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ee
d
en
s
ity
,
ca
n
o
p
y
d
im
en
s
io
n
,
b
a
s
al
ar
ea
,
an
d
p
r
o
f
ile
o
f
v
er
tica
l
ca
n
o
p
y
,
wh
ich
ar
e
r
eq
u
ir
e
d
f
o
r
th
e
m
o
d
elin
g
an
en
v
ir
o
n
m
en
t
[
1
4
]
.
Po
p
escu
et
a
l.
[
1
5
]
d
is
co
v
er
ed
th
e
s
tr
o
n
g
r
elatio
n
s
h
ip
b
etwe
en
th
e
f
ield
m
ea
s
u
r
em
en
t
d
ata
(
ca
n
o
p
y
co
v
er
)
an
d
p
o
in
t
d
e
n
s
ity
u
s
in
g
th
is
tech
n
o
lo
g
y
.
M
o
r
eo
v
e
r
,
th
e
esti
m
atio
n
ac
cu
r
a
cy
o
f
ab
o
v
e
g
r
o
u
n
d
b
io
m
ass
in
cr
ea
s
es
s
im
u
ltan
eo
u
s
ly
with
th
e
in
cr
ea
s
e
in
p
o
in
t
d
en
s
ity
[
1
6
]
.
As
s
tated
ea
r
li
er
o
n
,
L
iDAR
p
o
in
t
clo
u
d
d
ata,
wh
ich
h
as
h
ig
h
r
eso
lu
tio
n
is
ca
p
ab
le
o
f
est
im
atin
g
th
e
ab
o
v
e
g
r
o
u
n
d
b
io
m
ass
(
AGB)
,
by
im
p
lem
en
tin
g
al
l
o
m
etr
ic
r
elati
o
n
s
h
ip
s
o
f
h
eig
h
t
p
o
in
t
d
e
n
s
ity
an
d
ca
r
b
o
n
s
to
ck
d
ata
f
r
o
m
th
e
f
ield
s
am
p
le
[
1
7
]
.
Fu
r
th
er
m
o
r
e
,
W
an
-
Mo
h
d
-
J
aa
f
ar
et
a
l.
[
1
8
]
d
ev
elo
p
e
d
th
e
r
ela
tio
n
s
h
ip
b
etwe
en
h
eig
h
t
an
d
w
id
th
d
ata
o
n
ca
n
o
p
y
an
d
it wa
s
v
alid
ated
with
th
e
f
ield
d
ata.
T
h
er
ef
o
r
e
,
it c
an
p
r
ed
ict
th
e
ab
o
v
e
g
r
o
u
n
d
b
i
o
m
ass
in
tr
o
p
ical
f
o
r
ests
.
T
h
is
r
elatio
n
s
h
ip
co
u
ld
also
b
e
u
s
ed
to
ass
ess
ca
r
b
o
n
s
to
ck
[
1
9
,
20
]
.
T
h
is
r
esear
ch
was
co
n
d
u
cte
d
to
s
tu
d
y
L
iDAR
tech
n
o
lo
g
y
,
wh
ich
ca
n
p
r
o
v
id
e
co
m
p
lete,
f
ast,
a
n
d
ac
cu
r
ate
d
ata,
an
d
wh
en
co
m
b
in
ed
with
f
ield
d
ata
ca
n
b
e
u
s
ed
f
o
r
p
la
n
n
in
g
,
m
an
ag
in
g
,
an
d
m
o
n
ito
r
i
n
g
p
ea
tlan
d
ec
o
s
y
s
tem
s
.
I
n
ad
d
itio
n
,
it a
ls
o
aim
s
to
est
im
ate
th
e
ab
o
v
e
g
r
o
u
n
d
b
io
m
ass
(
A
GB
)
m
o
d
el
u
s
in
g
L
iDAR
d
ata
.
2.
RE
S
E
ARCH
M
E
T
H
O
D
2
.
1
.
L
o
ca
t
io
n a
nd
t
im
e
Field
m
ea
s
u
r
em
en
t
was
co
n
d
u
cted
in
t
h
e
r
esto
r
atio
n
ar
ea
o
f
th
e
p
ea
tlan
d
ec
o
s
y
s
tem
in
PT.
R
im
b
a
Ma
k
m
u
r
Utam
a,
wh
ich
is
a
d
m
in
is
tr
ativ
ely
lo
ca
ted
i
n
E
ast
W
ar
in
g
in
R
eg
en
cy
o
f
C
en
tr
al
Kalim
an
tan
a
s
s
h
o
wn
in
Fig
u
r
e
1
an
d
h
as
a
I
UPHHK
-
R
E
ar
ea
o
f
2
1
7
.
7
5
5
h
a.
Data
was
co
llected
b
etwe
en
J
u
ly
-
Au
g
u
s
t
201
8
.
A
n
d
wer
e
an
aly
ze
d
in
th
e
Sp
atial
An
aly
s
is
an
d
Mo
d
e
lin
g
L
ab
o
r
ato
r
y
,
Dep
a
r
tm
en
t
o
f
C
o
n
s
er
v
atio
n
o
f
Fo
r
est
R
eso
u
r
ce
s
an
d
E
co
to
u
r
i
s
m
,
Facu
lty
o
f
Fo
r
estry
,
I
PB
Un
iv
er
s
ity
.
2
.
2
.
T
o
o
ls
a
nd
ma
t
er
ia
ls
T
h
e
to
o
ls
u
s
ed
wer
e
d
i
g
ital,
a
n
d
DSLR
ca
m
er
a,
f
is
h
ey
e
len
s
,
tr
ip
o
d
,
g
lo
b
al
p
o
s
itio
n
in
g
s
y
s
tem
(
GPS),
m
ac
h
ete,
p
h
ib
a
n
d
,
h
y
p
s
o
m
ete
r
,
co
m
p
ass
,
m
ea
s
u
r
in
g
ta
p
e,
a
n
d
r
o
p
es
.
W
h
ile
th
e
s
o
f
twar
e
f
o
r
m
an
a
g
in
g
a
n
d
an
aly
s
in
g
th
e
d
ata
wer
e
Ar
cG
I
S
1
0
.
3
,
R
s
tu
d
io
,
Hem
iView
2
.
1
,
an
d
Mic
r
o
s
o
f
t
ex
ce
l.
L
astl
y
,
o
th
er
m
ater
ials
u
tili
ze
d
in
clu
d
e
s
p
lo
t
p
lan
an
d
co
o
r
d
i
n
ates o
f
p
lo
t
r
ef
er
e
n
ce
o
n
GPS
an
d
tally
s
h
ee
t
.
Fig
u
r
e
1
.
R
esear
ch
lo
ca
tio
n
;
(
a)
in
C
en
tr
al
Kalim
an
tan
Pro
v
in
ce
,
(
b
)
E
ast
Ko
tawa
r
in
g
in
R
eg
en
cy
,
a
n
d
(
c)
I
UPHHK
-
R
E
PT.
R
im
b
a
Ma
k
m
u
r
Utam
a
2
.
3
.
Da
t
a
c
o
llect
io
n
L
iDAR
Po
in
t
clo
u
d
s
d
ata
a
n
d
v
eg
etatio
n
d
ata
we
r
e
th
e
b
asic
d
ata
u
s
ed
in
t
h
is
s
tu
d
y
.
T
h
e
d
ata
u
s
ed
f
o
r
f
o
r
m
u
latin
g
b
io
m
ass
esti
m
atio
n
m
o
d
el
.
E
ac
h
o
f
t
h
ese
d
ata
w
as
o
b
tain
ed
f
r
o
m
d
ir
ec
t
ac
q
u
is
itio
n
s
alth
o
u
g
h
b
y
p
r
o
ce
s
s
ed
d
ata
.
T
h
e
ty
p
es o
f
d
ata
an
d
r
esear
ch
f
lo
w
ca
n
b
e
s
ee
n
in
T
ab
le
1
an
d
Fig
u
r
e
2
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
1
6
9
3
-
6
9
3
0
T
E
L
KOM
NI
KA
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l Co
n
tr
o
l
,
Vo
l.
19
,
No
.
3
,
J
u
n
e
2
0
2
1
:
7
7
0
-
7
8
0
772
Fig
u
r
e
2
.
R
esear
ch
f
lo
w
T
ab
le
1
.
T
y
p
es o
f
d
ata
in
th
e
r
esear
ch
No
Ty
p
e
o
f
D
a
t
a
Y
e
a
r
M
e
t
h
o
d
1
Tr
e
e
D
i
a
m
e
t
e
r
a
n
d
H
e
i
g
h
t
2
0
1
8
D
i
r
e
c
t
me
a
su
r
e
me
n
t
2
P
o
i
n
t
C
l
o
u
d
(
L
i
D
A
R
)
2
0
1
8
D
i
r
e
c
t
me
a
su
r
e
me
n
t
3
Tr
e
e
c
a
n
o
p
y
p
h
o
t
o
2
0
1
8
H
e
mi
s
p
h
e
r
i
c
a
l
p
h
o
t
o
g
r
a
p
h
2
.
4
.
F
ield
da
t
a
m
e
a
s
urem
ent
Dete
r
m
in
atio
n
o
f
f
ield
s
u
r
v
e
y
to
o
b
tain
v
eg
etatio
n
an
d
L
iDA
R
d
ata
was p
er
f
o
r
m
ed
b
y
p
laci
n
g
a
p
lo
t
o
f
4
0
x
4
0
(
m
)
with
in
th
e
L
iDAR
f
lig
h
t
r
an
g
e,
wh
ic
h
is
2
x
1
(
k
m
)
or
2
0
0
h
a
,
u
s
in
g
th
e
s
y
s
tem
atic
s
am
p
lin
g
m
eth
o
d
as
s
h
o
wn
in
Fig
u
r
e
2
.
T
h
e
Ve
g
etatio
n
d
ata
co
llected
wer
e
th
e
d
iam
eter
at
b
r
ea
s
t
h
eig
h
t
(
d
b
h
)
o
f
t
h
e
tr
ee
s
with
d
iam
eter
≥
1
0
cm
,
to
tal
h
ei
g
h
t
o
f
tr
ee
,
tr
ee
s
p
ec
ies
(
co
m
m
o
n
n
am
e
a
n
d
L
atin
n
am
e)
,
p
lo
t
co
o
r
d
in
ates,
an
d
an
y
th
in
g
r
elate
d
to
g
r
o
wth
s
ites
ar
o
u
n
d
th
e
m
ea
s
u
r
em
en
t
p
l
o
ts
.
T
o
f
ac
ilit
ate
th
e
m
ea
s
u
r
e
m
en
t,
th
e
m
ain
p
l
o
t
(
4
0
x
4
0
)
was d
iv
id
e
d
in
t
o
q
u
ad
r
an
t o
f
2
0
x
2
0
(
m
)
.
C
an
o
p
y
d
e
n
s
ity
m
ea
s
u
r
em
en
t
was c
ar
r
ie
d
o
u
t a
t e
ac
h
ce
n
tr
al
p
o
in
t o
f
th
e
q
u
a
d
r
an
t,
an
d
ce
n
t
r
al
p
o
in
t
o
f
t
h
e
m
ain
p
lo
t,
th
er
ef
o
r
e,
t
h
e
to
tal
o
b
s
er
v
atio
n
p
o
i
n
t in
ea
ch
p
lo
t
was
5
p
o
in
ts
.
T
h
e
m
ea
s
u
r
em
en
ts
w
er
e
ca
r
r
ied
o
u
t
u
s
in
g
h
e
m
is
p
h
er
ical
ca
m
er
a
an
d
d
en
s
ito
m
ete
r
.
L
iDAR
d
ata
wa
s
o
b
tain
ed
f
r
o
m
th
e
th
ir
d
p
ar
ty
(
PT.
Ocr
o
n
Glo
b
al)
with
ac
q
u
is
itio
n
p
ar
am
eter
s
as
s
h
o
wn
in
T
ab
l
e
2
.
T
h
e
ty
p
e
o
f
L
iDAR
s
en
s
o
r
was th
e
Yello
w
Scan
Ma
p
p
er
,
m
o
u
n
ted
o
n
DJI
Ma
tr
ice
6
0
0
d
r
o
n
e
.
T
ab
l
e
2
.
L
iDAR
Acq
u
is
itio
n
Par
am
eter
s
P
a
r
a
me
t
e
r
S
p
e
c
i
f
i
c
a
t
i
o
n
D
r
o
n
e
D
JI
M
a
t
r
i
c
e
6
0
0
S
p
e
e
d
6
-
1
0
m
/
s
F
l
i
g
h
t
a
l
t
i
t
u
d
e
70
-
1
0
0
m a
b
o
v
e
s
e
a
l
e
v
e
l
La
ser s
p
e
e
d
2
s
H
o
r
i
z
o
n
t
a
l
a
c
c
u
r
a
c
y
20
-
3
0
c
m
u
s
i
n
g
G
C
P
a
n
d
m
o
r
e
t
h
a
n
1
w
i
t
h
o
u
t
G
C
P
V
e
r
t
i
c
a
l
a
c
c
u
r
a
c
y
10
-
1
5
c
m
Li
D
A
R
p
o
i
n
t
d
e
n
s
i
t
y
12
-
1
8
p
o
i
n
t
s/
m
2
S
p
a
t
i
a
l
r
e
s
o
l
u
t
i
o
n
5
-
1
5
c
m/
p
i
x
e
l
d
e
p
e
n
d
s
o
n
f
l
i
g
h
t
a
l
t
i
t
u
d
e
F
l
i
g
h
t
s
i
d
e
l
a
p
6
0
%
F
l
i
g
h
t
o
v
e
r
l
a
p
8
0
%
S
c
a
n
n
i
n
g
r
a
n
g
e
0
.
1
-
3
0
m
D
a
t
a
a
c
q
u
i
s
i
t
i
o
n
r
a
t
e
4
3
,
2
0
0
p
o
i
n
t
s/
sec
2
.
5
.
Da
t
a
a
na
ly
s
is
2
.
5
.
1
.
Act
ua
l
bio
ma
s
s
Ab
o
v
e
g
r
o
u
n
d
b
i
o
m
ass
d
ata
c
an
b
e
m
ea
s
u
r
ed
d
ir
ec
tly
f
r
o
m
d
estru
ctio
n
s
am
p
lin
g
b
y
cu
tti
n
g
th
e
tr
ee
s
.
Un
f
o
r
tu
n
atelly
t
h
is
m
eth
o
d
w
as
co
s
tly
an
d
co
m
p
licated
,
an
o
th
er
way
th
at
we
co
n
d
u
cted
was
u
s
in
g
allo
m
etr
ic
m
o
d
el.
B
y
u
s
in
g
th
is
allo
m
etr
i
c
eq
u
atio
n
,
we
ju
s
t
m
ea
s
u
r
e
d
tr
ee
d
iam
eter
in
th
e
f
ield
.
Data
a
n
aly
s
is
o
f
th
e
a
b
o
v
e
g
r
o
u
n
d
b
io
m
ass
(
AGB)
esti
m
atio
n
,
esp
ec
ially
f
o
r
th
e
tr
ee
,
was
p
er
f
o
r
m
ed
u
s
in
g
th
e
allo
m
et
r
i
es
eq
u
atio
n
d
ev
elo
p
e
d
b
y
J
ay
a
et
a
l
.
[
2
]
o
f
AGB =
0
.
1
0
7
D
2.
486
.
D
r
ep
r
es
en
ted
tr
ee
d
iam
eter
o
f
b
r
ea
s
t h
eig
h
t (
DB
H)
.
2
.
5
.
2
.
L
iDAR
da
t
a
pro
ce
s
s
ing
2
.
5
.
2
.
1
.
Desig
nin
g
o
f
dig
it
a
l
t
er
ra
in m
o
del
(
DT
M
)
T
er
r
estrial
m
o
d
el
o
r
DT
M
is
t
h
e
r
ep
r
esen
tatio
n
o
f
a
ter
r
ain
o
b
tain
ed
f
r
o
m
th
e
p
o
in
t
f
ea
tu
r
es
o
f
L
iDA
R
d
ata
o
f
g
r
o
u
n
d
class
.
T
h
is
d
ata
wh
ich
was
u
s
ed
f
o
r
d
esig
n
i
n
g
th
e
g
r
o
u
n
d
m
o
d
el
was
ed
ited
to
clea
r
u
p
th
e
ter
r
ain
p
o
in
t
cl
o
u
d
,
wh
ich
wa
s
d
ir
ec
tly
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te
r
s
ec
t
ed
with
wa
ter
s
,
an
d
co
r
r
ec
t
ed
p
r
o
p
o
r
tio
n
ally
.
DT
M
m
a
k
in
g
p
r
o
ce
s
s
was
p
er
f
o
r
m
ed
o
n
th
e
p
o
in
t
clo
u
d
class
o
f
g
r
o
u
n
d
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ea
tu
r
e,
to
o
b
tain
a
2
D
r
aster
.
T
h
is
cr
ea
tio
n
was
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KOM
NI
KA
T
elec
o
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m
u
n
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B
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ma
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esti
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ystem
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h
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iz
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773
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ied
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t
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s
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ter
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o
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a
0
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5
r
eso
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tio
n
R
Stu
d
io
s
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twar
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DT
M
was
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s
ed
f
o
r
th
e
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m
aliza
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f
th
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ata
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h
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e
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a
te
th
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ca
n
o
p
y
co
v
er
an
d
tr
ee
h
eig
h
t
.
2
.
5
.
2
.
2
.
L
iDAR
c
a
no
py
co
v
e
r
(
CC)
estim
a
t
io
n
C
an
o
p
y
co
v
er
esti
m
atio
n
in
p
e
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ce
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tag
e
was p
er
f
o
r
m
ed
u
s
in
g
L
iDAR
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ata,
in
th
e
f
o
r
m
o
f
d
i
g
ital te
r
r
ain
mode
l
(
DT
M)
,
wh
ic
h
h
ad
b
ee
n
n
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r
m
alize
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an
d
f
ilter
ed
.
T
h
e
m
eth
o
d
u
s
ed
was
th
e
f
ir
s
t
r
etu
r
n
c
an
o
p
y
in
d
ex
(
FR
C
I
)
.
Acc
o
r
d
in
g
to
Ma
et
a
l
.
[
2
1
]
,
FR
C
I
co
u
ld
g
en
er
ate
h
i
g
h
er
ca
n
o
p
y
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v
e
r
d
ata
d
u
e
to
L
iDAR
p
en
etr
atio
n
in
f
o
r
est ar
ea
s
.
Fu
r
th
e
r
m
o
r
e
,
its
ca
lcu
latio
n
co
m
p
ar
es th
e
f
ir
s
t w
ith
th
e
s
in
g
le
r
etu
r
n
s
as r
ef
er
r
ed
in
[
2
1
,
2
2
]
.
=
∑
F
i
r
s
t
C
an
o
p
y
+
∑
S
i
n
g
l
e
C
an
o
p
y
∑
F
i
r
s
t
T
o
t
al
+
∑
S
i
n
g
l
e
T
o
t
al
(
1
)
De
sc
rip
ti
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n
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F
RCI
=
f
ir
s
t
r
etu
r
n
ca
n
o
p
y
in
d
e
x
(
%),
First
ca
n
o
p
y
=f
ir
s
t
r
et
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r
n
in
ter
s
ec
tin
g
th
e
ca
n
o
p
y
,
Sin
g
l
e
ca
n
o
p
y
=
s
in
g
le
r
etu
r
n
in
ter
s
ec
tin
g
th
e
ca
n
o
p
y
,
First
to
tal
=to
tal
n
u
m
b
er
o
f
f
ir
s
t
r
etu
r
n
,
Sin
g
le
to
tal
=
to
tal
n
u
m
b
er
o
f
s
in
g
le
r
etu
r
n
.
2
.
5
.
2
.
3
.
L
iDAR
t
re
e
heig
ht
e
s
t
im
a
t
io
n
T
h
e
n
o
r
m
alize
d
an
d
f
ilter
e
d
p
o
in
t
clo
u
d
was
u
s
ed
t
o
d
eter
m
in
e
th
e
to
p
o
f
ea
ch
tr
ee
,
wh
ic
h
r
e
p
r
esen
ts
th
eir
p
o
s
itio
n
an
d
h
eig
h
t.
T
h
e
alg
o
r
ith
m
u
s
ed
was
lo
ca
l
m
ax
im
a
(
L
M)
f
ilter
in
g
in
s
q
u
ar
es
o
n
R
s
tu
d
io
.
As
im
p
lem
en
ted
b
y
Po
p
esc
u
et
a
l.
[
1
5
]
,
it
s
h
o
ws
th
at
LM
m
eth
o
d
with
s
q
u
ar
e
win
d
o
ws
is
b
etter
th
an
with
cir
cle
o
n
es
.
T
h
is
r
esear
ch
u
s
ed
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x
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cm
win
d
o
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f
4
0
x
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0
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a
cc
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d
in
g
to
t
h
e
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l
o
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ize
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f
f
iel
d
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ata
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llectio
n
.
T
h
e
m
ea
n
o
f
th
e
id
en
tific
atio
n
r
es
u
lts
o
f
ea
c
h
tr
ee
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eig
h
t
wer
e
esti
m
ated
to
r
ep
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t
th
e
h
ei
g
h
t
v
al
u
e
f
o
r
ea
c
h
p
lo
t
[
2
3
]
.
2
.
5
.
3
.
Reg
re
s
s
io
n
m
o
del f
o
r
m
ula
t
i
on
T
h
e
f
o
r
m
u
lated
m
o
d
els
wer
e
L
iDAR
h
eig
h
t
an
d
b
io
m
ass
e
s
tim
atio
n
m
o
d
els.
T
h
e
C
C
(
ca
n
o
p
y
co
v
e
r
)
an
d
T
r
ee
Hig
h
th
at
wer
e
ex
tr
ac
ted
b
y
th
e
p
o
in
t
clo
u
d
L
iDAR
d
ata
wer
e
u
s
ed
as
in
d
ep
en
d
et
v
ar
iab
le
i
n
f
o
r
m
u
latio
n
m
o
d
el.
Her
e
ar
e
s
ev
er
al
r
eg
r
ess
io
n
m
o
d
els to
f
o
r
m
u
late:
−
L
in
ea
r
r
eg
r
ess
io
n
:
Y
=
a
+
bX
(
2
)
−
L
o
g
ar
ith
m
ic
r
e
g
r
ess
io
n
:
Y
=
a
+
b
ln
X
(
3
)
−
Q
u
ad
r
atic
r
eg
r
ess
io
n
:
Y
=
a
+
b
X
²
(
4
)
−
E
x
p
o
n
e
n
tial r
eg
r
ess
io
n
:
Y
=
a
+
e
xp
bX
(
5
)
−
P
o
wer
r
eg
r
ess
io
n
:
Y
=
a
X
b
(
6
)
2
.
5
.
4
.
Cla
s
s
ic
a
s
s
um
ptio
n t
est
T
h
e
class
ic
ass
u
m
p
tio
n
test
was
p
er
f
o
r
m
ed
at
th
e
test
lev
el
o
f
5
% o
r
α
=
0
.
0
5
.
I
t
was th
e
n
o
r
m
ality
test
,
an
d
aim
ed
to
d
eter
m
in
e
th
e
d
is
tr
ib
u
tio
n
o
f
d
ata.
Fu
r
th
e
r
m
o
r
e,
it
was
ca
r
r
ied
o
u
t
b
y
th
e
Ko
lm
o
g
o
r
o
v
-
Sm
ir
n
o
v
test
.
T
h
e
n
ex
t
test
co
n
d
u
cted
w
as
th
e
h
eter
o
s
ce
d
asti
city
test
,
wh
ich
was
i
n
ten
d
ed
to
ch
ec
k
t
h
e
u
n
if
o
r
m
ity
o
f
th
e
r
est o
f
th
e
m
o
d
el,
u
s
in
g
th
e
Gl
etser
s
tatis
tical
test
.
2
.
5
.
5
.
Co
rr
ela
t
i
o
n
a
nd
a
cc
ura
cy
t
est
T
h
e
s
tatis
tical
test
u
s
ed
was
th
e
co
r
r
elatio
n
test
,
a
n
d
it
ai
m
ed
to
f
in
d
o
u
t
th
e
r
elatio
n
s
h
ip
b
etwe
en
v
ar
iab
les
in
th
e
b
io
m
ass
es
tim
atio
n
.
T
h
e
r
elatio
n
s
h
ip
b
etwe
e
n
th
e
b
io
m
ass
an
d
L
iDAR
d
ata
was
an
aly
ze
d
u
s
ed
th
e
co
r
r
elatio
n
ap
p
r
o
ac
h
o
f
P
ea
r
s
o
n
’
s
p
r
o
d
u
ct
m
o
m
e
n
t
(
r
)
.
C
o
r
r
elatio
n
test
was
p
er
f
o
r
m
ed
to
f
in
d
o
u
t
th
e
d
if
f
er
en
ce
b
etwe
en
th
e
v
alu
e
o
b
tain
ed
f
r
o
m
f
ield
b
io
m
ass
an
d
th
e
b
est
b
io
m
ass
f
r
o
m
L
iDAR
,
L
ea
f
Ar
ea
I
n
d
ex
(
L
AI
)
an
d
ca
n
o
p
y
c
o
v
er
o
f
L
i
DAR
(
FR
C
I
)
,
an
d
ac
tu
al
tr
ee
h
eig
h
t
an
d
L
iDAR
tr
ee
h
eig
h
t
.
W
h
en
th
e
co
r
r
elatio
n
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
1
6
9
3
-
6
9
3
0
T
E
L
KOM
NI
KA
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l Co
n
tr
o
l
,
Vo
l.
19
,
No
.
3
,
J
u
n
e
2
0
2
1
:
7
7
0
-
7
8
0
774
v
alu
e
is
ap
p
r
o
ac
h
in
g
1
/
-
1
it
m
ea
n
s
th
at
th
e
v
al
u
e
o
f
esti
m
atio
n
m
o
d
el
h
as
a
cl
o
s
e
r
elatio
n
s
h
ip
with
th
e
ac
t
u
al
v
alu
e
o
f
th
e
f
ield
d
ata.
On
th
e
co
n
tr
a
r
y
,
if
th
e
co
r
r
elatio
n
v
a
lu
e
ap
p
r
o
ac
h
in
g
0
,
it
m
ea
n
s
th
at
th
e
v
al
u
e
o
f
th
e
esti
m
atio
n
m
o
d
el
h
as
a
d
is
tan
t
r
elatio
n
s
h
ip
f
r
o
m
th
e
ac
tu
al
v
a
lu
e
.
Acc
u
r
ac
y
test
was
p
er
f
o
r
m
ed
to
ascer
tain
th
e
ac
cu
r
ac
y
o
f
th
e
esti
m
atio
n
as
co
m
p
ar
ed
t
o
th
e
ac
tu
al
d
ata
.
T
h
i
s
test
co
u
ld
b
e
p
er
f
o
r
m
ed
b
y
lo
o
k
in
g
at
th
e
R
MSE
(
r
o
o
t
m
ea
n
s
q
u
a
r
e
er
r
o
r
)
,
ag
g
r
eg
ate
d
e
v
iatio
n
(
SA)
a
n
d
s
(
d
ev
iatio
n
s
tan
d
a
r
t)
v
alu
e
[
24]
.
Acc
o
r
d
in
g
to
Sp
u
r
r
[
25
]
,
a
g
o
o
d
e
q
u
atio
n
h
a
s
ag
g
r
eg
ate
d
e
v
iatio
n
(
SA)
v
alu
e
r
an
g
es
f
r
o
m
-
1
to
+1
.
T
h
e
s
m
aller
th
e
s
tan
d
ar
d
d
ev
iatio
n
is
,
th
e
m
o
r
e
ac
cu
r
ate
th
e
ex
p
ec
ted
v
alu
e
[
26]
.
2
.
5
.
6
.
Select
io
n o
f
t
he
bes
t
-
f
it
m
o
d
el
Fo
r
a
m
o
d
el
to
b
e
f
ea
s
ib
le
as
a
r
eg
r
ess
io
n
m
o
d
el
f
o
r
t
h
e
esti
m
atio
n
o
f
b
io
m
ass
,
it
n
ee
d
s
to
h
av
e
a
h
ig
h
co
ef
f
icien
t
o
f
d
eter
m
in
ati
o
n
v
alu
e.
I
n
ad
d
itio
n
,
ag
g
r
eg
ate
d
ev
iatio
n
v
alu
e
is
also
co
n
s
id
er
ed
a
cr
iter
ia
f
o
r
s
elec
tin
g
th
e
b
est
m
o
d
el.
W
h
en
a
m
o
d
el
h
as
an
Ag
g
r
eg
ate
d
ev
iatio
n
v
alu
e
o
f
-
1
to
1
it
m
ea
n
s
th
at
th
at
it
i
s
f
ea
s
ib
le
to
b
e
u
s
ed
as
t
h
e
b
e
s
t
esti
m
atio
n
m
o
d
el
[
2
]
.
Selectio
n
o
f
th
e
b
est
b
io
m
ass
esti
m
atio
n
m
o
d
el
was
co
n
d
u
cte
d
b
y
r
an
k
in
g
th
e
co
m
p
ar
ativ
e
v
alu
es
(
S,
SA,
R
M
SE
)
,
wh
er
e
th
e
b
est
r
an
k
was
g
iv
en
to
th
e
g
r
ea
test
s
co
r
e.
T
h
e
s
co
r
e
was id
en
tifie
d
u
s
in
g
th
e
(
7
)
:
Sc
ore
=
(
(
ev
−
mi
n
ma
x
−
mi
n
)
x
(
5
−
1
)
)
+
1
(
7)
wh
er
e
,
E
v
:
E
s
tim
atio
n
v
alu
e
,
m
in
:
m
in
im
u
m
v
alu
e,
a
n
d
m
a
x
:
m
ax
im
u
m
v
alu
e.
3.
RE
SU
L
T
S
A
ND
AN
AL
Y
SI
S
3
.
1
.
F
ield
inv
ent
o
ry
T
h
e
m
ea
s
u
r
em
e
n
t
o
f
v
e
g
etatio
n
ch
a
r
ac
ter
is
tics
wh
ich
in
cl
u
d
es,
h
eig
h
t
,
d
iam
e
ter
,
tr
ee
s
p
ec
ies
an
d
n
u
m
b
er
o
f
tr
ee
was
p
er
f
o
r
m
e
d
m
an
u
ally
u
s
in
g
s
im
p
le
m
ea
s
u
r
in
g
to
o
ls
.
I
t
was
d
is
co
v
er
e
d
th
at
th
e
av
er
ag
e
h
eig
h
t,
an
d
d
iam
eter
(
DB
H)
o
f
th
e
tr
ee
s
was
2
7
m
an
d
5
7
c
m
r
esp
ec
tiv
ely
.
I
n
a
d
d
itio
n
,
t
h
e
n
u
m
b
er
o
f
tr
e
e
at
r
esear
ch
lo
ca
tio
n
was
2632
,
a
n
d
co
n
s
is
ted
o
f
6
8
ty
p
es,
an
d
3
6
Fam
ily
.
Ho
wev
er
,
o
n
e
o
f
th
em
co
u
ld
n
o
t
b
e
id
en
tifie
d
an
d
s
o
was
lab
elled
as u
n
k
n
o
w
n
.
T
h
e
d
ata
was v
ar
ied
b
a
s
ed
o
n
th
e
h
eig
h
t a
n
d
tr
e
e
d
ata
at
ea
ch
p
l
o
t.
3
.
2
.
A
c
t
ua
l
bio
m
a
s
s
B
io
m
ass
co
n
s
id
er
ed
in
th
is
r
e
s
ea
r
ch
was
lim
ited
to
th
e
tr
ee
with
d
iam
ater
at
b
r
ea
s
t
h
eig
h
t
(
DB
H)
g
r
ea
ter
th
an
th
e
1
0
cm
,
an
d
with
p
lo
t
ar
ea
o
f
4
0
x
4
0
m
.
T
h
e
h
ig
h
est
b
io
m
ass
co
n
ten
t
u
s
in
g
allo
m
etr
y
b
y
J
ay
a
et
a
l
.
[
2
]
(
B
K)
was
37
.
0
7
9
to
n
s
/p
lo
t
an
d
th
e
l
o
west
was
0
.
0
3
3
t
o
n
s
/p
lo
t
as
s
h
o
wn
in
Fig
u
r
e
3
.
T
h
e
av
er
a
g
e
b
io
m
ass
s
to
ck
was
20
.
9
7
to
n
s
/p
lo
t
at
B
K
ca
lcu
latio
n
.
T
h
e
r
esu
lts
o
f
th
e
ca
lcu
latio
n
u
s
in
g
two
al
l
o
m
etr
ies
s
h
o
wed
th
at
b
o
th
wer
e
n
o
t
s
ig
n
if
ican
tly
d
if
f
e
r
en
t
as
s
h
o
wn
i
n
Fig
u
r
e
4
.
T
h
er
ef
o
r
e
,
in
o
r
d
e
r
to
d
eter
m
in
e
t
h
e
b
io
m
ass
esti
m
atio
n
m
o
d
el,
th
e
two
r
esu
lts
,
an
d
ea
ch
b
io
m
ass
esti
m
atio
n
m
o
d
els
wer
e
u
s
ed
in
T
ab
le
3
.
F
ig
u
r
e
3
.
R
esu
lt
ca
lcu
latio
n
f
i
eld
b
io
m
a
ss
3
.
3
.
E
s
t
im
a
t
io
n o
f
c
a
no
py
co
v
er
a
nd
heig
ht
f
ro
m
L
iDAR
C
an
o
py
co
v
e
r
r
ep
r
esen
ted
b
y
FR
C
I
v
alu
e
[
2
1
]
r
esu
lted
in
th
e
h
ig
h
est
v
alu
e
at
p
lo
t
6
with
99
.
8
2
%
an
d
th
e
lo
west
at
p
lo
t
2
of
0
.
4
2
%
a
s
s
h
o
wn
in
Fig
u
r
e
4
.
T
h
e
p
lo
t
with
lo
w
d
e
n
s
ity
v
alu
e
was
in
th
e
o
p
en
f
o
r
est,
wit
h
v
eg
etatio
n
co
m
p
o
s
itio
n
d
o
m
in
ated
b
y
s
h
r
u
b
s
,
f
er
n
s
an
d
wee
d
s
,
wh
ich
co
u
l
d
r
ea
ch
2
m
h
ei
g
h
t
.
T
h
e
r
ef
o
r
e
,
th
e
ca
n
o
p
y
co
v
er
was r
elativ
ely
lo
w.
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KOM
NI
KA
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l Co
n
tr
o
l
B
io
ma
s
s
esti
ma
tio
n
mo
d
el
fo
r
p
ea
t sw
a
mp
fo
r
est ec
o
s
ystem
u
s
in
g
… (
Mu
h
a
m
a
d
R
iz
a
l
)
775
T
h
e
co
m
p
ar
is
o
n
ch
ar
t
b
etwe
e
n
ac
tu
al
an
d
p
r
e
d
icted
ca
n
o
p
y
co
v
er
(
Fig
u
r
e
4
)
s
h
o
wed
alm
o
s
t
s
im
ilar
ch
an
g
in
g
p
atter
n
.
I
n
a
d
d
itio
n
,
s
im
ilar
d
is
tr
ib
u
tio
n
p
atter
n
s
h
o
wed
a
clo
s
e
r
elatio
n
s
h
ip
b
etwe
en
th
e
ac
tu
al
an
d
th
e
esti
m
ated
v
alu
e
,
with
co
r
r
e
latio
n
v
alu
e
o
f
0
.
9
3
(
L
AI
:
FR
C
I
)
.
T
h
e
h
ig
h
esti
m
atio
n
v
alu
e
o
f
L
iDAR
b
ased
on
m
ea
n
lo
ca
l
m
ax
im
a
(
L
M)
r
es
u
lted
in
th
e
r
an
g
e
o
f
m
ea
n
tr
e
e
h
eig
h
t
b
ein
g
7
.
92
-
23
.
7
6
m
,
with
th
e
av
er
ag
e
at
18
.
1
2
m
.
I
n
ad
d
itio
n
,
th
e
tallest
tr
ee
was
at
p
lo
t
9
w
h
ile
th
e
l
o
west
at
p
lo
t
1
as
s
h
o
wn
in
Fig
u
r
e
4
.
Data
o
n
h
eig
h
t
wo
u
ld
b
e
u
s
ed
as
i
n
d
ep
e
n
d
en
t
v
ar
iab
le
in
d
esig
n
in
g
t
h
e
b
io
m
ass
esti
m
atio
n
m
o
d
el
.
T
h
e
c
o
m
p
ar
is
o
n
b
etwe
en
th
e
ac
tu
al
an
d
p
r
e
d
icted
m
ea
n
tr
ee
h
eig
h
t in
ea
ch
p
lo
t
(
Fig
u
r
e
4
)
s
h
o
wed
th
at
th
e
p
r
ed
icted
h
eig
h
t w
as g
r
ea
ter
,
b
u
t
b
o
th
ch
ar
t
p
atter
n
wer
e
al
m
o
s
t
th
e
s
am
e,
an
d
s
lig
h
tly
in
ter
s
ec
ted
in
p
lo
t
1
,
2
an
d
4
,
wh
ich
wer
e
th
e
lo
w
p
lo
ts
.
I
t
in
d
icate
d
th
at
tr
ee
h
eig
h
t
esti
m
atio
n
f
r
o
m
L
iDA
R
was
b
etter
in
th
e
ar
ea
wit
h
lo
w
ca
n
o
p
y
co
v
e
r
.
Ho
wev
er
,
th
e
p
r
e
d
icted
tr
ee
h
e
ig
h
t
h
ad
a
clo
s
e
r
elatio
n
s
h
ip
wi
th
th
at
o
f
th
e
ac
tu
al
tr
ee
,
with
c
o
r
r
elatio
n
(
r
)
v
alu
e
o
f
0
.
7
2
4
as
s
h
o
wn
in
T
a
b
l
e
4
,
a
n
d
b
ased
o
n
ac
c
u
r
ac
y
test
,
it
s
h
o
wed
a
g
o
o
d
R
MSE
=
0
.
9
8
6
an
d
SA=0
.
3
5
2
,
s
in
ce
its
v
alu
e
was w
ith
in
th
e
r
ec
o
m
m
en
d
ed
r
an
g
e
o
f
-
1
to
1
[
2
5
]
.
De
s
c
r
ipt
ion:
C
C
L
A
I
=CC
ac
tual
,
C
C
p
=CC
pr
e
diction
Fig
u
r
e
4
.
C
C
an
d
tr
ee
h
ig
h
p
r
e
d
ictio
n
v
alu
e
a
n
d
th
ei
r
co
m
p
ar
is
o
n
with
ac
tu
al
v
alu
e
p
e
r
p
lo
t
3
.
4
.
B
io
ma
s
s
estim
a
t
io
n
m
o
del
T
h
e
b
io
m
ass
esti
m
atio
n
m
o
d
el
was
d
esig
n
b
ased
o
n
t
h
e
a
n
aly
s
is
o
f
th
e
r
elatio
n
s
h
ip
b
e
twee
n
th
e
d
ep
en
d
e
n
t
v
ar
iab
le
(
Y)
,
wh
ich
id
th
e
b
io
m
as
s
,
th
e
in
d
ep
en
d
en
t
v
ar
iab
le
(
X
)
,
C
C
(
X1
)
an
d
tr
e
e
h
eig
h
t
(
X2
)
f
r
o
m
L
iDAR
d
ata.
Fu
r
th
er
m
o
r
e,
it
was
d
esig
n
ed
u
s
in
g
3
0
b
i
o
m
ass
f
ield
d
ata
,
ca
n
o
p
y
c
o
v
er
(
C
C
)
f
r
o
m
L
iDAR
an
d
tr
ee
h
eig
h
t
f
r
o
m
L
iDAR
.
Selectio
n
o
f
its
eq
u
atio
n
was b
ased
o
n
s
ca
tter
d
ia
g
r
am
p
atter
n
.
T
ab
l
e
3.
E
s
tim
atio
n
m
o
d
el
b
i
o
m
ass
ca
lcu
latio
n
r
esu
lts
M
o
d
e
l
BK
R
e
g
r
e
ssi
o
n
E
q
u
a
t
i
o
n
M1
Y
=
-
3
.
37
0
+
27
.
97
0*
X
1
M2
Y
=
-
18
.
48
0
+
2
.
1
2
2
*
X
2
M3
Y
=
-
18
.
47
0
+
0
.
03
0
X
1
+
2
.
1
2
1
*
X
2
M4
Y
=
2
2
.
0
4
5
+
5
.
3
8
7
*
LN
(
X
1
)
M5
Y
=
-
69
.
5
0
6
+
3
1
.
2
1
4
*
LN
(
X
2
)
M6
Y
=
-
73
.
0
6
2
–
0
.
4
2
4
*
LN
(
X
1
)
+
32
.
3
9
7
*
LN
(
X
2
)
M7
Y
=
0
.
1
2
3
+
2
6
.
3
0
7
*
X
1
2
M8
Y
=
-
2
.
1
6
4
+
0
.
0
6
4
*
X
2
2
M9
Y
=
-
3
.
498
+
5
.
3
9
5
*
X
1
2
+
0
.
0
5
6
*
X
2
2
M
1
0
Y
=
2
6
.
0
5
8
*
X
1
1
.
8
08
M
1
1
Y
=
0
.
0
3
5
*
X
2
2
.
168
M
1
2
Y
=
-
12
.
1
4
5
*
X
1
-
0
.
031
+ X
2
1
.
197
M
1
3
Y
=
2
.
7
0
7
3
5
*
e
x
p
(2
.
286*X
1)
M
1
4
Y
=
2
.
1
7
5
*
e
x
p
(0
.
1
18*X
2)
M
1
5
Y
=
1
.
5
0
8
*
e
x
p
(0
.
712*X
1
+
0
.
104*X
2)
N
o
t
e
:
Y
=
B
K
,
X
1
=
C
C
,
X
2
=
H
e
i
g
h
t
o
f
L
i
D
AR
3
.
5
.
M
o
del
bu
ild
i
ng
t
est
3
.
5
.
1
.
Cla
s
s
ic
a
s
s
um
ptio
n t
est
A
g
o
o
d
m
o
d
el
is
o
n
e
th
at
m
ee
t
s
class
ica
l
ass
u
m
p
tio
n
s
with
th
e
ex
p
ec
tatio
n
th
at
it
ca
n
p
r
o
v
id
e
ac
cu
r
ac
y
an
d
c
o
n
s
is
ten
cy
in
m
ak
in
g
est
im
atio
n
s
.
T
h
e
class
ic
ass
u
m
p
tio
n
test
s
u
s
ed
in
th
is
r
esear
ch
wer
e
n
o
r
m
ality
a
n
d
h
eter
o
s
ce
d
asti
city
test
.
N
or
m
ality
test
wa
s
co
n
d
u
cted
to
s
p
o
t
th
e
n
o
r
m
al
d
is
tr
ib
u
tio
n
o
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th
e
r
em
ain
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er
o
f
th
e
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o
d
el
u
s
in
g
Ko
lm
o
g
o
r
o
v
-
Sm
ir
n
o
v
test
,
an
d
th
e
r
esu
lts
(
T
a
b
le
4
)
s
h
o
wed
th
at
th
e
m
o
d
els w
ith
th
e
Y
2
v
a
r
iab
le
(
B
K)
all
m
et
th
e
n
o
r
m
ality
a
s
s
u
m
p
tio
n
.
T
h
e
n
ex
t
test
was
th
e
h
eter
o
s
ce
d
asti
city
test
.
I
t
aim
s
to
s
p
o
t
th
e
u
n
if
o
r
m
ity
o
f
th
e
r
est o
f
th
e
m
o
d
el
u
s
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g
g
lacie
r
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tatis
tical
te
s
t.
T
h
e
r
esu
lts
o
f
th
e
s
ig
n
if
ica
n
ce
test
o
f
v
ar
ia
b
les
wer
e
with
in
th
e
r
an
g
e
o
f
0
.
087
-
0
.
9
9
5
,
th
er
ef
o
r
e,
it
ca
n
b
e
s
aid
th
at
all
m
o
d
els
wer
e
h
o
m
o
g
en
eo
u
s
b
ec
au
s
e
wh
en
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
1
6
9
3
-
6
9
3
0
T
E
L
KOM
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T
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t E
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n
tr
o
l
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l.
19
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3
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J
u
n
e
2
0
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1
:
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7
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ig
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er
e
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eter
o
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ce
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asti
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o
r
H
0
r
ejec
tio
n
[
2
7
,
2
8
]
.
T
h
e
r
esu
lts
o
f
n
o
r
m
ality
an
d
h
eter
o
s
ce
d
asti
city
test
s
p
r
o
v
i
d
ed
in
f
o
r
m
atio
n
a
b
o
u
t
th
e
n
ex
t
m
o
d
el
to
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e
test
ed
.
T
ab
l
e
4
.
R
esu
lts
o
f
n
o
r
m
ality
t
est
B
K
V
S
C
C
p
;
A
_
H
p
N
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r
mal
i
t
y
Te
st
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e
t
e
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o
sce
d
a
st
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c
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t
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T
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st
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o
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l
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scri
p
t
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scri
p
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n
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1
5
0
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mal
0
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9
9
0
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o
n
st
a
n
t
M2
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mal
0
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6
3
9
C
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st
a
n
t
M3
0
.
0
6
4
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r
mal
0
.
5
5
4
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st
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n
t
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1
5
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r
mal
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1
9
5
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n
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8
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r
mal
0
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3
8
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8
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06
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9
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5
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4
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st
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n
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1
0
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0
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0
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6
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st
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n
t
M
1
1
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1
5
0
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r
mal
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5
8
2
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o
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st
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n
t
M
1
2
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1
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0
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0
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2
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st
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3
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4
2
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st
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n
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1
4
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mal
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1
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st
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n
t
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1
5
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5
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r
mal
0
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9
9
5
C
o
n
st
a
n
t
3
.
5
.
2
.
Co
rr
ela
t
i
o
n
t
est
T
h
e
r
elatio
n
s
h
ip
b
etwe
en
th
e
d
ep
en
d
e
n
t
(
Y)
a
n
d
i
n
d
ep
e
n
d
e
n
t
v
ar
iab
le
(
X)
ca
n
b
e
id
e
n
tifi
ed
th
r
o
u
g
h
co
r
r
elatio
n
test
.
Mo
r
eo
v
er
,
to
d
is
co
v
er
th
e
r
elatio
n
s
h
ip
am
o
n
g
th
e
s
tr
u
ctu
r
i
n
g
v
ar
iab
les
in
d
esig
n
in
g
th
e
m
o
d
el,
a
co
r
r
elatio
n
test
was
p
er
f
o
r
m
ed
o
n
t
h
e
ac
tu
a
l
an
d
p
r
e
d
icted
v
alu
es
,
wh
ich
wer
e
t
h
e
ca
n
o
p
y
co
v
er
v
alu
e
f
r
o
m
CCa
,
th
e
p
r
ed
icted
ca
n
o
p
y
co
v
er
v
alu
e
f
r
o
m
FR
C
I
/C
C
p
,
ac
tu
al
m
ea
n
tr
ee
h
eig
h
t
(
A_
Ha)
,
a
n
d
Me
an
tr
ee
h
eig
h
t
f
r
o
m
L
iDAR
(
A_
Hp
)
.
C
C
a
an
d
FR
C
I
r
ep
r
esen
ted
th
e
ac
tu
al
an
d
p
r
ed
icte
d
ca
n
o
p
y
co
v
e
r
(T
ab
l
e
5
)
,
an
d
d
ata
o
n
th
e
later
was
co
llec
ted
f
r
o
m
th
e
p
r
ev
io
u
s
s
tu
d
ies.
T
h
e
co
r
r
elatio
n
test
aim
ed
at
p
r
o
v
in
g
th
at
th
e
f
ield
an
d
p
r
ed
icted
v
a
r
iab
le
(
L
iDAR
v
a
r
iab
le
)
wer
e
clo
s
ely
r
elate
d
.
T
h
e
r
esu
lts
o
f
th
e
co
r
r
elatio
n
a
n
aly
s
is
,
wh
ich
ar
e
s
h
o
wn
in
T
ab
le
5
s
h
o
w
th
at
th
e
co
r
r
elatio
n
b
etwe
en
th
e
ac
tu
al
an
d
p
r
ed
ictio
n
v
ar
i
ab
les
wer
e
p
o
s
itiv
e.
Fu
r
t
h
er
m
o
r
e,
th
e
clo
s
en
ess
r
elatio
n
s
h
ip
test
was
co
n
d
u
cted
b
etwe
en
th
e
p
ar
am
eter
o
f
th
e
f
ield
an
d
p
r
ed
ictio
n
,
a
n
d
th
e
r
esu
lts
s
h
o
wed
th
at
a
s
tr
o
n
g
r
elatio
n
s
h
ip
ex
is
ted
b
etwe
en
th
em
,
s
u
ch
as b
etwe
en
th
e
ac
tu
al
an
d
p
r
ed
icted
h
eig
h
t o
f
0
.
7
2
4
,
an
d
b
etwe
en
C
C
p
an
d
C
C
a
o
f
0
.
9
3
4
.
T
h
is
m
ea
n
s
th
at
th
e
p
a
r
am
eter
s
o
f
tr
ee
h
eig
h
t
an
d
ca
n
o
p
y
co
v
er
f
r
o
m
L
iDAR
,
as
th
e
p
r
ed
ic
tiv
e
v
ar
iab
les
co
u
ld
r
ep
r
esen
t th
e
ac
tu
al
v
eg
etatio
n
p
ar
am
eter
s
.
T
h
er
ef
o
r
e,
th
e
v
a
r
iab
le
f
r
o
m
L
iDAR
co
u
ld
b
e
u
s
ed
as in
d
ep
en
d
en
t
v
ar
iab
le
in
th
e
b
io
m
ass
esti
m
atio
n
m
o
d
el
.
T
h
e
r
esu
lts
o
f
th
e
an
aly
s
is
in
T
ab
le
5
s
h
o
wed
th
at
th
e
co
r
r
elatio
n
b
etwe
en
th
e
d
ep
en
d
en
t
(
Y)
a
n
d
th
e
i
n
d
ep
e
n
d
en
t
v
ar
iab
le
(
X
)
h
ad
a
p
o
s
iti
v
e
co
r
r
elatio
n
,
with
r
an
g
e
v
alu
e
o
f
0
.
671
-
0
.
8
24
.
Fu
r
th
er
m
o
r
e,
th
e
p
o
s
itiv
e
co
r
r
elatio
n
c
o
ef
f
icie
n
t
v
alu
es
wer
e
g
r
ea
ter
th
an
0
.
5
o
n
ea
ch
v
ar
iab
les,
an
d
th
is
in
d
icate
d
a
clo
s
e
r
elat
io
n
s
h
ip
b
etwe
en
th
e
b
io
m
ass
v
ar
iab
le
to
th
e
CC
v
ar
iab
le
an
d
th
e
h
eig
h
t v
a
r
iab
le
f
r
o
m
L
iDAR
d
ata.
T
h
e
p
o
s
itiv
e
co
r
r
elatio
n
v
alu
e
ex
p
lain
ed
t
h
at
an
in
cr
ea
s
e
in
b
io
m
ass
v
alu
e
wo
u
ld
b
e
f
o
llo
wed
b
y
an
i
n
cr
ea
s
e
in
th
e
CC
an
d
t
r
ee
h
eig
h
t
v
alu
e
f
r
o
m
L
iDAR
an
d
v
ice
v
er
s
a.
T
ab
le
5.
R
esu
lts
o
f
co
r
r
elatio
n
test
b
etwe
en
v
ar
iab
les
V
a
r
i
a
b
l
e
C
Ca
A
_
H
a
C
C
p
A
_
H
p
A
_
H
a
0
.
5
5
4
C
C
p
0
.
9
3
4
0
.
4
9
9
A
_
H
p
0
.
8
0
5
0
.
7
2
4
0
.
8
0
1
BK
0
.
7
3
5
0
.
6
7
1
0
.
7
4
5
0
.
8
2
4
N
o
t
e
:
C
C
p
=
p
r
e
d
i
c
t
e
d
c
a
n
o
p
y
c
o
v
e
r
(
%/
p
l
o
t
)
,
C
C
a
=
a
c
t
u
a
l
c
a
n
o
p
y
c
o
v
e
r
f
ro
m
L
AI
(
%
/
p
l
o
t
)
,
A
_
H
p
=
p
r
e
d
i
c
t
e
d
m
e
a
n
h
e
i
g
h
t
f
r
o
m
L
i
D
AR
(
m
/
p
l
o
t
)
,
A
_
H
a
=
a
c
t
u
a
l
m
e
a
n
h
e
i
g
h
t
f
r
o
m
f
i
e
l
d
m
e
a
su
r
e
m
e
n
t
(
m
/
p
l
o
t
)
,
BK
=
Bi
o
m
a
ss
o
f
e
q
u
a
t
i
o
n
c
a
l
c
u
l
a
t
i
o
n
r
e
su
l
t
(
t
o
n
/
p
l
o
t
)
,
3
.
5
.
3
.
Acc
ura
cy
t
est
Acc
u
r
ac
y
test
was
p
er
f
o
r
m
ed
to
f
in
d
o
u
t
h
o
w
ac
cu
r
ate
th
e
esti
m
ated
v
alu
es
wer
e,
co
m
p
a
r
ed
to
th
e
ac
tu
al
o
n
es
.
I
n
ad
d
itio
n
,
t
h
e
a
cc
u
r
ac
y
test
u
s
ed
was
R
MSE
.
Mo
d
el
v
alid
atio
n
test
aim
ed
at
d
eter
m
in
in
g
th
e
r
eliab
ilit
y
o
f
th
e
r
esu
lted
esti
m
atio
n
b
y
lo
o
k
in
g
at
th
e
SA.
Valid
atio
n
an
d
ac
cu
r
ac
y
test
s
wer
e
ca
r
r
ied
o
u
t
b
y
ce
n
s
u
s
,
u
s
in
g
all
d
ata
(
3
0
o
b
s
er
v
atio
n
p
lo
ts
)
(
T
ab
le
6
)
.
T
h
e
r
esu
lts
o
f
ac
cu
r
ac
y
an
d
v
alid
ity
test
s
(
T
ab
le
6
)
s
h
o
wed
ac
ce
p
tab
le
v
alu
e
(
C
C
p
v
s
C
C
a2
R
MSE
=
0
.
0
0
5
an
d
SA
=
-
0
.
0
4
2
)
,
o
r
in
o
th
er
wo
r
d
,
FR
C
I
v
ar
iab
l
e
co
u
ld
ex
p
lain
th
e
ac
tu
al
v
ar
ia
b
le
.
Acc
u
r
ac
y
test
s
wer
e
th
en
p
er
f
o
r
m
e
d
o
n
th
e
b
io
m
ass
esti
m
atio
n
m
o
d
el
b
y
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KOM
NI
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T
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m
u
n
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m
p
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iz
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ee
n
th
e
esti
m
ated
an
d
th
e
ac
tu
al
v
alu
e
o
f
ea
c
h
in
d
e
p
en
d
en
t v
ar
iab
le.
T
h
e
tab
le
s
h
o
ws
th
at
th
e
esti
m
ated
ac
cu
r
ac
y
[
2
8
]
o
f
th
e
r
an
g
e
o
f
R
MSE
v
alu
es
o
b
tain
e
d
f
r
o
m
eq
u
atio
n
(
B
K)
is
0
.
0001
-
1
.
5
9
1
5
(
%)
(
T
ab
le
7
)
.
B
esid
es
R
MSE
,
th
e
ac
cu
r
ac
y
test
v
alu
e
also
u
s
ed
wer
e
Stan
d
ar
d
Dev
iatio
n
(
S),
an
d
th
eir
v
alu
e
r
an
g
ed
f
r
o
m
5
.
25
-
7
.
2
7
.
Acc
o
r
d
in
g
to
Dr
ap
e
r
an
d
Sm
ith
[
2
6
]
th
e
s
m
aller
th
e
S
v
alu
e
is
th
e
b
etter
m
o
d
el
.
SA v
alu
e
r
ep
r
ese
n
ted
th
e
v
alid
ity
v
alu
e
o
f
th
e
m
o
d
el
.
I
n
ad
d
itio
n
,
th
e
s
m
aller
it i
s
,
th
e
more
v
alid
th
e
m
o
d
el
is
b
ec
a
u
s
e
th
e
d
if
f
er
e
n
c
e
b
etwe
en
th
e
esti
m
ated
an
d
a
ctu
al
v
alu
e
wo
u
ld
b
e
s
m
aller
as
well
.
T
h
e
r
esu
lts
o
f
th
e
an
aly
s
is
s
h
o
w
ed
th
at
v
alu
e
o
f
SA
r
an
g
ed
f
r
o
m
–
0
.
0
1
2
5
0
3
7
–
0
.
0
0
9
0
7
6
7
(
T
ab
le
7
)
.
Fu
r
th
er
m
o
r
e
,
th
is
was
with
in
th
e
r
an
g
e
o
f
v
alu
e
s
r
eq
u
ir
ed
b
y
Sp
u
r
r
[
2
5
]
,
wh
ich
is
-
1
to
1
.
L
astl
y
,
S,
R
MSE
an
d
th
o
s
e
v
alu
es
wo
u
ld
b
e
u
s
ed
as
th
e
cr
iter
ia
to
d
eter
m
in
e
th
e
b
est b
io
m
ass
esti
m
ato
r
m
o
d
el
.
T
ab
l
e
6
.
R
esu
lts
o
f
ac
cu
r
ac
y
t
ests
o
f
tr
ee
h
eig
h
t a
n
d
ca
n
o
p
y
co
v
er
V
a
r
i
a
b
l
e
R
M
S
E
SA
C
C
p
V
S
C
c
a
0
.
0
0
5
-
0
.
042
A
_
H
p
V
s
A
_
H
a
0
.
9
8
6
0
.
3
5
2
N
o
t
e
:
C
C
p
=
p
re
d
i
c
t
e
d
c
a
n
o
p
y
d
e
n
s
i
t
y
,
C
C
a
=
a
c
t
u
a
l
c
a
n
o
p
y
c
o
v
e
r
f
ro
m
L
AI
,
A_
H
p
=
p
re
d
i
c
t
e
d
m
e
a
n
h
e
i
g
h
t
f
r
o
m
L
i
D
AR,
A_
H
a
=
a
c
t
u
a
l
m
e
a
n
h
e
i
g
h
t
(
f
i
e
l
d
m
e
a
s
u
reme
n
t
)
T
ab
l
e
7
.
R
esu
lts
o
f
ac
cu
r
ac
y
t
ests
B
K
M
o
d
e
l
C
o
d
e
BK
E
q
u
a
t
i
o
n
S
SA
R
M
S
E
(
%)
Li
n
e
a
r
M1
Y
=
-
2
.
5
0
0
+
2
8
.
1
2
0
*
X
1
5
.
27
-
0
.
0
0
0
0
9
1
4
0
.
0
0
8
5
M2
Y
=
-
13
.
2
6
0
+
1
.
8
8
9
*
X
2
5
.
31
-
0
.
0
0
0
2
7
4
8
0
.
0
1
9
1
M3
Y
=
-
12
.
8
4
0
+
9
.
02
X
1
+
1
.
4
5
*
X
2
5
.
25
0
.
0
0
0
5
7
1
9
0
.
0
7
1
5
Lo
g
a
r
i
t
h
mi
c
M4
Y
=
2
3
.
1
0
8
+
5
.
5
6
*
LN
(
X
1
)
5
.
33
-
0
.
0
0
0
0
0
1
4
0
.
0
0
0
4
M5
Y
=
-
60
.
8
9
0
+
2
8
.
5
5
*
LN
(
X
\
)
5
.
57
-
0
.
0
0
0
0
0
6
4
0
.
0
0
0
7
M6
Y
=
-
53
.
4
5
5
+
0
.
8
8
7
*
LN
(
X
1
)
+
2
6
.
0
8
1
*
LN
(
X
2
)
6
.
27
-
0
.
0
0
0
0
0
6
6
0
.
0
0
0
5
Q
u
a
d
r
a
t
i
c
M7
Y
=
1
.
4
0
7
+
2
5
.
9
2
4
*
X
1
2
6
.
29
-
0
.
0
1
2
5
0
3
7
0
.
0
0
0
2
M8
Y
=
1
.
7
0
9
+
0
.
0
5
6
*
X
2
6
.
21
-
0
.
0
0
0
0
0
0
4
0
.
0
0
0
1
M9
Y
=
-
1
.
1
0
9
+
1
1
.
3
9
5
*
X
1
2
+0
.
0
3
9
*
X
2
2
5
.
41
-
0
.
0
0
0
0
0
0
5
0
.
0
0
0
3
P
o
w
e
r
M
1
0
Y
=
2
6
.
4
6
1
6
*
X
1
1
.
47
094
5
.
50
0
.
0
0
2
3
1
6
5
0
.
3
5
2
0
M
1
1
Y
=
0
.
1
6
1
8
7
6
*
X
2
1
.
6717
5
7
.
27
0
.
0
0
5
6
4
9
7
1
.
1
5
2
3
M
1
2
Y
=
-
5
.
6
8
6
*
X
1
-
0
.
164
+
X
2
1
.
138
7
.
27
0
.
0
0
0
0
3
0
1
0
.
0
6
2
2
Ex
p
o
n
e
n
t
i
a
l
M
1
3
Y
=
3
.
6
1
2
*
e
x
p
2
.
02
1
*
X
1
5
.
72
0
.
0
0
9
0
7
6
7
1
.
5
9
1
5
M
1
4
Y
=
3
.
6
0
7
*
e
x
p
0
.
09
4*X
2
5
.
29
0
.
0
0
7
7
6
7
1
1
.
1
5
8
7
M
1
5
Y
=
2
.
3
2
6
*
e
x
p
(1
.
0
17*
X
1
+
0
.
069
*X
2)
6
.
42
0
.
0
0
7
2
0
1
7
1
.
2
0
2
3
3
.
5
.
4
.
Select
io
n o
f
t
he
b
est
bio
m
a
s
s
estim
a
t
io
n
m
o
del
T
h
e
m
o
d
els
u
s
ed
in
o
b
tain
i
n
g
th
e
b
i
o
m
ass
esti
m
atio
n
e
q
u
atio
n
ar
e
lin
ea
r
,
lo
g
ar
ith
m
ic,
p
o
wer
,
q
u
ad
r
atic
a
n
d
e
x
p
o
n
en
tial
m
o
d
els
(
s
ee
T
ab
le
7
)
.
Fu
r
th
e
r
m
o
r
e
,
th
e
b
est
r
e
g
r
ess
io
n
eq
u
atio
n
m
o
d
el
was
o
b
tain
e
d
by
s
co
r
i
n
g
t
h
e
s
tan
d
ar
d
d
ev
ia
tio
n
(
s
)
,
ag
g
r
eg
ate
d
ev
iatio
n
(
SA)
an
d
r
o
o
t
m
ea
n
s
q
u
a
r
e
e
r
r
o
r
(
R
MSE
)
.
T
h
e
h
ig
h
est s
co
r
e
was r
a
n
k
ed
f
ir
s
t,
o
r
i
n
o
th
e
r
wo
r
d
s
,
it
is
th
e
b
est b
io
m
ass
esti
m
ato
r
m
o
d
el
(
T
a
b
le
8
).
T
h
e
s
co
r
in
g
r
esu
lts
s
h
o
wed
th
at
M9
wh
ich
is
a
q
u
a
d
ra
ti
c
re
g
re
ss
io
n
m
o
d
e
l
was th
e
b
est
m
o
d
el
in
th
e
B
K
eq
u
atio
n
,
as it h
ad
a
s
co
r
e
o
f
1
4
.
97
3
.
Fu
r
th
er
m
o
r
e,
it
h
ad
a
R
MSE
o
f
0
.
0
0
0
3
%
,
S
o
f
5
.
4
1
an
d
v
alid
atio
n
v
alu
e
(
SA)
o
f
0
.
0
0
0
0
0
0
5
(
T
ab
le
7
)
.
T
h
is
v
alid
atio
n
r
esu
lts
co
u
ld
b
e
ca
teg
o
r
ized
as
g
o
o
d
s
in
ce
it
ap
p
r
o
ac
h
ed
th
e
s
co
r
e
‘
0
’
,
an
d
in
o
th
er
wo
r
d
s
th
e
esti
m
ati
on
m
o
d
el
c
o
u
ld
in
c
r
ea
s
in
g
ly
d
escr
ib
e
th
e
ac
tu
al
s
tate.
T
h
e
M9
r
eg
r
ess
io
n
eq
u
atio
n
m
o
d
el
was
Y
=
-
1
.
1
0
9
+
1
1
.
3
9
5
*
X
1
2
+0
.
0
3
9
*
X
2
2
(
s
ee
T
ab
l
e
7)
,
with
R
2
of
72
.
1
6
%,
an
d
it
ca
n
b
e
in
ter
p
r
eted
th
at
th
e
v
ar
iab
le
Y
(
B
io
m
ass
)
co
u
ld
b
e
ex
p
lain
ed
b
y
FR
C
I
an
d
L
iDAR
tr
ee
h
eig
h
t o
f
72
.
1
6
%.
3
.
6
.
B
io
m
a
s
s
dis
t
rib
utio
n
T
h
e
b
io
m
ass
d
is
tr
ib
u
tio
n
o
f
t
h
e
r
esu
lts
o
f
ea
ch
ca
lcu
latio
n
ca
n
b
e
s
ee
n
in
Fig
u
r
e
5
.
B
io
m
ass
at
th
e
r
esear
ch
lo
ca
tio
n
r
a
n
g
ed
m
ajo
r
ly
f
r
o
m
27
-
5
5
(
t
on)
,
with
a
n
av
er
ag
e
v
al
u
e
o
f
3
9
.
8
7
1
to
n
s
.
Ho
wev
er
,
in
s
o
m
e
lo
ca
tio
n
s
th
er
e
wer
e
b
io
m
ass
s
to
ck
s
wh
ich
h
ad
m
in
u
s
an
d
ze
r
o
v
alu
es.
T
h
is
was d
u
e
to
th
e
lo
w
FR
C
I
v
ar
iab
le
(
0
)
.
B
K
esti
m
atio
n
m
o
d
el
s
h
o
wed
th
at
th
e
b
io
m
ass
v
al
ue
at
th
e
r
esear
ch
lo
ca
tio
n
(
lo
g
g
ed
-
o
v
er
s
ec
o
n
d
ar
y
p
ea
t
s
wam
p
f
o
r
est)
with
a
n
ar
ea
o
f
2
0
0
h
a
was
2
4
4
.
3
1
4
to
n
s
/h
a.
T
h
is
r
esu
lt
was
alm
o
s
t
s
im
ilar
to
th
at
o
b
tain
ed
in
No
v
ita
’
s
r
esear
ch
(
2
7
6
.
9
5
to
n
s
/h
a
)
[
2
9
]
,
wh
ich
was
co
n
d
u
cted
in
th
e
lo
g
g
e
d
-
o
v
er
p
ea
t
s
wam
p
f
o
r
ests
in
Me
r
an
g
,
So
u
th
Su
m
atr
a
,
b
u
t
h
ig
h
er
th
an
th
at
m
en
tio
n
ed
in
R
o
ch
m
ay
a
n
to
[
3
0
]
r
esear
ch
,
of
1
6
6
.
9
3
to
n
s
/h
a
,
in
a
s
ec
o
n
d
ar
y
p
ea
t
f
o
r
ests
,
an
d
K
r
o
s
h
en
d
er
a
et
a
l.
[
3
1
]
o
f
1
5
9
.
9
to
n
s
/h
a
in
a
lo
g
g
ed
-
o
v
er
s
ec
o
n
d
ar
y
f
o
r
ests
.
I
n
a
d
d
i
t
i
o
n
,
t
h
e
b
i
o
m
a
s
s
i
n
t
h
e
m
i
x
e
d
p
e
a
t
f
o
r
e
s
t
s
,
i
n
C
e
n
t
r
a
l
K
a
l
i
m
a
n
t
a
n
w
a
s
3
1
1
t
o
n
s
/
h
a
[
3
2
]
.
S
o
m
e
v
a
r
i
a
t
i
o
n
s
i
n
t
h
e
r
e
s
u
l
t
s
o
f
t
h
e
s
e
c
a
l
c
u
l
a
t
i
o
n
s
w
e
r
e
d
u
e
t
o
d
i
f
f
e
r
e
n
c
e
s
t
h
e
c
a
l
c
u
l
a
t
i
o
n
m
e
t
h
o
d
,
a
n
d
t
h
e
c
o
n
d
i
t
i
o
n
o
f
r
e
s
e
a
r
c
h
a
r
e
a
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
1
6
9
3
-
6
9
3
0
T
E
L
KOM
NI
KA
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l Co
n
tr
o
l
,
Vo
l.
19
,
No
.
3
,
J
u
n
e
2
0
2
1
:
7
7
0
-
7
8
0
778
T
ab
el
8
.
T
h
e
ch
o
s
en
m
o
d
el
o
f
B
K
b
est b
io
m
ass
eq
u
atio
n
M
o
d
e
l
R
2
S
SA
R
M
S
E
S
c
o
r
e
R
a
n
k
i
n
g
M9
7
2
.
1
6
%
4
.
9
7
4
5
.
0
0
0
4
.
9
9
9
1
4
.
9
7
3
1
M5
6
9
.
3
6
%
4
.
8
9
3
5
.
0
0
0
4
.
9
9
8
1
4
.
8
9
2
2
M3
6
9
.
9
0
%
5
.
0
0
0
4
.
9
9
6
4
.
8
2
1
1
4
.
8
1
7
3
M2
6
7
.
8
5
%
4
.
8
4
5
4
.
9
9
9
4
.
9
5
2
1
4
.
7
9
6
4
M8
6
7
.
1
9
%
4
.
3
7
1
5
.
0
0
0
5
.
0
0
0
1
4
.
3
7
1
5
M1
5
5
.
5
5
%
2
.
9
8
4
5
.
0
0
0
4
.
9
7
9
1
2
.
9
6
2
6
M7
5
5
.
3
5
%
2
.
9
5
5
5
.
0
0
0
5
.
0
0
0
1
2
.
9
5
5
7
M
1
0
6
6
.
0
9
%
3
.
0
9
7
4
.
9
8
1
4
.
1
1
6
1
2
.
1
9
3
8
M
1
4
6
3
.
2
7
%
4
.
6
8
4
4
.
9
3
7
2
.
0
8
8
1
1
.
7
0
9
9
M
1
1
5
6
.
3
8
%
4
.
5
2
3
4
.
9
3
7
2
.
1
0
4
1
1
.
5
6
5
10
M4
4
0
.
2
6
%
1
.
0
0
0
5
.
0
0
0
4
.
9
9
9
1
0
.
9
9
9
11
M6
6
9
.
7
3
%
1
.
0
0
0
5
.
0
0
0
4
.
9
9
9
1
0
.
9
9
9
12
M
1
5
6
8
.
2
8
%
4
.
0
8
0
4
.
9
3
5
1
.
9
7
8
1
0
.
9
9
3
13
M
1
2
6
9
.
5
0
%
4
.
9
3
1
1
.
0
0
0
4
.
8
4
4
1
0
.
7
7
5
14
M
1
3
5
3
.
9
2
%
2
.
6
8
3
4
.
9
1
4
1
.
0
0
0
8
.
5
9
7
15
Fig
u
r
e
5
.
B
io
m
ass
d
is
tr
ib
u
tio
n
o
f
B
K
eq
u
atio
n
4.
CO
NCLU
SI
O
N
C
C
an
d
tr
ee
h
eig
h
t
f
r
o
m
L
iD
AR
c
o
u
ld
b
e
u
s
ed
as
v
ar
iab
les
to
esti
m
ate
th
e
am
o
u
n
t
o
f
b
io
m
ass
,
s
in
ce
th
er
e
was
ac
cu
r
ac
y
(
R
MSE
=
0
.
0
0
5
,
SA
=
-
0
.
0
4
2
)
b
etwe
en
th
e
ac
tu
al
a
n
d
p
r
ed
icted
C
C
,
an
d
m
ea
n
tr
ee
h
eig
h
t
(
R
MSE
=
0
,
9
8
6
,
SA
=
0
,
3
5
2
)
.
T
h
e
b
io
m
ass
esti
m
atio
n
m
o
d
el
u
s
ed
th
e
q
u
ad
r
atic
m
o
d
el
,
with
eq
u
atio
n
Y1
=
-
3
.
4
9
8
+5
.
3
9
5
*
X
1
2
+0
.
0
5
6
4
*
X
2
2
.
I
n
ad
d
itio
n
,
th
e
SA
v
al
u
e
was
0
.
0
0
0
0
0
0
5
(
B
K)
,
an
d
th
e
r
esu
ltin
g
R
2
was
72
.
16%
(
B
K)
.
T
h
e
m
o
d
els
p
r
o
d
u
ce
d
a
b
io
m
ass
v
alu
e
o
f
244
.
5
1
0
to
n
s
/h
a
(
B
K)
.
T
h
is
s
tu
d
y
o
n
ly
u
s
ed
3
0
s
am
p
les
b
ec
au
s
e
o
f
lim
ited
r
eso
u
r
ce
s
.
T
h
er
ef
o
r
e,
in
f
u
tu
r
e
s
tu
d
ies,
m
o
r
e
s
am
p
les
s
h
o
u
ld
b
e
u
s
ed
in
o
r
d
er
to
o
b
tain
m
o
r
e
ac
cu
r
a
te
esti
m
ato
r
m
o
d
el
s
.
L
a
s
tly
,
ad
v
an
ce
d
a
n
aly
s
is
wh
ich
in
teg
r
ates
L
iDAR
an
d
s
atellite
im
ag
er
y
is
n
ee
d
ed
to
o
b
tain
th
e
ar
ea
(
PT.
R
MU
a
r
ea
)
o
f
t
h
e
b
io
m
ass
.
AC
K
NO
WL
E
DG
E
M
E
NT
S
T
h
e
au
th
o
r
s
wo
u
ld
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e
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x
p
r
ess
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r
atitu
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d
s
th
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I
n
ter
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atio
n
al
Par
tn
er
s
h
ip
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r
o
g
r
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e
(
I
PP
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o
f
t
h
e
U
K
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p
a
c
e
A
g
e
n
c
y
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h
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g
h
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c
o
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e
t
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n
d
e
r
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o
r
e
s
t
s
2
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2
0
P
r
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c
t
(
h
t
t
p
s
:
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c
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)
f
o
r
th
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f
in
an
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ce
.
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KOM
NI
KA
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l Co
n
tr
o
l
B
io
ma
s
s
esti
ma
tio
n
mo
d
el
fo
r
p
ea
t sw
a
mp
fo
r
est ec
o
s
ystem
u
s
in
g
… (
Mu
h
a
m
a
d
R
iz
a
l
)
779
REFE
RENC
E
S
[1
]
Th
e
In
d
o
n
e
sia
n
Ag
e
n
c
y
f
o
r
Ag
ricu
lt
u
ra
l
Re
se
a
rc
h
a
n
d
De
v
e
lo
p
m
e
n
t
)
,
“
In
d
o
n
e
sia
n
P
e
a
tl
a
n
d
s:
F
o
rm
a
ti
o
n
,
Ch
a
ra
c
teristics
,
a
n
d
P
o
ten
ti
a
l
fo
r
S
u
p
p
o
rt
in
g
F
o
o
d
S
e
c
u
rit
y
(
i
n
In
d
o
n
e
sia
:
La
h
a
n
G
a
m
b
u
t
In
d
o
n
e
sia
:
P
e
m
b
e
n
t
u
k
a
n
,
Ka
ra
k
teristik
,
d
a
n
P
o
ten
si
M
e
n
d
u
k
u
n
g
Ke
tah
a
n
a
n
P
a
n
g
a
n
)
,
”
Re
v
isi
o
n
E
d
isi,
Ja
k
a
rta:
IAA
RD P
re
ss
,
2
0
1
6
.
[2
]
A.
Ja
y
a
,
e
t
a
l
.,
“
Tro
p
ica
l
p
e
a
t
s
wa
m
p
fo
re
st
b
i
o
m
a
ss
u
n
d
e
r
v
a
ri
o
u
s
la
n
d
c
o
v
e
r
c
o
n
d
it
io
n
s
(
i
n
I
n
d
o
n
e
sia
:
B
io
m
a
sa
h
u
tan
ra
wa
g
a
m
b
u
t
tro
p
ik
a
p
a
d
a
b
e
rb
a
g
a
i
k
o
n
d
isi
p
e
n
u
t
u
p
a
n
lah
a
n
)
,
”
J
u
rn
a
l
Pe
n
e
li
ti
a
n
H
u
ta
n
d
a
n
Ko
n
se
rv
a
si
Al
a
m
,
v
o
l.
4
.
p
p
.
3
4
1
-
2
5
2
,
2
0
0
7
.
[3
]
M
.
R
.
C
.
P
o
sa
,
e
t
al
.,
“
Bio
d
iv
e
rsit
y
a
n
d
c
o
n
se
rv
a
ti
o
n
o
f
tr
o
p
ica
l
p
e
a
t
sw
a
m
p
fo
re
sts,”
Bi
o
S
c
ien
c
e
,
v
o
l
.
6
1
,
p
p
.
49
-
5
7
,
2
0
1
1
.
[4
]
Wah
y
u
n
t
o
,
S
.
Rit
u
n
g
,
S
u
p
a
rt
o
,
H.
S
u
b
a
g
jo
,
“
P
e
a
t
Distrib
u
ti
o
n
a
n
d
Ca
rb
o
n
C
o
n
ten
t
in
S
u
m
a
tra
a
n
d
Ka
li
m
a
n
tan
2
0
0
4
(
i
n
In
d
o
n
e
sia
:
S
e
b
a
ra
n
G
a
m
b
u
t
d
a
n
Ka
n
d
u
n
g
a
n
Ka
rb
o
n
d
i
S
u
m
a
tera
d
a
n
Ka
li
m
a
n
tan
2
0
0
4
)
,
”
W
e
tl
a
n
d
s
In
ter
n
a
t
io
n
a
l
-
I
n
d
o
n
e
sia
Pro
g
ra
m
me
,
Bo
g
o
r.
ID.
2
0
0
5
.
[5
]
INCA
S
,
“
Da
ta n
a
sio
n
a
l
,
”
2
0
1
8
.
[
On
li
n
e
].
A
v
a
il
a
b
le:
h
tt
p
:
//
ww
w.i
n
c
a
s
-
in
d
o
n
e
sia
.
o
rg
/i
d
/
d
a
ta/n
a
ti
o
n
a
l
-
d
a
ta/
[6
]
A.
A.
Alm
u
lq
u
,
e
t
a
l
.
,
“
Tree
sp
e
c
ies
c
o
m
p
o
siti
o
n
a
n
d
str
u
c
tu
re
o
f
d
r
y
fo
re
st
i
n
M
u
ti
s
T
ima
u
P
r
o
tec
ted
F
o
re
s
t
M
a
n
a
g
e
m
e
n
t
Un
it
o
f
Eas
t
Nu
sa
T
e
n
g
g
a
ra
,
I
n
d
o
n
e
sia
,”
Bi
o
d
ive
rs
it
a
s
,
v
o
l
.
1
9
,
n
o
.
2
,
p
p
.
4
9
6
-
5
0
3
,
2
0
1
8
.
[7
]
M
.
B
.
S
a
leh
,
e
t
a
l
.
,
“
Alg
o
r
it
h
m
fo
r
d
e
tec
ti
n
g
d
e
fo
re
sta
ti
o
n
a
n
d
fo
re
st
d
e
g
ra
d
a
t
io
n
u
sin
g
v
e
g
e
t
a
ti
o
n
in
d
ice
s
,
”
T
EL
KOM
NIKA
T
e
lec
o
mm
u
n
ic
a
ti
o
n
C
o
mp
u
ti
n
g
El
e
c
tro
n
ics
a
n
d
Co
n
tro
l
,
v
o
l
.
1
7
,
n
o
.
5
,
p
p
.
2
3
3
5
-
2
3
4
5
,
Oc
t.
2
0
1
9
.
[8
]
C.
Du
p
u
is,
e
t
a
l
.
,
“
H
o
w
c
a
n
re
m
o
te
se
n
sin
g
h
e
lp
m
o
n
it
o
r
tr
o
p
ica
l
m
o
ist
fo
re
st
d
e
g
ra
d
a
ti
o
n
?
—
a
sy
st
e
m
a
ti
c
re
v
iew
,
”
Rem
o
te S
e
n
s
i
n
g
,
v
o
l.
1
2
,
n
o
.
7
,
p
p
.
1
0
8
7
-
1
1
1
0
,
2
0
2
0
.
[9
]
UN
F
CCC
(
Un
it
e
d
Na
ti
o
n
s
F
ra
m
e
wo
rk
C
o
n
v
e
n
ti
o
n
o
n
C
li
m
a
te
C
h
a
n
g
e
)
,
“
Re
c
o
m
m
e
n
d
a
ti
o
n
s
o
n
f
u
tu
re
fin
a
n
c
i
n
g
o
p
ti
o
n
s
f
o
r
e
n
h
a
n
c
i
n
g
t
h
e
d
e
v
e
l
o
p
m
e
n
t,
d
e
p
lo
y
m
e
n
t,
d
iff
u
sio
n
a
n
d
tran
sfe
r
o
f
tec
h
n
o
l
o
g
ies
u
n
d
e
r
t
h
e
c
o
n
v
e
n
ti
o
n
,”
p
re
se
n
ted
a
t
T
h
e
Un
it
e
d
Na
ti
o
n
s
F
ra
m
e
wo
rk
Co
n
v
e
n
ti
o
n
in
Cli
m
a
te Ch
a
n
g
e
C
o
n
fe
re
n
c
e
,
Bo
n
n
,
M
a
y
2
0
0
9
.
[1
0
]
J.
Zö
rn
e
r
,
e
t
a
l.
,
“
Li
DA
R
-
Ba
se
d
Re
g
io
n
a
l
In
v
e
n
to
r
y
o
f
Tall
Tre
e
s
—
Welli
n
g
t
o
n
,
Ne
w
Zea
lan
d
,
”
Fo
re
sts
,
v
o
l.
9
,
p
p
.
7
0
2
-
7
1
7
.
2
0
1
8
.
[1
1
]
A.
P
a
sc
u
a
l
,
“
U
sin
g
tree
d
e
tec
ti
o
n
b
a
se
d
o
n
a
ir
b
o
r
n
e
las
e
r
sc
a
n
n
in
g
t
o
imp
ro
v
e
fo
re
st
in
v
e
n
to
r
y
c
o
n
sid
e
ri
n
g
e
d
g
e
e
_
e
c
ts an
d
th
e
c
o
-
re
g
istrati
o
n
fa
c
t
o
r
,
”
Rem
o
te
S
e
n
s
in
g
,
v
o
l
.
1
1
,
n
o
.
2
2
,
p
p
.
2
6
7
5
-
2
6
9
2
,
2
0
1
9
.
[1
2
]
B
.
Lo
h
a
n
i
,
“
Air
b
o
r
n
e
a
lt
ime
tri
c
LIDAR:
P
rin
c
i
p
le,
d
a
ta
c
o
ll
e
c
ti
o
n
,
p
r
o
c
e
ss
in
g
a
n
d
a
p
p
li
c
a
ti
o
n
s
,
”
2
0
1
8
.
[
o
n
li
n
e
].
Av
a
il
a
b
le:
h
tt
p
:/
/h
o
m
e
.
ii
tk
.
a
c
.
i
n
/~
b
l
o
h
a
n
i/
Li
DA
R_
Tu
t
o
rial/Air
b
o
rn
e
_
Alt
ime
tri
c
Li
d
a
r_
T
u
t
o
rial.
Htm
[1
3
]
J.
B.
Ca
m
p
b
e
ll
,
“
In
tr
o
d
u
c
ti
o
n
to
Re
m
o
te S
e
n
sin
g
,
”
Ne
w Yo
rk
:
T
h
e
Gu
il
d
fo
rd
Pre
ss
,
2
0
0
7
.
[1
4
]
R
.
Du
b
a
y
a
h
a
n
d
J
.
Dra
k
e
,
“
LIDA
R
re
m
o
te
se
n
sin
g
fo
r
fo
re
stry
,
J
o
u
rn
a
l
o
f
Fo
re
stry
,”
v
o
l.
98
,
n
o
.
6
,
p
p
.
44
-
46,
2
0
0
0
.
[1
5
]
S
.
C
.
P
o
p
e
sc
u
,
e
t
a
l
.,
“
M
e
a
su
rin
g
i
n
d
i
v
id
u
a
l
tree
c
ro
wn
d
iam
e
ter
wit
h
li
d
a
r
a
n
d
a
ss
e
ss
in
g
it
s
in
fl
u
e
n
c
e
o
n
e
stim
a
ti
n
g
fo
re
st v
o
lu
m
e
a
n
d
b
i
o
m
a
ss
,”
Ca
n
a
d
i
a
n
J
o
u
rn
a
l
o
f
Rem
o
te S
e
n
si
n
g
,
v
o
l
.
29
,
n
o
.
5
,
p
p
.
5
6
4
-
5
7
7
,
M
a
y
2
0
0
3
.
[1
6
]
J
.
Ju
b
a
n
sk
i,
e
t
a
l
.
,
“
De
tec
ti
o
n
o
f
larg
e
a
b
o
v
e
-
g
ro
u
n
d
b
i
o
m
a
ss
v
a
riab
il
it
y
in
l
o
wla
n
d
f
o
re
st
e
c
o
sy
ste
m
s
b
y
a
irb
o
r
n
e
Li
DA
R
,”
Bi
o
g
e
o
sc
ien
c
e
s
,
v
o
l
.
10
,
n
o
.
6
,
p
p
.
3
9
1
7
-
3
9
3
0
,
Ju
n
e
2
0
1
3
.
[1
7
]
A
.
F
e
rra
z
,
e
t
a
l
.
,
“
Airb
o
rn
e
li
d
a
r
e
stim
a
ti
o
n
o
f
a
b
o
v
e
g
r
o
u
n
d
f
o
re
st
b
io
m
a
ss
in
th
e
a
b
se
n
c
e
o
f
field
in
v
e
n
to
r
y
,
”
Rem
o
te
S
e
n
sin
g
,
v
o
l
.
8
,
n
o
.
8
,
p
p
.
1
-
18
,
A
u
g
u
st
2
0
1
6
.
[1
8
]
W
.
S
.
Wan
-
M
o
h
d
-
Ja
a
fa
r,
e
t
a
l
.
,
“
M
o
d
e
ll
i
n
g
i
n
d
i
v
id
u
a
l
tree
a
b
o
v
e
g
r
o
u
n
d
b
i
o
m
a
ss
u
sin
g
d
isc
re
te
re
tu
r
n
li
d
a
r
i
n
l
o
wla
n
d
d
ip
ter
o
c
a
rp
fo
re
st
o
f
M
a
lay
sia
,”
J
o
u
rn
a
l
o
f
T
r
o
p
ic
a
l
F
o
re
st S
c
ien
c
e
,
v
o
l.
29
,
n
o
.
4
,
pp.
4
6
5
-
4
8
4
,
M
a
r
c
2
0
1
7
.
[1
9
]
G
.
P
.
As
n
e
r,
e
t
a
l
,
“
A
u
n
iv
e
rsa
l
a
i
rb
o
r
n
e
Li
DA
R
a
p
p
ro
a
c
h
fo
r
tro
p
i
c
a
l
fo
re
st
c
a
rb
o
n
m
a
p
p
in
g
,
”
Oe
c
o
lo
g
i
a
,
v
o
l.
1
6
8
,
pp
.
1
1
4
7
-
1
1
6
0
,
2
0
1
2
.
[2
0
]
H
.
A
.
M
a
rg
o
li
s,
e
t
a
l
.,
“
C
o
m
b
in
i
n
g
sa
telli
te
li
d
a
r,
a
irb
o
rn
e
li
d
a
r,
a
n
d
g
ro
u
n
d
p
lo
ts
t
o
e
stim
a
te
t
h
e
a
m
o
u
n
t
a
n
d
d
istri
b
u
ti
o
n
o
f
a
b
o
v
e
g
ro
u
n
d
b
i
o
m
a
ss
in
th
e
b
o
re
a
l
fo
re
st
o
f
No
rt
h
Am
e
rica
,
”
Ca
n
a
d
i
a
n
J
o
u
rn
a
l
o
f
F
o
re
st
Res
e
a
rc
h
,
v
o
l.
45
,
n
o
.
7
,
p
p
.
8
3
8
-
8
5
5
.
Ju
l
y
2
0
1
5
.
[2
1
]
Q.
Ma
,
e
t
a
l
.
,
“
Co
m
p
a
riso
n
o
f
c
a
n
o
p
y
c
o
v
e
r
e
stim
a
ti
o
n
fr
o
m
a
irb
o
rn
e
li
d
a
r,
a
e
rial
ima
g
e
ry
,
a
n
d
sa
te
ll
it
e
ima
g
e
ry
,
”
IEE
E
J
o
u
rn
a
l
o
f
S
e
lec
ted
T
ro
p
ics
in
Ap
p
li
e
d
Ea
rt
h
O
b
se
rv
a
ti
o
n
a
n
d
Rem
o
te S
e
n
si
n
g
,
v
o
l.
10
,
n
o
.
9
,
pp.
4
2
2
5
-
4
2
3
6
,
2
0
1
7
.
[2
2
]
L.
B.
P
ra
se
ty
o
,
e
t
a
l
.
,
“
Ca
n
o
p
y
c
o
v
e
r
o
f
m
a
n
g
r
o
v
e
e
stim
a
ti
o
n
b
a
se
d
o
n
a
irb
o
rn
e
L
i
DA
R
&
Lan
d
sa
t
8
OLI
,
”
in
IOP
Co
n
f.
S
e
rie
s: E
a
rt
h
a
n
d
En
v
ir
o
n
me
n
ta
l
S
c
ien
c
e
,
2
0
1
8
.
[2
3
]
S
.
C.
P
o
p
e
sc
u
a
n
d
R
Wy
n
n
e
,
“
S
e
e
in
g
t
h
e
tree
s
in
t
h
e
fo
re
st:
u
sin
g
li
d
a
r
a
n
d
m
u
lt
is
p
e
c
tral
d
a
ta
fu
sio
n
wit
h
l
o
c
a
l
fil
terin
g
a
n
d
v
a
ria
b
le
win
d
o
w
siz
e
fo
r
e
stim
a
ti
n
g
tree
h
e
ig
h
t
,”
P
h
o
to
g
ra
mm
e
tric
E
n
g
i
n
e
e
rin
g
a
n
d
R
e
mo
te
S
e
n
si
n
g
,
v
o
l.
7
0
,
n
o
.
5
,
pp
.
89
-
6
0
4
,
M
a
y
2
0
0
4
.
[2
4
]
Am
a
ro
,
et
al
.
,
“
M
o
d
e
ll
in
g
F
o
re
st
S
y
ste
m
s
,
”
Lo
n
d
o
n
:
CA
BI
P
u
b
li
s
h
in
g
,
2
0
0
3
.
[2
5
]
S
.
H
.
S
p
u
rr
,
“
F
o
re
st I
n
v
e
n
to
r
y
,
”
Ne
wY
o
rk
:
T
h
e
Ro
n
a
l
d
Pre
ss
Co
mp
a
n
y
,
In
c
.
1
9
5
2
.
[2
6
]
N
.
R
.
Dra
p
e
r
a
n
d
H.
S
m
it
h
,
“
An
a
li
sis Re
g
re
si T
e
ra
p
a
n
Ed
isi
2
,
”
Ja
k
a
rta (ID):
Gr
a
me
d
ia
,
1
9
9
2
.
[2
7
]
A.
Wi
d
a
r
y
o
n
o
,
“
Ek
o
n
o
m
e
tri
k
a
T
e
o
ri
d
a
n
Ap
li
k
a
si
(I
n
Ba
h
a
sa
:
Eco
n
o
m
e
tri
c
Th
e
o
r
y
a
n
d
A
p
p
l
ica
ti
o
n
)
,
”
Yo
g
y
a
k
a
rt
a
(ID):
Eko
n
o
n
isi
a
F
E,
2
0
0
7
.
[2
8
]
I.
G
h
o
z
a
li
,
“
M
u
lt
iv
a
riate
An
a
ly
si
s
Ap
p
li
c
a
ti
o
n
wit
h
S
P
S
S
P
ro
g
ra
m
(
in
In
d
o
n
e
sia
:
Ap
li
k
a
si
An
a
li
s
is
M
u
lt
i
v
a
riate
d
e
n
g
a
n
P
ro
g
ra
m
S
P
S
S
)
,
”
S
e
m
a
ra
n
g
(ID):
U
n
ive
rs
it
a
s Dip
o
n
e
g
o
ro
Pre
ss
.
2
0
0
1
.
[2
9
]
N.
No
v
it
a
,
“
Th
e
p
o
te
n
ti
a
l
fo
r
a
b
o
v
e
g
ro
u
n
d
b
o
u
n
d
c
a
rb
o
n
i
n
lo
g
g
e
d
-
o
v
e
r
p
e
a
t
fo
re
sts
(
in
In
d
o
n
e
sia
:
P
o
ten
si
k
a
rb
o
n
terik
a
t
d
i
a
tas
p
e
rm
u
k
a
a
n
tan
a
h
p
a
d
a
h
u
tan
g
a
m
b
u
t
b
e
k
a
s
teb
a
n
g
a
n
)
,”
M.
S
.
t
h
e
sis
,
I
PB
Un
iv,
Bo
g
o
r,
I
n
d
o
n
e
sia
,
2
0
1
0
.
[3
0
]
Y.
Ro
c
h
m
a
y
a
n
to
,
“
Ch
a
n
g
e
s
i
n
c
a
rb
o
n
c
o
n
ten
t
a
n
d
e
c
o
n
o
m
ic
v
a
lu
e
in
t
h
e
c
o
n
v
e
rsio
n
o
f
p
e
a
t
sw
a
m
p
fo
re
st
to
p
u
lp
in
d
u
strial
p
u
l
p
wo
o
d
p
lan
tati
o
n
s
(
in
In
d
o
n
e
sia
:
P
e
ru
b
a
h
a
n
k
a
n
d
u
n
g
a
n
k
a
rb
o
n
d
a
n
n
il
a
i
e
k
o
n
o
m
in
y
a
p
a
d
a
k
o
n
v
e
rsi
h
u
tan
ra
wa
g
a
m
b
u
t
m
e
n
jad
i
h
u
tan
tan
a
m
a
n
i
n
d
u
stri
p
u
lp
)
,”
M
.
S
.
t
h
e
sis
,
De
p
t.
Fo
re
st
M
a
n
a
g
e
me
n
t
,
IP
B
Un
iv,
Bo
g
o
r
,
In
d
o
n
e
sia
,
2
0
0
9
.
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