ch a
s
o
n algo
rithm
s
of algo
rith
m
sit
u
mea
s
u
r
io
nal Aeron
a
the founda
t
t
he th
resho
mod
e
l an
d
c
us
e
r
s to
ob
s
n
informatio
n
re
d tide
oc
c
c
ientific anal
I
SSN: 230
2
sim
p
ly
t
h
ro
r
in
ve
r
s
io
n
,
r
re
finement
y
software.
r
esentation
L
i
n
user int
e
data model
b
vious
l
y im
p
t
he tool, whi
c
s
e m
ap,
sup
p
a
bo
ut ra
dio
da
ta pret
re
a
e
ld
s
p
e
c
tr
u
m
(c
hl-
α
) d
a
t
a
r
um me
as
ur
e
this tool ac
h
c
teris
t
ic
ban
d
SSS, c
h
l-
α
,
s
,
su
ch a
s
I
n
m
, one
co
n
r
e
m
ents; th
e
a
utics and
S
t
ion of
p
a
r
a
ld
of SST a
n
c
onve
rts th
e
m
s
e
r
ve chan
g
n
ac
co
rd
in
g
c
ur an
d ta
k
ysi
s
ability,
t
2
-4
046
ugh a
HA
Bs
re
s
u
lt
L
ayer,
e
rf
ace
s and
p
rov
e
s
c
h
p
orte
d
metri
c
a
tment
m
data,
a
, sea
e
m
ent
h
ieves
d
from
SSTU
n
vers
e
n
du
ct
s
e
ot
her
S
pa
ce
a
me
te
r
n
d chl-
m
into
g
ea
ble
to the
e into
t
hat i
s
Evaluation Warning : The document was created with Spire.PDF for Python.
TEL
K
adju
s
exa
m
alon
g
accu
r
also
outp
u
conv
e
3. K
e
prop
e
ENV
I
prog
r
ENV
I
Hier
a
lang
u
com
b
and
a
mod
u
3.1.
W
imag
e
will e
Figu
e
the
m
glob
a
oce
a
mod
e
K
OM
NIKA
s
t the view
p
m
ple, the
dat
a
g
with the i
n
r
acy. Th
e d
a
The HA
B
h
e
lp sci
enti
s
u
t format
of
e
nient scien
t
e
y
technolo
g
For a
c
hi
e
e
r
t
y meas
u
r
e
I
/IDL (E
nvir
o
r
am
-d
evelop
I
/
I
D
L ma
ke
s
a
rc
hic
a
l D
a
t
a
u
age, which
b
i
ned wit
h
th
a
rti
s
tic.
The follo
w
u
le, HAB
s
m
o
W
ater p
a
ra
m
Our to
ol
e
. B
o
th
par
a
labo
rate the
re 2. HABs
m
quatio
n co
e
f
OC3 i
s
a
m
o
s
t opti
m
iz
e
a
l o
c
ea
n ob
s
n ba
nd refl
e
e
l buil
d
in
g of
HAB
s
p
a
r
amete
r
s
a
collected i
n
n
cr
eas
i
ng to
o
a
t
a
so
ur
ce
s
a
B
s m
onitor t
o
s
ts
to do s
o
the rang
e,
t
is
ts
for the l
o
g
ies of to
ol
e
vin
g
the ai
m
e
me
nt dat
a i
o
nm
ent f
o
r
in
g tool
s, i
n
it conven
ie
n
a
Fo
rmat
(H
seamle
ss
ird party co
n
w
i
n
g
conte
n
o
nito
ring mo
m
eter inv
e
r
s
mo
ni
to
r
s
H
A
a
meters are
details a
b
o
u
m
onitori
ng
m
f
f
i
cient
s,
w
h
i
c
m
e
a
n e
m
piri
cal
e
d
on
e
com
s
ervation sta
e
ct
an
ce rat
i
o
biquad
rat
i
c
I
S
s
monitor: A
t
a
c
cording t
o
n
the field
w
o
l running
t
i
a
re al
so div
e
r
o
ol, in
additi
o
me a
naly
s
i
s
includin
g
t
h
o
ng-te
rm m
o
design
m
s of
RS da
t
nterpolatio
n
,
Vi
suali
z
in
g
n
which
A
E
n
ce to mani
p
DF). O
u
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147
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ENVI to
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.5 to judg
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4
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chiev
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B
eration an
d
D
F data
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m
h
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u
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Module
h
i
s
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t
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u
gh
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a
SST
0
13 : 144 –
1
, the nu
m
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rithm (S
WA
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uce SST fr
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ry produ
ce
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tly [11]
.
s
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ss
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p to
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A
HABs
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S detectio
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at, which c
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m
ation:
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43
879
(
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K
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he wat
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r p
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r
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n
With the i
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ibilities of H
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l
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ndex fo
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Bs
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S
t
ly or indire
c
h
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plete the
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S
T
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ission radi
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K
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uri
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T
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se
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e t
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or HABs m
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r refle
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t
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c
1
,
c
i
ting for ES
C
a
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infrared e
m
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hl-
α
is the
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r
f
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m
ak
es
ch
l-
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of
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[1
2
t
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eutrop
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c
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ai
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shold of
chl
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, according
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,
y
. IDL supp
o
image
s as
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nag
e
me
nt,
w
n
izations to
w
pli
c
ation mo
SST(
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qua)
P
2.133
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2
-4
046
h
and
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nitor.
s
ph
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,
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[10].
h
t
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]. S
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ard
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P
.M.
Evaluation Warning : The document was created with Spire.PDF for Python.
TELKOM
NIKA
ISSN:
2302-4
046
148
HABs m
onitor: A tool for detecting
H
ABs in East China Sea (Che
n Zeng
)
whe
r
e
data a
dd, data
dele
t
e, data che
c
k an
d d
a
ta
m
odify are tota
lly supe
rvise
d
and
co
ntroll
ed
by the unified software - SQL Server. T
h
rou
gh t
he secu
rity contro
l within SQL Server, the h
uge
amount
of o
r
i
g
inal
disord
er data
gain
cl
e
a
rly di
st
rib
u
tion a
nd
well
manag
eme
n
t. Th
e tool
buil
t
-in
pro
c
e
ss
co
ntrol sim
p
lifies
the use
r
dat
a sele
ct
ion
a
bout co
mplex
queri
e
s, opti
m
ize
s
the u
s
er
operation p
r
o
c
e
s
ses a
nd redu
ce
s ope
ra
tion time.
Figure 3 d
e
m
onst
r
ate
s
the mod
e
l di
agra
m
de
sig
ned for th
e
databa
se, a
one-to
-o
ne
relation
shi
p
throu
gh the m
e
sh mo
del, which n
o
t only reflect
s
the ri
ch involved f
eature
s
, but
also
sho
w
s the
co
mplicate
d
rel
a
tionship
s
be
tween
data.
The field
wo
rk data
co
ntai
ns the
storag
e o
f
several data,
whi
c
h ta
kes a phen
ome
non view th
rough
our to
ol, and b
r
o
w
se
s the
spat
ial
distrib
u
tion
chara
c
te
risti
c
s via calculatio
n and in
te
rp
o
l
ation betwee
n
them. RS Image d
a
ta, a
fter
pretreatment,
co
mbin
ed
with average
of fitting
coef
ficients by th
e regressio
n
mod
e
l, get
the
water SST, a
nd then monit
o
r the re
d tide based on in
versio
n thre
shold an
alysis.
Figure 3. The
databa
se mo
del image fo
r this t
ool: the Name in all th
ose li
sts are deman
ded
stri
ctly to be Year-Month
-
Date-Ho
u
r-Mi
nute (e.g
., 20
07-0
9
-27-16-30) that ma
ke
s it same to
comp
are. All
the items in b
o
ld-type letter are
that users nee
d to pre
pare
d
, and ot
her on
es
can
gain calculation in our tool.
All record
ed
ones
a
r
e sto
r
e paths ex
ce
pt Name an
d Prope
rty in list
Field Wo
rk.
In the a
c
tual
pro
c
e
d
u
r
e
s
, datab
ase m
anag
ement
make
s
data
pro
c
e
s
s mo
re cl
early,
define
s
pre
c
eden
ce
relati
onship con
s
traints, su
ch
t
hat the pret
reatment
process is g
eom
etric
corre
c
tion, b
o
w
co
rre
ctio
n, tailoring,
and atm
o
sp
h
e
ric corre
c
tion. This to
ol
use
s
con
d
itio
nal
inquiry restri
ctions, ena
blin
g use
r
s to
se
lect t
he data
operation whi
c
h only fit for this step. Th
is
limitation gre
a
tly optimize
s
u
s
er ope
ra
tion pro
c
e
s
s
and time. In
addition to th
e satellite
da
ta
pretreatment
pro
c
e
ss, water quality pa
rameter inve
rsion mo
dule,
red tide mo
nitoring m
o
d
u
le,
field work dat
a module al
so entirely app
ly the i
nquiry con
d
ition
s
limit, at users
co
nvenien
ce.
4. Tool application
This to
ol i
s
applie
d when
maki
ng
use
of MO
DIS L
1
B imag
e de
tects
red
tid
e
. The
followin
g
is a
case of MO
DIS/Terra on
Septem
ber
27, 2007, re
solution of 25
0m to pre
s
en
t the
effec
t
ivenes
s
of this
tool.
Figure 4 di
sp
lays the u
s
a
ge of this too
l
to
a gre
a
t e
x
tent, which i
s
pithy, and
artistic.
The Data Ma
nagem
ent in t
he up
per-ri
gh
t of the in
terfa
c
e o
perates t
he interactio
n
betwe
en u
s
e
r
s
and d
a
taba
se
, rep
r
e
s
ent
s the dat
a sto
r
a
ge, an
d si
mp
l
i
fies dat
a p
r
o
g
re
ss.
The
user inte
rfa
c
e
(UI)
of this to
ol refers from
O
ffice 20
07; t
he tool
bar in
volves nin
e
t
ags,
whi
c
h
repre
s
e
n
ts
m
a
in
module
cl
assification
s; the
col
u
mn
bar
in the left of
win
dow is for laye
r b
r
o
w
se, the mi
d
d
le
wind
ow for i
m
age di
splay
,
the upper-ri
ght one fo
r d
a
taba
se inq
u
i
r
y and statu
s
,
and the bott
o
m-
right for layer
feature inq
u
iry.
From
the
Fi
g
u
re 4 we ca
n
se
e som
e
key
st
ep
s
and
modul
es in t
he runni
ng
proce
s
s of
the tool, which provide
s
a
clea
r impression towa
rd
thi
s
tool. Thro
u
gh multi-sou
r
ce data p
r
o
c
e
ss,
Evaluation Warning : The document was created with Spire.PDF for Python.
149
ISSN: 2302-4
046
TELKOM
NIKA
Vol. 11, No
. 1, Janua
ry 2013 : 144 – 1
5
0
this tool
integ
r
ates
several
functio
n
s to
sci
entif
ic
re
searche
s
, e.
g., wo
rk field
d
a
ta an
alysi
s
and
cal
c
ulatio
n, remote sen
s
in
g image
pre
p
r
ocess a
nd
in
versio
n. Moreover, ou
r to
ol ca
n notify the
red tid
e
a
nd
catch the
po
sition i
n
the
ESC, whi
c
h
ve
rifies th
e p
r
acti
cality an
d scie
ntificity of it,
according to the Re
d Tide report on
re
se
arch [17] publ
ishe
d in 200
7
,
ESC.
a
b
c
d
e
f
Figure 4. The
function di
spl
a
y of this tool: Figur
e 4a. is the browse o
f
administrative map from
spe
c
ial g
eo-d
a
taba
se; Figu
re 4b is
seve
ral inte
rpol
atio
n method
s sh
owin
g sp
ecial
distributio
n
toward ae
rial
survey data;
Figure 4c d
e
m
onst
r
at
e
s
the spe
c
tru
m
re
flectan
c
e calculation from
field work sou
r
ce , the imag
e dra
w
ing a
n
d
the
storage
of characte
ri
stic band d
a
ta for fitting;
Figure 4d sho
w
s the
water
para
m
eter inv
e
rsi
on from e
m
piri
cal mod
u
le whi
c
h i
s
saved in the
Figure 4c, or
from publi
s
h
e
d
module that
is introdu
ce
d
in sectio
n 3; Figure 4e di
splays the HA
Bs
detectio
n
re
sult through
ch
lorop
h
yll-
α
a
n
d
sea
surfa
c
e
temperatu
r
e
value thre
sho
l
d, and
comp
utes the
position of it; Figure 4f op
en up
s gra
phi
cs
cap
a
city in
cludi
ng title, legen
d,
coo
r
din
a
te axes.
5. Conclusio
n
With p
r
a
c
tical
function, m
u
ltisource
data
i
nput, su
rrou
nding fu
nctio
n
exploration
at the
core of the
HABs monito
r, this tool
real
ize
the
ori
g
in
al de
sign
aim
.
It enforce
s
comp
re
hen
si
ve
admini
s
tratio
n ab
out multi
s
ou
rce d
a
ta,
reali
z
e
s
the
HABs dete
c
tion,
build
s rel
a
tionship
b
e
twee
n
multisou
rce i
n
formatio
n to obtain more
exact co
ncl
u
sion a
nd p
r
o
v
ides fun
c
tio
n
s of browse
and
analysi
s
towa
rd multisource data.
However, wit
h
the dev
elopment of science & technology,
this system still has something
to c
o
mplement.
1)
By the limitation of in situ
measure
m
e
n
t in
ESC, it exists big
g
e
r
erro
rs in
gl
obal mo
del
inversi
on.
With the in
crea
si
ng of real m
e
asu
r
em
ent d
a
taba
se a
nd
compl
e
me
nt of empiri
cal
Evaluation Warning : The document was created with Spire.PDF for Python.
TELKOM
NIKA
ISSN:
2302-4
046
150
HABs m
onitor: A tool for detecting
H
ABs in East China Sea (Che
n Zeng
)
model, we can lift up the application
coverage
an
d accu
ra
cy for the sy
ste
m
cate
ring t
o
different se
asons in dive
rse climate in E
S
C.
2)
Enhan
cing
diversity of obt
aining
satellit
e dat
a; this
system merely carrie
s on M
O
DIS data
and give
s
priority to o
c
e
an
colo
r for
the o
c
curren
ce
and
deve
l
opment
of
HABs, n
o
t to
mention
of forecastin
g. M
any arti
cle
s
reporte
d that
HABs h
a
s hi
ghly co
rrelati
on with
sea
surfa
c
e
win
d
, therefo
r
e
we
can j
o
int wi
n
d
situatio
n to
pre
d
ict the
HABs afte
r g
a
ining SA
R
information.
3)
We still n
o
t con
s
id
er ab
o
u
t metadata
cont
rol, neve
r
thele
ss it b
e
com
e
s m
o
re and mo
re
importa
nt alo
ng
with the
g
r
owth
of i
n
formation in
dat
aba
se, the
m
e
tadata m
a
n
ageme
n
t is
proved to be
a key link for
databa
se
saf
e
ty.
Last
but
not l
east, it i
s
i
m
p
o
rtant to
note
that
the
a
c
cura
cy of
re
sul
t
s la
rgely
dep
end
on th
e
input d
a
ta a
n
d
the
empi
rical mod
e
l, whi
c
h m
a
kes the
quality of
RS informatio
n
top p
r
io
rity.
For the pu
rpo
s
e of re
sea
r
ch and ed
ucational onl
y, this tool is just a basi
c
version.
Referen
ces
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Cha
ng F
H
, Ud
dstrom M, Pink
erton M.
Studi
es of the w
i
nte
r
200
0 Gy
mno
d
ini
u
m cate
nat
um
outbr
eak
s
in
New
Z
e
a
l
a
nd
usin
g r
e
motely s
ens
ed
sea s
u
rf
ace
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ature
a
nd c
h
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o
p
h
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a
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m
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es
. Proceed
ings
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oto
x
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nc
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rkshop, Ne
w
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gton, 20
01
;
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X
,
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an
kton distri
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Evaluation Warning : The document was created with Spire.PDF for Python.