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Evaluation Warning : The document was created with Spire.PDF for Python.
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J
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Sci
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Vo
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43
,
No
.
2
,
Au
g
u
s
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20
26
:
65
1
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6
6
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652
Geo
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r
s
,
l
an
d
u
s
e
p
atter
n
s
,
i
n
f
r
astru
ct
u
r
e
n
etwo
r
k
s
,
a
n
d
en
v
ir
o
n
m
en
tal
r
is
k
s
to
b
e
r
e
p
r
esen
ted
a
n
d
e
x
am
in
ed
with
in
th
eir
g
e
o
g
r
ap
h
ic
co
n
tex
t
,
r
ev
ea
lin
g
s
p
atial
h
eter
o
g
en
eity
an
d
r
eg
io
n
al
d
ep
en
d
en
cies
th
at
a
r
e
n
o
t
ca
p
tu
r
ed
b
y
co
n
v
en
tio
n
al
s
tatis
t
ical
m
eth
o
d
s
.
ML
tech
n
iq
u
es,
p
ar
ticu
lar
ly
th
o
s
e
ca
p
ab
le
o
f
h
an
d
lin
g
h
ig
h
-
d
i
m
en
s
io
n
al
an
d
n
o
n
lin
ea
r
d
ata
,
h
av
e
b
ee
n
wid
ely
ap
p
lied
in
s
p
atial
m
o
d
elin
g
tas
k
s
s
u
ch
as
p
o
p
u
la
tio
n
d
is
tr
ib
u
t
io
n
an
al
y
s
is
,
u
r
b
an
s
tr
u
ctu
r
e
e
x
tr
ac
tio
n
,
a
n
d
lan
d
u
s
e
ch
an
g
e
p
r
e
d
ictio
n
[
1
]
-
[
6
]
.
T
h
ese
ad
v
an
ce
s
d
em
o
n
s
tr
ate
th
e
s
tr
o
n
g
p
o
ten
tial
o
f
i
n
teg
r
at
in
g
g
eo
s
p
atial
d
ata
an
d
in
tellig
en
t a
lg
o
r
ith
m
s
f
o
r
r
eg
io
n
al
-
s
ca
le
d
ec
is
io
n
s
u
p
p
o
r
t
.
Am
o
n
g
v
ar
io
u
s
ML
a
p
p
r
o
ac
h
es,
r
an
d
o
m
f
o
r
est
(
R
F)
h
as
e
m
er
g
ed
as
a
r
o
b
u
s
t
an
d
v
e
r
s
atile
m
eth
o
d
f
o
r
s
p
atial
p
r
ed
ictio
n
an
d
cl
ass
if
icatio
n
.
Stu
d
ies
h
av
e
s
h
o
wn
th
at
RF
p
e
r
f
o
r
m
s
well
in
m
o
d
elin
g
s
p
atial
d
is
tr
ib
u
tio
n
s
o
f
p
o
p
u
latio
n
an
d
b
u
ilt
en
v
ir
o
n
m
en
ts
,
ev
en
u
n
d
er
lim
ited
d
ata
co
n
d
itio
n
s
,
d
u
e
to
its
en
s
em
b
le
s
tr
u
ctu
r
e
an
d
r
esis
tan
ce
to
o
v
er
f
itti
n
g
[
1
]
,
[
2
]
.
I
ts
ef
f
ec
ti
v
en
ess
h
as
also
b
ee
n
d
e
m
o
n
s
tr
ated
in
s
u
itab
ilit
y
an
aly
s
is
,
wh
er
e
m
u
ltis
o
u
r
ce
g
eo
s
p
atial
d
ata
ar
e
in
teg
r
ated
to
ev
alu
ate
s
p
atial
p
o
ten
tial
f
o
r
s
p
ec
if
ic
ac
tiv
itie
s
o
r
d
e
v
elo
p
m
e
n
t
p
r
i
o
r
ities
[
7
]
-
[
9
]
.
Fu
r
th
er
m
o
r
e,
RF
h
as
b
ee
n
s
u
cc
ess
f
u
lly
ap
p
lied
in
a
wid
e
r
a
n
g
e
o
f
g
eo
s
p
atial
ap
p
licatio
n
s
,
in
clu
d
in
g
u
r
b
a
n
cr
im
e
h
o
ts
p
o
t
d
e
tectio
n
[
1
0
]
,
h
y
d
r
o
lo
g
ical
p
r
ed
ictio
n
[
1
1
]
,
an
d
d
is
aster
-
r
elate
d
s
p
atial
m
o
d
elin
g
s
u
ch
as lan
d
s
lid
e
s
u
s
ce
p
tib
i
lity
ass
es
s
m
en
t [
1
2
]
,
[
1
3
]
.
R
ec
en
t
liter
atu
r
e
h
ig
h
lig
h
ts
a
g
r
o
win
g
tr
en
d
to
war
d
co
m
b
in
in
g
ML
with
g
eo
s
p
atial
in
tell
ig
en
ce
to
s
u
p
p
o
r
t
s
o
cio
-
ec
o
n
o
m
ic
an
d
en
v
ir
o
n
m
e
n
tal
d
ec
is
io
n
m
a
k
in
g
.
I
n
te
g
r
ativ
e
ap
p
r
o
ac
h
es
th
at
m
er
g
e
s
o
cio
-
ec
o
n
o
m
ic
i
n
d
icato
r
s
with
s
p
atial
d
ata
h
av
e
b
ee
n
ap
p
li
ed
to
ass
ess
v
u
ln
er
ab
ilit
y
,
s
u
s
tain
ab
ilit
y
,
an
d
d
ev
elo
p
m
e
n
t
p
o
ten
tial
ac
r
o
s
s
r
eg
io
n
s
[
3
]
,
[
1
0
]
.
I
n
th
e
c
o
n
tex
t
o
f
u
r
b
an
a
n
d
r
eg
io
n
al
s
tu
d
ies,
ML
-
b
ased
g
eo
s
p
atial
an
aly
s
is
h
as b
ee
n
u
s
ed
to
m
o
d
el
u
r
b
a
n
ex
p
an
s
io
n
,
lan
d
u
s
e
d
y
n
am
ics,
ca
r
b
o
n
e
m
is
s
io
n
s
,
an
d
m
u
lti
-
h
az
ar
d
v
u
l
n
er
ab
ilit
y
,
p
r
o
v
id
i
n
g
v
alu
ab
le
in
s
ig
h
ts
f
o
r
p
lan
n
er
s
an
d
p
o
licy
m
a
k
er
s
[
4
]
,
[
1
4
]
-
[
1
6
]
.
H
o
wev
er
,
m
an
y
o
f
th
ese
s
tu
d
ies
f
o
cu
s
o
n
s
in
g
le
-
s
ec
to
r
o
r
d
o
m
ain
-
s
p
ec
if
ic
p
r
o
b
lem
s
an
d
d
o
n
o
t
ex
p
licitly
a
d
d
r
ess
in
teg
r
ated
IR
ass
ess
m
en
t.
Desp
ite
its
s
tr
o
n
g
p
r
e
d
ictiv
e
ca
p
ab
ilit
y
,
th
e
ap
p
licatio
n
o
f
RF
in
s
p
atial
m
o
d
elin
g
r
eq
u
ir
es
ca
r
ef
u
l
co
n
s
id
er
atio
n
o
f
s
p
atial
au
t
o
c
o
r
r
elatio
n
a
n
d
v
alid
atio
n
s
tr
ateg
ies.
R
ec
en
t
s
tu
d
ies
em
p
h
asize
th
e
im
p
o
r
tan
ce
o
f
s
p
atially
awa
r
e
m
o
d
elin
g
,
s
p
atial
cr
o
s
s
-
v
alid
atio
n
,
an
d
th
e
u
s
e
o
f
s
p
atial
p
r
o
x
ies
to
im
p
r
o
v
e
g
en
er
aliza
tio
n
an
d
av
o
id
b
iased
p
r
ed
ictio
n
s
[
9
]
,
[
1
7
]
-
[
2
1
]
.
T
h
ese
m
eth
o
d
o
lo
g
ical
co
n
s
id
er
atio
n
s
ar
e
p
ar
ticu
lar
ly
im
p
o
r
tan
t
wh
en
ML
m
o
d
els
ar
e
u
s
ed
t
o
s
u
p
p
o
r
t
s
tr
ateg
ic
d
ec
is
io
n
m
a
k
in
g
,
s
u
ch
as
r
eg
i
o
n
al
in
v
estme
n
t
p
lan
n
i
n
g
,
wh
er
e
r
eliab
ilit
y
an
d
in
ter
p
r
eta
b
ilit
y
ar
e
ess
en
tial.
W
h
ile
th
e
p
r
esen
t
s
tu
d
y
ad
o
p
ts
leav
e
-
o
n
e
-
o
u
t
cr
o
s
s
-
v
alid
atio
n
to
ad
d
r
ess
th
e
ch
allen
g
e
o
f
a
s
m
all
r
eg
io
n
al
s
am
p
le,
f
o
r
m
al
s
p
atial
au
to
co
r
r
elatio
n
test
in
g
r
e
m
a
in
s
an
im
p
o
r
ta
n
t
d
ir
ec
tio
n
f
o
r
f
u
tu
r
e
r
e
f
in
em
en
t
o
f
th
e
m
o
d
elin
g
f
r
am
ewo
r
k
a
s
s
h
o
wn
in
s
ec
tio
n
4
.
Desp
ite
th
e
g
r
o
win
g
b
o
d
y
o
f
r
esear
ch
co
m
b
in
in
g
g
e
o
s
p
atial
an
aly
s
is
an
d
ML
,
m
o
s
t
ex
is
tin
g
s
tu
d
ies
ad
d
r
ess
th
ese
co
m
p
o
n
e
n
ts
s
ep
ar
ately
:
s
p
atial
s
u
itab
ilit
y
o
r
h
az
ar
d
m
o
d
eli
n
g
o
n
o
n
e
h
an
d
,
an
d
s
o
cio
-
ec
o
n
o
m
ic
ass
es
s
m
en
t
o
n
th
e
o
t
h
er
,
with
f
ew
f
r
am
ewo
r
k
s
jo
in
tly
in
te
g
r
atin
g
s
o
cio
-
e
co
n
o
m
ic
in
d
ic
ato
r
s
,
in
f
r
astru
ctu
r
e
ac
ce
s
s
ib
ilit
y
,
an
d
d
is
aster
r
is
k
in
to
a
s
in
g
le
p
r
e
d
ictiv
e
s
co
r
e
f
o
r
i
n
v
estme
n
t
d
ec
is
io
n
m
ak
in
g
.
Mo
r
eo
v
e
r
,
ex
is
tin
g
RF
-
b
ased
s
p
atial
s
tu
d
ies
r
ar
ely
ad
d
r
ess
th
e
c
h
allen
g
e
o
f
v
alid
atin
g
m
o
d
els
o
n
s
m
all,
r
eg
io
n
-
lev
el
d
atasets
,
wh
ich
is
a
co
m
m
o
n
c
o
n
s
tr
ain
t
in
s
u
b
-
n
atio
n
al
in
v
estme
n
t
p
lan
n
in
g
co
n
tex
ts
.
T
h
is
r
esear
ch
ad
d
r
ess
es
th
e
id
en
tifie
d
g
a
p
b
y
p
r
o
p
o
s
in
g
a
n
i
n
tellig
en
t
s
y
s
tem
th
at
in
teg
r
ates
g
eo
s
p
atial
d
ata
p
r
o
ce
s
s
in
g
an
d
a
RF
-
b
ased
class
if
icatio
n
m
o
d
el
to
ass
es
s
r
eg
io
n
al
IR
.
T
h
e
s
y
s
t
em
co
m
b
in
es
m
u
ltid
im
en
s
io
n
al
s
o
cio
-
ec
o
n
o
m
ic
in
d
icato
r
s
,
in
f
r
astru
ct
u
r
e
ac
c
ess
ib
ilit
y
m
etr
ics,
lan
d
u
s
e
ch
ar
ac
ter
is
tics
,
an
d
d
is
a
s
ter
r
is
k
v
ar
iab
les
in
to
a
u
n
if
ied
s
p
atial
f
r
am
ewo
r
k
.
B
y
lev
er
ag
in
g
th
e
s
tr
en
g
th
s
o
f
RF
in
h
an
d
lin
g
h
eter
o
g
e
n
eo
u
s
d
ata
an
d
ca
p
tu
r
in
g
n
o
n
lin
ea
r
r
elatio
n
s
h
ip
s
,
th
e
p
r
o
p
o
s
ed
ap
p
r
o
ac
h
aim
s
to
p
r
o
d
u
ce
r
eliab
le
an
d
in
ter
p
r
etab
le
IR
clas
s
if
icatio
n
s
at
th
e
r
eg
io
n
a
l
lev
el
[
1
]
,
[
1
0
]
,
[
1
7
]
.
T
o
en
h
a
n
ce
u
s
ab
ilit
y
an
d
tr
a
n
s
p
ar
en
c
y
,
th
e
p
r
e
d
ictio
n
r
esu
lts
ar
e
im
p
lem
en
ted
with
in
a
s
p
ati
al
d
ec
is
io
n
-
s
u
p
p
o
r
t
en
v
ir
o
n
m
en
t
th
at
en
ab
les
in
ter
ac
tiv
e
v
is
u
aliza
tio
n
an
d
ex
p
lo
r
atio
n
o
f
r
eg
io
n
al
i
n
v
estme
n
t p
atter
n
s
.
T
h
e
n
o
v
elty
o
f
th
is
s
tu
d
y
lies
in
its
h
o
lis
tic
in
teg
r
atio
n
o
f
g
eo
s
p
atial
d
ata,
en
s
em
b
le
ML
,
an
d
d
ec
is
io
n
-
s
u
p
p
o
r
t
v
is
u
aliza
tio
n
f
o
r
IR
p
r
ed
ictio
n
.
Un
lik
e
p
r
ev
io
u
s
s
tu
d
ies
th
at
f
o
cu
s
o
n
is
o
lated
s
p
atial
o
r
s
ec
to
r
al
an
aly
s
es,
th
is
r
esear
ch
p
r
o
v
id
es
a
co
m
p
r
eh
en
s
iv
e
an
d
s
ca
lab
le
f
r
am
ew
o
r
k
t
ailo
r
ed
to
r
e
g
io
n
al
in
v
estme
n
t
ass
es
s
m
en
t.
Ho
wev
er
,
g
iv
e
n
th
e
lim
ited
s
am
p
le
s
ize
o
f
1
5
ad
m
in
is
tr
ativ
e
r
eg
io
n
s
u
s
ed
in
th
is
s
tu
d
y
,
th
e
p
r
o
p
o
s
ed
f
r
a
m
ewo
r
k
s
h
o
u
l
d
b
e
r
e
g
ar
d
e
d
as
a
p
r
o
o
f
-
of
-
co
n
ce
p
t
th
at
d
em
o
n
s
tr
ates
m
eth
o
d
o
lo
g
ical
f
ea
s
ib
ilit
y
r
ath
er
th
an
a
f
u
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le
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el;
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ad
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er
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d
m
o
r
e
d
iv
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r
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d
atasets
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em
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s
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ec
ess
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.
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h
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p
r
o
p
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ed
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y
s
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co
n
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ib
u
tes
to
th
e
ad
v
an
ce
m
e
n
t
o
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g
eo
s
p
atial
ar
t
if
icial
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tellig
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ce
b
y
d
em
o
n
s
tr
atin
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h
o
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RF
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ased
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tellig
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tem
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ca
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u
p
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o
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tr
ateg
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r
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le
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t d
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ak
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r
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2.
MET
H
O
D
T
h
is
r
esear
ch
ap
p
lies
a
g
eo
s
p
atial
-
b
ased
in
tellig
en
t
s
y
s
tem
f
r
am
ewo
r
k
to
p
r
e
d
ict
r
e
g
io
n
al
IR
u
s
in
g
RF
class
if
icatio
n
.
T
h
e
m
eth
o
d
o
lo
g
ical
p
r
o
ce
s
s
is
co
n
d
u
cte
d
ch
r
o
n
o
l
o
g
ically
,
e
n
s
u
r
in
g
s
cien
tifi
c
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
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SS
N:
2502
-
4
7
5
2
Geo
s
p
a
tia
l d
a
ta
p
r
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s
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d
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d
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est
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tem
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r
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Yu
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h
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a
h
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u
g
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o
h
o
)
653
r
ep
r
o
d
u
cib
ilit
y
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d
co
n
s
is
ten
cy
with
p
r
i
o
r
g
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s
p
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ML
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tu
d
ies
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2
]
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[
1
0
]
,
[
1
4
]
,
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2
2
]
-
[
2
4
]
.
T
h
e
o
v
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all
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k
f
lo
w
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in
Fig
u
r
e
1
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Fig
u
r
e
1
.
R
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r
k
f
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T
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tem
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d
ML
to
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o
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el
s
p
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atter
n
s
in
f
lu
en
cin
g
r
eg
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n
al
IR
.
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h
e
r
esear
ch
f
r
am
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r
k
co
n
s
is
ts
o
f
f
o
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r
s
eq
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en
tial
p
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ases
:
(
i
)
d
a
ta
ac
q
u
is
itio
n
,
(
ii
)
g
eo
s
p
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p
r
ep
r
o
ce
s
s
in
g
an
d
f
ea
tu
r
e
en
g
in
ee
r
in
g
,
(
iii
)
RF
m
o
d
elin
g
,
an
d
(
iv
)
v
alid
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n
an
d
p
er
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o
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m
a
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ce
ev
alu
ati
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n
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et
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d
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ata
ac
q
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is
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T
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d
ataset
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m
p
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ltis
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eo
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d
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o
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ic
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ata
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ated
at
th
e
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eg
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n
al
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d
is
tr
ict/p
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v
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ce
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el.
Data
wer
e
co
llected
f
r
o
m
o
f
f
icial
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tatis
tical
ag
en
cies,
s
p
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o
p
en
d
ata
p
o
r
tals
,
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d
th
em
atic
GI
S d
atasets
.
T
h
e
d
ataset
ca
teg
o
r
ies ar
e
s
u
m
m
ar
ize
d
in
T
ab
le
1
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
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4
7
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2
I
n
d
o
n
esian
J
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lec
E
n
g
&
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p
Sci
,
Vo
l.
43
,
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.
2
,
Au
g
u
s
t
20
26
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1
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6
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T
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Data
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et
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elin
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I
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f
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c
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D
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t
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a
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t
A
g
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y
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t
h
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9
A
d
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1
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o
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s
(
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t
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l
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m
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v
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All
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ized
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d
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is
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ativ
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b
o
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n
d
ar
ies to
e
n
s
u
r
e
s
p
atial
co
n
s
is
ten
cy
[
4
]
,
[
2
2
]
,
[
2
5
]
.
C.
Geo
s
p
atial
p
r
ep
r
o
ce
s
s
in
g
an
d
f
ea
tu
r
e
en
g
in
ee
r
in
g
Geo
s
p
atial
p
r
ep
r
o
ce
s
s
in
g
in
cl
u
d
ed
:
i)
s
p
atial
o
v
er
lay
an
d
a
g
g
r
eg
atio
n
,
ii)
h
an
d
lin
g
m
is
s
in
g
v
alu
es
u
s
in
g
m
ed
ian
im
p
u
tatio
n
,
an
d
iii)
f
ea
tu
r
e
n
o
r
m
aliza
tio
n
u
s
in
g
m
in
–
m
a
x
s
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lin
g
.
T
h
e
m
in
–
m
a
x
n
o
r
m
aliza
tio
n
i
s
d
ef
in
ed
as:
′
=
(
−
)
/
(
−
)
(
1
)
wh
er
e
(
X)
r
e
p
r
esen
ts
th
e
o
r
ig
i
n
al
f
ea
tu
r
e
v
alu
e,
an
d
(
X′)
is
t
h
e
n
o
r
m
alize
d
v
alu
e.
C
o
r
r
elatio
n
an
al
y
s
is
an
d
f
ea
tu
r
e
im
p
o
r
tan
ce
s
cr
ee
n
in
g
wer
e
ap
p
lied
to
r
e
d
u
ce
r
ed
u
n
d
an
c
y
an
d
im
p
r
o
v
e
m
o
d
el
in
ter
p
r
etab
ilit
y
[
1
1
]
,
[
2
6
]
.
T
h
e
s
p
atial
d
is
tr
ib
u
tio
n
o
f
s
elec
ted
f
ea
tu
r
es is
v
is
u
alize
d
in
Fig
u
r
e
2
.
Fig
u
r
e
2
.
Sp
atial
d
is
tr
ib
u
tio
n
o
f
s
elec
ted
s
o
cio
ec
o
n
o
m
ic
an
d
i
n
f
r
astru
ctu
r
e
i
n
d
icato
r
s
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
Geo
s
p
a
tia
l d
a
ta
p
r
o
ce
s
s
in
g
a
n
d
r
a
n
d
o
m
f
o
r
est
-
b
a
s
ed
in
tellig
en
t sys
tem
fo
r
… (
Yu
d
h
in
a
n
to
C
a
h
yo
N
u
g
r
o
h
o
)
655
D.
RF
-
b
ased
m
o
d
elin
g
RF
is
an
en
s
em
b
le
lear
n
in
g
m
eth
o
d
th
at
co
n
s
tr
u
cts
m
u
ltip
le
d
ec
is
io
n
tr
ee
s
u
s
in
g
b
o
o
ts
tr
ap
s
am
p
lin
g
an
d
r
an
d
o
m
f
ea
tu
r
e
s
elec
tio
n
.
T
h
e
f
in
al
p
r
ed
ictio
n
is
d
eter
m
in
ed
th
r
o
u
g
h
m
ajo
r
ity
v
o
tin
g
[
2
]
,
[
1
0
]
.
T
h
e
Gin
i I
n
d
ex
,
u
s
ed
to
s
p
lit n
o
d
es in
ea
ch
d
ec
is
io
n
tr
ee
,
is
f
o
r
m
u
lated
as:
=
1
−
ᵢ
₌₁ⁿ
ᵢ
²
(
2
)
wh
er
e
(
p
ᵢ
)
d
e
n
o
tes th
e
p
r
o
b
ab
i
lity
o
f
class
(
i)
.
T
h
e
m
o
d
elin
g
p
r
o
ce
d
u
r
e
is
illu
s
tr
ated
in
Fig
u
r
e
3
.
T
h
e
RF
h
y
p
er
p
ar
am
eter
s
u
s
ed
i
n
th
e
ex
p
er
im
e
n
t
ar
e
p
r
esen
ted
in
T
a
b
le
2
.
Fig
u
r
e
3
.
RF
-
b
ased
IR
p
r
e
d
ictio
n
(
f
lo
wc
h
ar
t)
T
ab
le
2
.
RF
h
y
p
e
r
p
ar
am
eter
s
No
H
y
p
e
r
p
a
r
a
me
t
e
r
V
a
l
u
e
D
e
scri
p
t
i
o
n
1
n
_
e
st
i
ma
t
o
r
s
1
0
0
N
u
mb
e
r
o
f
d
e
c
i
si
o
n
t
r
e
e
s
i
n
t
h
e
f
o
r
e
s
t
2
c
r
i
t
e
r
i
o
n
G
i
n
i
i
n
d
e
x
S
p
l
i
t
t
i
n
g
c
r
i
t
e
r
i
o
n
u
se
d
t
o
me
a
su
r
e
n
o
d
e
i
m
p
u
r
i
t
y
3
max
_
d
e
p
t
h
10
M
a
x
i
m
u
m
d
e
p
t
h
o
f
e
a
c
h
d
e
c
i
si
o
n
t
r
e
e
,
l
i
mi
t
i
n
g
o
v
e
r
f
i
t
t
i
n
g
o
n
s
mal
l
s
a
m
p
l
e
s
4
mi
n
_
sa
mp
l
e
s
_
s
p
l
i
t
2
M
i
n
i
m
u
m
n
u
m
b
e
r
o
f
s
a
mp
l
e
s
r
e
q
u
i
r
e
d
t
o
sp
l
i
t
a
n
i
n
t
e
r
n
a
l
n
o
d
e
5
mi
n
_
sa
mp
l
e
s
_
l
e
a
f
1
M
i
n
i
m
u
m
n
u
m
b
e
r
o
f
s
a
mp
l
e
s
r
e
q
u
i
r
e
d
t
o
b
e
a
t
a
l
e
a
f
n
o
d
e
6
max
_
f
e
a
t
u
r
e
s
sq
r
t
N
u
mb
e
r
o
f
f
e
a
t
u
r
e
s c
o
n
si
d
e
r
e
d
w
h
e
n
l
o
o
k
i
n
g
f
o
r
t
h
e
b
e
st
sp
l
i
t
7
b
o
o
t
st
r
a
p
Tr
u
e
W
h
e
t
h
e
r
b
o
o
t
s
t
r
a
p
sa
mp
l
e
s
a
r
e
u
s
e
d
w
h
e
n
b
u
i
l
d
i
n
g
t
r
e
e
s
8
r
a
n
d
o
m
_
s
t
a
t
e
42
S
e
e
d
v
a
l
u
e
t
o
e
n
s
u
r
e
r
e
p
r
o
d
u
c
i
b
i
l
i
t
y
o
f
r
e
su
l
t
s
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
43
,
No
.
2
,
Au
g
u
s
t
20
26
:
65
1
-
6
6
1
656
E.
Mo
d
el
ev
alu
atio
n
an
d
v
alid
ati
o
n
Mo
d
el
p
er
f
o
r
m
an
ce
was
ev
alu
ated
u
s
in
g
wid
ely
ac
ce
p
ted
cl
ass
if
icatio
n
m
etr
ics:
ac
cu
r
ac
y
,
p
r
ec
is
io
n
,
r
ec
all,
an
d
F1
-
s
co
r
e,
d
ef
i
n
ed
a
s
f
o
llo
ws:
=
(
+
)
/
(
+
+
+
)
(
3
)
=
/
(
+
)
(
4
)
=
/
(
+
)
(
5
)
1
=
2
×
(
×
)
/
(
+
)
(
6
)
wh
er
e
(
T
P),
(
T
N)
,
(
FP
)
,
a
n
d
(
FN)
r
ep
r
esen
t
tr
u
e
p
o
s
itiv
es,
tr
u
e
n
e
g
ativ
es,
f
alse
p
o
s
itiv
es,
an
d
f
alse
n
e
g
ativ
es,
r
esp
ec
tiv
ely
[
1
4
]
,
[
2
1
]
,
[
2
7
]
.
Giv
en
th
e
lim
ited
s
am
p
le
s
ize
o
f
1
5
ad
m
in
is
tr
ativ
e
r
e
g
io
n
s
,
m
o
d
el
p
er
f
o
r
m
a
n
ce
was a
s
s
ess
ed
u
s
in
g
leav
e
-
one
-
o
u
t c
r
o
s
s
-
v
alid
atio
n
(
L
OOCV)
,
in
wh
ich
ea
ch
r
eg
i
o
n
was iter
ativ
ely
h
eld
o
u
t a
s
th
e
test
in
s
tan
ce
wh
ile
th
e
RF
m
o
d
el
was
tr
ain
ed
o
n
th
e
r
e
m
ain
in
g
1
4
r
eg
io
n
s
.
T
h
is
p
r
o
c
ess
wa
s
r
ep
ea
ted
f
o
r
all
1
5
r
eg
io
n
s
,
an
d
th
e
ag
g
r
e
g
ated
p
r
ed
ictio
n
s
wer
e
u
s
ed
to
co
m
p
u
te
th
e
class
if
icatio
n
m
etr
ics
in
(
3
)
–
(
6
)
.
L
OOCV
was
s
elec
ted
o
v
er
a
co
n
v
en
tio
n
al
tr
ain
-
test
s
p
lit
to
m
ax
im
ize
th
e
u
s
e
o
f
th
e
lim
i
ted
av
ailab
le
d
ata
an
d
to
r
ed
u
ce
v
ar
ia
n
ce
in
p
er
f
o
r
m
an
ce
esti
m
atio
n
[
1
9
]
,
[
2
0
]
.
T
h
e
co
n
f
u
s
io
n
m
atr
ix
v
is
u
aliza
tio
n
an
d
class
if
icatio
n
p
er
f
o
r
m
an
ce
co
m
p
ar
is
o
n
ar
e
p
r
esen
ted
in
Fig
u
r
e
4
.
Fig
u
r
e
4
.
C
o
n
f
u
s
io
n
m
atr
i
x
an
d
p
er
f
o
r
m
an
ce
ev
alu
atio
n
o
f
RF
m
o
d
el
F.
Vis
u
al
an
aly
s
is
an
d
o
u
tp
u
t in
t
er
p
r
etatio
n
T
h
e
f
in
al
IR
r
esu
lts
wer
e
v
is
u
alize
d
as
th
em
atic
g
eo
s
p
atial
m
ap
s
,
en
ab
lin
g
in
tu
itiv
e
in
ter
p
r
etatio
n
o
f
r
eg
io
n
al
in
v
estme
n
t
p
o
ten
tial.
Ad
d
itio
n
ally
,
f
ea
t
u
r
e
im
p
o
r
ta
n
ce
s
co
r
es
wer
e
p
lo
tted
as
b
a
r
ch
ar
ts
to
id
en
tif
y
d
o
m
in
an
t i
n
d
icato
r
s
in
f
lu
e
n
cin
g
m
o
d
el
p
r
ed
ictio
n
s
.
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
T
h
is
s
ec
tio
n
p
r
esen
ts
th
e
e
x
p
er
im
en
tal
r
esu
lts
o
b
tain
ed
f
r
o
m
th
e
p
r
o
p
o
s
ed
g
eo
s
p
a
tial
-
b
ased
in
tellig
en
t
s
y
s
tem
an
d
p
r
o
v
id
es
a
co
m
p
r
eh
en
s
iv
e
d
is
cu
s
s
io
n
o
f
r
eg
io
n
al
IR
p
r
ed
ictio
n
.
T
h
e
r
esu
lts
ar
e
ex
p
r
ess
ed
th
r
o
u
g
h
tab
u
lar
s
u
m
m
ar
ies,
m
at
h
em
atica
l
f
o
r
m
u
latio
n
s
,
an
d
s
p
atial
v
is
u
aliza
tio
n
s
,
allo
win
g
o
b
jectiv
e
in
ter
p
r
etatio
n
an
d
p
o
licy
-
r
elev
an
t in
s
ig
h
ts
.
3
.
1
.
Da
t
a
s
et
s
um
ma
ry
a
nd
f
ea
t
ure
s
t
a
t
is
t
ics
T
h
e
p
r
o
ce
s
s
ed
d
ataset
co
n
s
is
ts
o
f
1
5
ad
m
in
is
tr
ativ
e
r
eg
io
n
s
in
L
am
p
u
n
g
Pro
v
in
ce
.
E
ac
h
r
eg
io
n
is
r
ep
r
esen
ted
b
y
a
m
u
ltid
im
en
s
io
n
al
f
ea
tu
r
e
v
ec
to
r
co
m
b
i
n
in
g
s
o
cio
ec
o
n
o
m
ic,
i
n
f
r
astru
ctu
r
e
,
ac
ce
s
s
ib
ilit
y
,
an
d
d
is
aster
-
r
is
k
v
ar
iab
les.
T
ab
le
3
s
u
m
m
ar
izes
th
e
k
e
y
p
r
o
ce
s
s
ed
v
ar
iab
les
u
s
ed
in
t
h
is
s
tu
d
y
,
in
clu
d
in
g
t
h
eir
v
alu
e
r
an
g
es a
n
d
d
escr
ip
tiv
e
s
tatis
tics
,
p
r
io
r
to
n
o
r
m
aliza
tio
n
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
Geo
s
p
a
tia
l d
a
ta
p
r
o
ce
s
s
in
g
a
n
d
r
a
n
d
o
m
f
o
r
est
-
b
a
s
ed
in
tellig
en
t sys
tem
fo
r
… (
Yu
d
h
in
a
n
to
C
a
h
yo
N
u
g
r
o
h
o
)
657
T
ab
le
3
.
Su
m
m
a
r
y
o
f
k
e
y
p
r
o
c
ess
ed
v
ar
iab
les
No
V
a
r
i
a
b
l
e
U
n
i
t
/
sc
a
l
e
M
i
n
M
a
x
M
e
a
n
S
t
d
.
D
e
v
.
1
U
r
b
a
n
i
z
a
t
i
o
n
I
n
d
e
x
(
U
)
0
–
1
(
n
o
r
m
a
l
i
z
e
d
)
0
.
1
2
0
.
9
4
0
.
4
8
0
.
2
7
2
R
o
a
d
a
c
c
e
ss
i
b
i
l
i
t
y
(
R
)
0
–
1
(
n
o
r
m
a
l
i
z
e
d
)
0
.
2
0
0
.
9
1
0
.
5
5
0
.
2
2
3
D
i
st
a
n
c
e
t
o
p
o
r
t
,
i
n
v
e
r
se
(
P
)
0
–
1
(
n
o
r
m
a
l
i
z
e
d
)
0
.
0
8
0
.
8
7
0
.
4
1
0
.
2
5
4
D
i
st
a
n
c
e
t
o
A
i
r
p
o
r
t
,
i
n
v
e
r
se
(
A
)
0
–
1
(
n
o
r
m
a
l
i
z
e
d
)
0
.
1
0
0
.
8
5
0
.
4
4
0
.
2
3
5
H
e
a
l
t
h
c
a
r
e
f
a
c
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d
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t
h
e
I
R
f
o
rm
u
l
a
t
i
o
n
i
n
(
7
)
.
I
n
ter
p
r
etatio
n
:
t
h
e
wid
e
r
a
n
g
e
o
f
I
R
v
alu
es
co
n
f
i
r
m
s
s
ig
n
if
i
ca
n
t
s
p
atial
h
eter
o
g
en
eity
in
r
eg
io
n
al
r
ea
d
in
ess
.
R
eg
io
n
s
with
h
ig
h
u
r
b
an
izatio
n
,
I
PM,
an
d
in
f
r
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ctu
r
e
d
e
n
s
ity
co
n
s
is
ten
tly
ac
h
iev
e
h
ig
h
e
r
I
R
s
co
r
es.
3
.
2
.
I
R
ma
t
hema
t
ica
l f
o
rm
u
la
t
io
n
T
h
e
IR
s
co
r
e
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o
m
p
u
te
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s
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g
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weig
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ted
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ir
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ased
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ev
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s
g
eo
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in
v
estme
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s
tu
d
ies.
3
.
3
.
Sp
a
t
ia
l
dis
t
ributio
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f
IR
Fig
u
r
e
5
p
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th
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ased
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R
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m
m
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ab
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4
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Fi
g
u
r
e
5
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Sp
atial
d
is
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tio
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f
IR
ac
r
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s
s
L
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Pro
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
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I
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J
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Vo
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,
No
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2
,
Au
g
u
s
t
20
26
:
65
1
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6
1
658
T
ab
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4
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k
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l
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k
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R
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o
n
g
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r
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ctu
r
e,
ac
ce
s
s
ib
ilit
y
,
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d
h
u
m
an
c
ap
ital.
Per
ip
h
er
al
r
eg
io
n
s
with
lim
ited
ac
ce
s
s
an
d
h
ig
h
er
d
is
aster
ex
p
o
s
u
r
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ex
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b
it
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R
v
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t
s
h
o
u
ld
b
e
n
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ted
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at
th
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s
ix
-
class
s
ch
em
e
in
T
ab
le
4
s
er
v
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a
d
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tiv
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p
o
licy
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o
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te
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class
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s
e
d
f
o
r
d
ash
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v
is
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d
s
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l
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er
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m
m
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n
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.
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lim
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p
le
s
ize
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,
t
h
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f
in
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g
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ain
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d
s
ch
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s
ed
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e
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lab
el
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class
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ier
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ated
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Hig
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el
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u
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etailed
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ec
tio
n
3
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4
.
3
.
4
.
I
nte
llig
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mo
del pre
dic
t
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n a
nd
perf
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rm
a
nce
I
n
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h
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n
g
40
M
e
d
i
u
m
Lo
w
0
.
6
4
No
B
a
n
d
a
r
La
mp
u
n
g
72
H
i
g
h
H
i
g
h
0
.
9
1
Y
e
s
La
mp
u
n
g
S
e
l
a
t
a
n
1
0
0
H
i
g
h
H
i
g
h
0
.
8
7
Y
e
s
La
mp
u
n
g
Te
n
g
a
h
71
H
i
g
h
H
i
g
h
0
.
9
4
Y
e
s
La
mp
u
n
g
T
i
mu
r
93
H
i
g
h
M
e
d
i
u
m
0
.
7
2
No
N
o
t
e
:
T
h
e
p
re
c
i
s
e
b
o
u
n
d
a
ry
b
e
t
w
e
e
n
Me
d
i
u
m
a
n
d
H
i
g
h
f
o
r
t
h
e
M
o
d
e
r
a
t
e
l
y
Fe
a
si
b
l
e
r
a
n
g
e
(
I
R
5
0
–
6
4
)
w
a
s
n
o
t
d
i
r
e
c
t
l
y
o
b
ser
v
e
d
i
n
t
h
e
s
a
m
p
l
e
d
r
e
g
i
o
n
s
i
n
T
a
b
l
e
5
,
a
n
d
f
u
t
u
re
w
o
r
k
w
i
t
h
a
l
a
rg
e
r s
a
m
p
l
e
i
s
n
e
e
d
e
d
t
o
f
u
rt
h
e
r
v
a
l
i
d
a
t
e
t
h
i
s
a
g
g
re
g
a
t
i
o
n
s
c
h
e
m
e
.
3
.
5
.
Dis
cus
s
io
n
T
h
e
co
m
b
i
n
ed
tab
u
lar
,
m
ath
e
m
atica
l,
an
d
s
p
atial
an
aly
s
es
co
n
f
ir
m
t
h
at
IR
is
a
m
u
ltid
im
en
s
io
n
al
g
eo
s
p
atial
p
h
en
o
m
en
o
n
.
T
h
e
r
esu
lts
in
d
icate
th
at
r
eg
io
n
s
wit
h
h
ig
h
I
R
s
co
r
es
co
n
s
is
ten
tly
alig
n
with
s
tr
o
n
g
e
r
in
v
estme
n
t
p
r
ed
ictio
n
s
,
v
alid
atin
g
th
e
p
r
o
p
o
s
ed
f
r
a
m
ewo
r
k
.
Fu
r
th
er
m
o
r
e,
th
e
W
eb
-
G
I
S
im
p
lem
en
tatio
n
en
h
an
ce
s
in
ter
p
r
etab
ilit
y
b
y
a
llo
win
g
u
s
er
s
to
ex
p
l
o
r
e
d
atas
et
attr
ib
u
tes,
m
o
d
el
o
u
tp
u
ts
,
a
n
d
s
p
atial
p
atter
n
s
s
im
u
ltan
eo
u
s
ly
.
T
h
is
a
p
p
r
o
a
c
h
b
r
i
d
g
es
th
e
g
ap
b
etwe
en
a
d
v
an
ce
d
ML
m
o
d
els
an
d
p
r
a
cti
ca
l
d
ec
is
io
n
-
m
ak
i
n
g
en
v
ir
o
n
m
en
ts
.
4.
CO
NCLU
SI
O
N
T
h
is
s
tu
d
y
h
as
d
e
v
elo
p
e
d
a
g
e
o
s
p
atial
-
b
ased
in
tellig
en
t
s
y
s
tem
u
tili
zin
g
th
e
RF
alg
o
r
ith
m
to
p
r
e
d
ict
r
eg
io
n
al
IR
in
I
n
d
o
n
esia.
I
n
al
ig
n
m
en
t
with
th
e
o
b
jectiv
es
s
tated
in
th
e
I
n
t
r
o
d
u
ctio
n
,
t
h
e
p
r
o
p
o
s
ed
f
r
am
ewo
r
k
in
teg
r
ates
m
u
ltis
o
u
r
ce
g
e
o
s
p
atial,
s
o
cio
ec
o
n
o
m
ic,
in
f
r
astr
u
ctu
r
e,
a
n
d
ac
ce
s
s
ib
ilit
y
d
ata
to
g
en
e
r
ate
an
IR
s
co
r
e.
T
h
e
e
x
p
er
im
e
n
tal
r
esu
lts
d
em
o
n
s
tr
ate
th
at
t
h
e
R
F
m
o
d
el
is
ca
p
ab
le
o
f
ca
p
tu
r
in
g
n
o
n
lin
ea
r
r
elatio
n
s
h
ip
s
am
o
n
g
s
p
atial
an
d
n
o
n
-
s
p
ati
al
v
ar
iab
les,
y
ield
in
g
p
r
o
m
is
in
g
class
if
icatio
n
p
e
r
f
o
r
m
an
c
e
an
d
m
ea
n
i
n
g
f
u
l
r
eg
io
n
al
d
if
f
er
e
n
tiatio
n
.
T
h
e
f
i
n
d
in
g
s
r
e
v
ea
l
th
at
r
eg
io
n
s
wit
h
h
ig
h
er
u
r
b
an
izatio
n
lev
els,
b
e
tter
in
f
r
astru
ctu
r
e
ac
ce
s
s
ib
ilit
y
,
lo
wer
p
o
v
er
ty
r
a
tes,
an
d
p
r
o
x
im
ity
to
s
tr
ateg
ic
f
ac
ilit
ies
s
u
ch
as
p
o
r
ts
an
d
i
n
d
u
s
tr
ial
zo
n
es
te
n
d
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
Geo
s
p
a
tia
l d
a
ta
p
r
o
ce
s
s
in
g
a
n
d
r
a
n
d
o
m
f
o
r
est
-
b
a
s
ed
in
tellig
en
t sys
tem
fo
r
… (
Yu
d
h
in
a
n
to
C
a
h
yo
N
u
g
r
o
h
o
)
659
to
ex
h
ib
it
h
i
g
h
er
IR
.
C
o
n
v
er
s
ely
,
r
eg
io
n
s
with
lim
ited
in
f
r
astru
ctu
r
e
a
n
d
h
ig
h
er
c
o
m
p
o
s
ite
d
is
aster
r
is
k
s
co
r
es
s
h
o
w
r
elat
iv
ely
lo
wer
in
v
estme
n
t
p
o
ten
tial.
T
h
e
co
n
f
u
s
io
n
m
atr
ix
an
d
p
e
r
f
o
r
m
an
ce
ev
alu
atio
n
in
d
icate
co
n
s
is
ten
t p
r
ed
ictiv
e
b
eh
a
v
io
r
o
f
th
e
R
F
-
b
ased
ap
p
r
o
ac
h
f
o
r
th
is
d
ataset.
T
h
ese
f
in
d
in
g
s
s
h
o
u
ld
n
o
n
et
h
eless
b
e
in
ter
p
r
eted
with
c
au
tio
n
g
iv
e
n
s
ev
er
al
lim
itatio
n
s
o
f
th
e
p
r
esen
t
s
tu
d
y
.
First,
th
e
an
aly
s
is
r
elie
s
o
n
a
s
m
all
s
am
p
le
o
f
o
n
ly
1
5
ad
m
in
is
tr
ativ
e
r
eg
io
n
s
,
wh
ich
co
n
s
tr
ain
s
th
e
s
tatis
tical
p
o
wer
o
f
th
e
m
o
d
el
a
n
d
i
n
cr
ea
s
es
th
e
r
is
k
o
f
o
v
e
r
f
itti
n
g
;
th
e
leav
e
-
one
-
o
u
t
c
r
o
s
s
-
v
alid
atio
n
s
tr
ateg
y
u
s
ed
h
er
e
m
itig
ates
b
u
t
d
o
es
n
o
t
elim
in
ate
th
is
co
n
ce
r
n
.
Seco
n
d
,
b
ec
au
s
e
all
1
5
r
eg
io
n
s
ar
e
lo
ca
ted
with
in
a
s
in
g
le
p
r
o
v
in
ce
,
p
o
t
en
tial
s
p
atial
au
to
co
r
r
elatio
n
an
d
clu
s
ter
in
g
e
f
f
ec
ts
wer
e
n
o
t
f
o
r
m
ally
test
ed
(
e.
g
.
,
v
ia
Mo
r
a
n
'
s
I
o
r
L
I
SA)
,
s
o
th
e
ex
ten
t
o
f
s
p
atial
b
ias
i
n
th
e
r
esu
lts
r
em
ain
s
u
n
q
u
a
n
t
if
ied
.
T
h
ir
d
,
th
e
IR
s
co
r
e
u
s
ed
as
th
e
class
if
icatio
n
tar
g
et
was
d
er
i
v
ed
f
r
o
m
a
s
u
b
jectiv
ely
weig
h
ted
c
o
m
p
o
s
ite
f
o
r
m
u
la
r
at
h
er
th
an
an
in
d
ep
en
d
en
t,
em
p
ir
ic
ally
v
alid
ated
g
r
o
u
n
d
tr
u
th
,
m
ea
n
in
g
th
e
R
F
m
o
d
el'
s
p
er
f
o
r
m
an
ce
r
ef
lects
its
ab
ilit
y
to
r
ep
r
o
d
u
ce
th
is
f
o
r
m
u
la
r
ath
e
r
t
h
an
an
ex
ter
n
a
l
in
v
estme
n
t
o
u
tco
m
e
.
As
s
u
ch
,
t
h
e
p
r
o
p
o
s
ed
f
r
am
ewo
r
k
s
h
o
u
ld
b
e
r
eg
ar
d
e
d
as a
p
r
o
o
f
-
of
-
co
n
ce
p
t f
o
r
in
teg
r
atin
g
g
e
o
s
p
atial
d
ata
with
en
s
em
b
le
ML
,
r
ath
er
th
an
a
f
u
lly
v
alid
ated
,
g
en
er
ali
za
b
le
in
v
estme
n
t
-
r
ea
d
in
ess
p
r
ed
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r
.
Fro
m
a
p
r
ac
tical
p
er
s
p
ec
tiv
e,
th
e
p
r
o
p
o
s
ed
s
y
s
tem
ca
n
s
er
v
e
as
a
p
r
elim
in
ar
y
d
ec
is
io
n
-
s
u
p
p
o
r
t
to
o
l
f
o
r
p
o
licy
m
a
k
er
s
an
d
i
n
v
esto
r
s
in
p
r
io
r
itizin
g
r
e
g
io
n
s
f
o
r
f
u
r
th
er
,
m
o
r
e
d
etailed
in
v
e
s
tm
en
t
ass
ess
m
en
t.
Fu
tu
r
e
r
esear
ch
s
h
o
u
ld
e
x
ten
d
th
is
wo
r
k
b
y
v
alid
atin
g
th
e
f
r
am
ewo
r
k
o
n
lar
g
er
an
d
m
o
r
e
g
eo
g
r
ap
h
ically
d
iv
er
s
e
d
atasets
s
p
an
n
in
g
m
u
ltip
le
p
r
o
v
i
n
ce
s
,
f
o
r
m
ally
t
esti
n
g
f
o
r
s
p
atial
au
to
c
o
r
r
ela
tio
n
,
b
en
c
h
m
ar
k
i
n
g
ag
ain
s
t
alter
n
ativ
e
class
if
ier
s
(
e.
g
.
,
lo
g
is
tic
r
eg
r
ess
io
n
(
L
R
)
,
s
u
p
p
o
r
t
v
ec
to
r
m
ac
h
in
es
(
S
VM
)
,
an
d
ex
tr
e
m
e
g
r
ad
ien
t b
o
o
s
tin
g
(
XGBo
o
s
t)
)
,
an
d
in
co
r
p
o
r
atin
g
tem
p
o
r
al
d
y
n
am
ics,
d
ee
p
lear
n
in
g
-
b
ased
s
p
atial
m
o
d
els,
an
d
r
ea
l
-
tim
e
r
em
o
te
s
en
s
in
g
d
a
ta
to
f
u
r
th
er
en
h
an
ce
p
r
e
d
ictio
n
ac
cu
r
ac
y
an
d
s
ca
lab
ilit
y
ac
r
o
s
s
b
r
o
ad
e
r
g
eo
g
r
a
p
h
ic
co
n
tex
ts
.
ACK
NO
WL
E
DG
M
E
N
T
S
T
h
e
au
th
o
r
s
wo
u
ld
lik
e
to
e
x
p
r
ess
th
eir
s
in
ce
r
e
ap
p
r
ec
iatio
n
to
th
e
n
atio
n
al
s
tatis
tical
an
d
g
eo
s
p
atial
ag
en
cies
f
o
r
p
r
o
v
i
d
in
g
o
p
en
-
a
cc
ess
s
o
cio
ec
o
n
o
m
ic
an
d
s
p
ati
al
d
atasets
th
at
s
u
p
p
o
r
ted
th
is
r
esear
ch
.
Gr
atitu
d
e
is
also
ex
ten
d
ed
to
co
lle
ag
u
es
an
d
r
esear
ch
ass
is
tan
ts
w
h
o
co
n
tr
i
b
u
ted
to
d
ata
p
r
ep
r
o
ce
s
s
in
g
,
g
eo
s
p
atial
an
aly
s
is
,
an
d
m
o
d
el
v
alid
atio
n
.
All
in
d
iv
id
u
als
ac
k
n
o
wled
g
ed
h
av
e
p
r
o
v
id
ed
th
ei
r
co
n
s
e
n
t
to
b
e
in
cl
u
d
ed
i
n
th
is
s
ec
tio
n
.
F
UNDING
I
NF
O
R
M
A
T
I
O
N
T
h
is
r
esear
ch
was
f
u
n
d
ed
b
y
th
e
M
in
is
tr
y
o
f
E
d
u
ca
tio
n
,
C
u
ltu
r
e,
R
esear
ch
,
an
d
T
ec
h
n
o
l
o
g
y
o
f
th
e
R
ep
u
b
lic
o
f
I
n
d
o
n
esia
(
K
eme
n
d
iksa
in
tek
)
u
n
d
er
r
esear
ch
g
r
an
t/co
n
tr
ac
t
No
.
1
5
5
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2
/DT
.
0
5
.
0
0
/PL/2
0
2
5
(
2
J
u
n
e
2
0
2
5
)
an
d
C
o
n
tr
ac
t
No
.
S.2
4
/0
3
4
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0
2
5
(
1
5
J
u
ly
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T.
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Z.
Ta
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[
6
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L.
B
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