Remo e Sens. 2011, 3, 945-961; doi:10.3390/ s3050945
Remo e Sensing
ISSN 2072-4292
www.mdpi.com/jou nal/ emo esensing
A icle
Compa ison o G id-Based and Segmen -Based Es ima ion o
Fo es A ibu es Using Ai bo ne Lase Scanning and Digi al
Ae ial Image y
Saka i Tuominen 1,* and Reija Haapanen 2
1 Finnish Fo es Resea ch Ins i u e, Me sän u kimuslai os, PL 18, 01301 Van aa, Finland
2 Haapanen Fo es Consul ing, Kä jenkosken ie 38, 64810 Vanhakylä, Finland;
E-Mail: eija.haapanen@haapanen o es consul ing. i
* Au ho o whom co espondence should be add essed; E-Mail: saka[email p o ec ed];
Tel.: +358-10-211-2167; Fax: +358-10-211-2202.
Recei ed: 2 Feb ua y 2011; in e ised o m: 4 Ma ch 2011 / Accep ed: 2 May 2011 /
Published: 12 May 2011
Abs ac : Fo es managemen planning in Finland is cu en ly adop ing a new-gene a ion
o es in en o y me hod, which is based on in e p e a ion o ai bo ne lase scanning da a
and digi al ae ial images. The in en o y me hod is based on a sys ema ic g id, whe e he
g id elemen s se e as in en o y uni s, o which he lase and ae ial image da a a e
ex ac ed and he o es a iables es ima ed. As an al e na i e o a complemen o he g id
elemen s, image segmen s can be used as in en o y uni s. The image segmen s a e
pa icula ly use ul as he basis o gene a ion o he sil icul u al ea men and cu ing uni s
since hei bounda ies should ollow he ac ual s and bo de s, whe eas when using g id
elemen s i is ypical ha some o hem co e pa s o se e al o es s ands. The p opo ion
o he so-called mixed cells depends on he size o he g id elemen s and he a e age size
and shape o he s ands. In his s udy, we ca ied ou au oma ic segmen a ion o wo s udy
a eas on he basis o lase and ae ial image da a wi h a iew o delinea ing mic o-s ands
ha a e homogeneous in ela ion o hei o es a ibu es. Fu he , we ex ac ed lase and
ae ial image ea u es o bo h sys ema ic g id elemen s and segmen s. Fo bo h uni s, he
ea u e se used o es ima ing he o es a ibu es was selec ed by means o a gene ic
algo i hm. O he ea u es selec ed, he majo i y (61–79%) we e based on he ai bo ne lase
scanning da a. Despi e he heo e ical ad an ages o he image segmen s, he lase and
ae ial ea u es ex ac ed om g id elemen s seem o wo k be e han ea u es ex ac ed
om image segmen s in es ima ion o o es a ibu es. We conclude ha es ima ion should
OPEN ACCESS
Remo e Sens. 2011, 3
946
be ca ied ou a g id le el wi h an a ea-speci ic combina ion o ea u es and es ima es o
image segmen s o be de i ed on he basis o he g id-le el es ima es.
Keywo ds: o es in en o y; ai bo ne lase scanning; ae ial pho og aphy; image
segmen a ion
1. In oduc ion
In Finland, he o es in en o y o o es managemen planning has adi ionally been based on
isual in en o y by s ands. In his me hod, he o es s ands ha a e delinea ed on he basis o ae ial
pho og aphs and hei g owing s ock and si e- ela ed cha ac e is ics a e measu ed o es ima ed in he
ield. The me hod equi es a la ge amoun o ieldwo k. The e o e, he isual in en o y me hod is o be
eplaced wi h a new-gene a ion o es in en o y me hod.
The new-gene a ion o es in en o y me hod will be based on in e p e a ion o ai bo ne lase
scanning (ALS) da a and digi al ae ial image y using ield sample plo s as e e ence da a. Lase
scanning has been conside ed he mos p omising emo e sensing echnology in o es in en o y, and i
has been widely applied o s and-le el o es in en o ies (e.g., [1–4]). On he o he hand, ALS da a a e
no well sui ed o es ima ion o ee species p opo ions o dominance a he applied poin densi y
(e.g., [5]). Acco dingly, op ical image y is needed o complemen he ALS da a. Spec al ea u es o
op ical images a e ypically used o sepa a ing di e en ee species, whe eas ex u al ea u es o
op ical images a e mainly connec ed wi h he size and spa ial a angemen o he ee c owns. In
Finland, ae ial images ha e been widely used in o es in en o y since he 1950s [6], and hei
a o dabili y and a ailabili y a e good (e.g., [3,7]).
S a is ically, he new-gene a ion o es in en o y me hod is based on wo-phase sampling wi h
s a i ica ion, whe e he in en o y da abase is based on a sys ema ic g id o sample uni s (i.e., g id
elemen s as sample uni s), and he size o he g id elemen s should co espond o he size o ield plo s.
Field measu emen s a e alloca ed in o s a a ha a e commonly de i ed on he basis o ea lie s and
in en o y da a. Typical emo e sensing da a sou ces used in he new-gene a ion o es in en o y sys em
a e low-densi y ALS da a ( ypically 1–2 pulses/m2) and digi al ae ial image y wi h a spa ial esolu ion
o app oxima ely 0.5 m con aining he ollowing spec al channels: blue (B), g een (G), ed (R) and
nea -in a ed (NIR).
The o es a iables a e es ima ed o each elemen o he in en o y g id, and each g id elemen is
commonly de ined as a squa e a ea. As an al e na i e o he g id-based app oach, use o au oma ic
s and delinea ion by image segmen a ion has been s udied o de ining in en o y uni s (e.g., [8]).
Au oma ic segmen a ion o ALS da a has also been applied o delinea ing e y small segmen s wi h a
iew o de ec ing indi idual ee c owns (e.g., [9,10]). In es ima ing s and le el o es a ibu es (a ea
based app oach) he segmen size is la ge han single ee c owns. S ands delinea ed au oma ically on
he basis o emo e sensing image y (i.e., image segmen s) ha e an ad an age o e g id elemen s
(e.g., [11,12]). They can be delinea ed in such a way ha hey exac ly ollow he ac ual s and bo de s,
whe eas he g id elemen s a e spa ially ‘spa se’ in ela ion o he ac ual s and bo de s in he o es and
Remo e Sens. 2011, 3
947
hey do no ollow he bo de lines accu a ely, ins ead o en in e sec ing ees om mo e han one s and
(e.g., [11]). On he o he hand, he g id elemen s a e unambiguously de ined by hei coo dina es, so
he same uni s can be used in subsequen in en o ies.
In delinea ion o he o es s ands, he p ima y inpu a iables a e he mean heigh o he ees and
he ee species composi ion (o dominance). F om he s and delinea ion pe spec i e, s and densi y
usually is a seconda y pa ame e . The heigh o he ees can be de i ed on he basis o he ALS da a.
As s a ed abo e, ALS da a wi h he applied pulse densi y do no se e well he pu pose o ecogni ion
o ee species. The e o e, again, op ical ae ial image y is gene ally used o dis inguishing o es
s ands on he basis o hei ee species composi ion.
The geome ically h ee-dimensional na u e o ALS da a makes i possible o ex ac a la ge numbe
o s a is ical ea u es. When combining he ALS da a wi h ae ial pho og aph da a, one inds ha he
numbe o a ailable ea u es inc eases u he . Consequen ly, he dimensionali y o he ea u e space
inc eases g ea ly, and he da a become spa se in ela ion o he ea u e space dimensions and he
con as be ween objec s in he ea u e space weakens, making, o example, he nea es neighbo
sea ch uns able [13,14]. Fo he es ima ion p ocedu e, he dimensionali y o da a mus he e o e be
educed, and a subse o ea u es wi h good disc imina ion abili y ound. In an ideal case, he analys
would be able o in e he op imal ea u e combina ions om he cha ac e is ics o he independen and
he dependen da a, bu in he case o a physically complex and a ying objec , such as a o es , his is
no possible, and au oma ed ea u e selec ion me hods mus be used.
The objec i es o his s udy we e: (a) o ind a sui able combina ion o lase and ae ial da a ea u es
o au oma ic s and delinea ion; (b) o ind a sui able combina ion o lase and ae ial da a ea u es o
he es ima ion o o es a ibu es; and (c) o compa e g id elemen s and au oma ically delinea ed s and
polygons in he es ima ion o o es a ibu es.
2. Ma e ials and Me hods
2.1. S udy A eas
The lase -scanning and ae ial-image-based es ima ion was es ed in wo s udy a eas. S udy a ea 1
was loca ed in he municipali y o Lammi, in Sou he n Finland (app oxima ely 61°19'N and 25°11'E).
The a ea co e ed app oxima ely 1,800 ha o s a e-owned o es . The ield da a in S udy a ea 1
consis ed o 281 ixed- adius (9.77 m) ci cula ield sample plo s ha we e measu ed in 2007. The
plo s we e loca ed wi h T imble's GEOXM 2005 Global Posi ioning Sys em (GPS) de ice, and he
loca ions we e p ocessed wi h local base s a ion da a, esul ing in an a e age e o o app oxima ely
0.6 m. S udy a ea 2 was in Eas e n Finland, in he municipali ies o Kuopio and Ka ula
(app oxima ely 62°55'N and 27°12'E), co e ing app oxima ely 36,700 ha o mainly p i a ely owned
o es . The ield da a consis ed o 546 ixed- adius (9 m) sample plo s measu ed in 2009. In o de o
co e all ypes o o es , bo h s udy a eas we e s a i ied on he basis o ea lie s and in en o y da a and
he ield sample plo s we e assigned o hese s a a. The loca ion o he s udy a eas and he sample plo
layou s a e p esen ed in Figu e 1.
Remo e Sens. 2011, 3
948
Figu e 1. Loca ion o he s udy a eas in Finland and o he sample plo s wi hin he s udy a eas.
Some di e ences we e e iden be ween he o es cha ac e is ics o he wo s udy a eas. In S udy
a ea 1, he o al g owing s ock was mo e e enly dis ibu ed among he ollowing ee species g oups:
Sco s pine, No way sp uce, and deciduous ees, whe eas S udy a ea 2 was clea ly domina ed by
No way sp uce. Fu he mo e, S udy a ea 2 had a somewha highe a e age s and olume, as well as
g ea e a ia ion in sample plo olumes. The s a is ics o he wo s udy a eas based on he sample plo
measu emen s a e p esen ed in Table 1.
Table 1. Fo es s a is ics o he s udy a eas: a e age, maximum (Max.) and s anda d
de ia ion (S d.) o he sample plo alues.
S udy a ea 1
S udy a ea 2
A e age
Max.
S d.
A e age
Max.
S d.
To al olume, m3/ha
178.7
575.4
115.4
191.3
798.5
131.5
Volume o Sco s pine, m3/ha
69.8
560.6
86.9
47.7
561.8
78.9
Volume o No way sp uce, m3/ha
63.7
575.4
94.9
102.9
739.2
128.0
Volume o deciduous species, m3/ha
45.2
312.0
56.2
40.7
400.4
63.9
Basal a ea, m2/ha
19.8
45.5
10.3
22.3
62.0
11.2
Mean heigh , m
17.0
30.5
6.7
16.9
35.6
6.7
Mean diame e , cm
21.1
50.2
9.4
20.7
60.3
10.0
Remo e Sens. 2011, 3
949
2.2. Remo e Sensing Da a
In S udy a ea 1, he emo e sensing da a consis ed o o ho ec i ied colo -in a ed digi al ae ial
image y (con aining nea -in a ed, ed, and g een bands) wi h a g ound esolu ion o 0.5 m and ALS
da a acqui ed om a lying al i ude o 1,900 m wi h a densi y o 1.8 e u ned pulses pe squa e me e .
In S udy a ea 2, he emo e sensing da a consis ed o o ho ec i ied digi al ae ial image y con aining
nea -in a ed, ed, g een, and blue bands wi h a g ound esolu ion o 0.5 m and ALS da a acqui ed
om a lying al i ude o 2,000 m wi h a densi y o 0.6 e u ned pulses pe squa e me e .
In addi ion o use o he ALS poin da a, he ALS da a we e in e pola ed o a as e image o ma ,
o wo ou pu images: heigh and in ensi y. The as e -image pixel alues o he heigh and in ensi y
images we e calcula ed wi h A cGis Spa ial Analys ools, using in e se dis ance weigh ed (wi h a
powe o 2) in e pola ion based on he wo nea es ALS poin s. The ou pu lase images we e
esampled o a spa ial esolu ion simila o ha o he ae ial images.
2.3. Au oma ic Image Segmen a ion
S and delinea ion was ca ied ou in he s udy a eas ia au oma ic segmen a ion o ae ial images and
ALS da a in e pola ed o as e o ma . The segmen a ion was ca ied ou in wo phases. In he i s
phase, ini ial segmen a ion was pe o med ia a modi ied implemen a ion o he ‘segmen a ion wi h
di ec ed ees’ algo i hm, which employs he local edge g adien [15,16]. The objec i e is o ind all
po en ial segmen bo de s in his phase. The e o e, his me hod ypically p oduces a e y la ge numbe
o small polygons when one is using high- esolu ion emo e sensing da a. In his s udy, he ini ial
segmen a ion was based en i ely on ALS heigh , co esponding mainly o s and heigh [17]
(see Figu e 2(a,b)). P io o he ini ial segmen a ion, he ALS heigh da a we e p e-p ocessed by
Gaussian smoo hing. The size o he smoo hing window was 3 × 3 pixels, and i e sequen ial
smoo hing ope a ions we e used, aimed a diminishing he wi hin-s and a ia ion and emphasizing
be ween-s ands a ia ion.
In he second phase, he ini ial segmen s we e p ocessed ia a egion-me ging algo i hm ha was
guided by pa ame e s such as he desi ed minimum size o he inal segmen s and he simila i y o
dissimila i y o he segmen s o be me ged [16]. The me ging o egions in o he inal segmen s was
ca ied ou on he basis o lase heigh , lase in ensi y, and he NIR/R a io o he ae ial images, wi h
he aim o aking in o accoun also he ee species composi ion o he ini ial segmen s (Figu e 2(c)).
Two au oma ic segmen a ions, wi h minimum segmen sizes o 350 m2 and 0.1 ha, we e ca ied ou in
bo h s udy a eas.

Remo e Sens. 2011, 3
950
Figu e 2. Lase heigh da a, ini ial segmen s based on he lase heigh da a, and inal
segmen s (min. size 0.1 ha) based on a combina ion o lase and ae ial image da a.
Examples om S udy a ea 2.
(a) (b)
(c)
2.4. Ex ac ion o Lase and Ae ial Image Fea u es
Th ee emo e sensing ea u e da a se s we e ex ac ed o each o he s udy a eas. In hese se s, he
emo e sensing ea u es we e alloca ed o each sample plo om a squa e window o a segmen in
which he sample plo was loca ed. The ea u e se G id was ex ac ed om a 20 × 20 m squa e
window cen e ed on each sample plo . The ea u e se Seg350 was ex ac ed om image segmen s
Remo e Sens. 2011, 3
951
whose minimum size was se as 350 m2. Fea u e se Seg1000 was ex ac ed om image segmen s wi h
a minimum size se as 0.1 ha.
The ollowing s a is ical and ex u al ea u es (max. 174) we e ex ac ed om he ae ial images and
ALS heigh and in ensi y o i s pulse da a o each ea u e da a se :
1. A e ages o pixel alues o g id elemen s (20 × 20 m) and image segmen s su ounding
each plo .
2. S anda d de ia ions o pixel alues o blocks, in o which a 32 × 32 pixel window was di ided.
The block sizes co esponded o 1 × 1, 2 × 2, 4 × 4, and 8 × 8 pixels. In addi ion o hese ou
s anda d de ia ion alues, he s anda d de ia ion o hese ou alues was compu ed. Fo he
segmen s, hese we e calcula ed as a e ages o he a ea co e ed [18].
3. Tex u al ea u es based on co-occu ence ma ices o pixel alues [19,20] ex ac ed o g id
elemen s and de i ed o segmen s as a e age alues o he g id elemen s wi hin segmen s:
 Angula second momen
 
q qp ),(
2
 Con as
  
q qp q ),(*)( 2
 Co ela ion
)*(/)*),(**( yx
q yx
qp q

  
 En opy
 
q qp qp )),(log(*),(
 Local homogenei y
  
q q qp ))(1/(),( 2
whe e:
N qM qp /),(),( 
M(q, ) = he co-occu ence ma ix o he equan i ied pixel alues q and
N = he o al numbe o possible pai s in he image window

x ,

x = he mean and s anda d de ia ion o he ow sums o he co-occu ence ma ix

y ,

y = he mean and s anda d de ia ion o he column sums o he co-occu ence ma ix
The ex u al ea u es based on co-occu ence ma ices o pixel alues we e ex ac ed in 4
di ec ions in he ex ac ion window: ho izon ally (0° angle), e ically (90°) and diagonally
(45° and 135°). Pixel lag o 3 me e s was applied in ex ac ing hese ea u es on he basis
o ea lie s udy [7].
In addi ion, he ollowing ea u es we e ex ac ed om he ALS heigh da a only:
4. Heigh s a is ics o he i s and las pulses o all ALS poin s inside he ield plo a ea o he
segmen a ea. These included mean, s anda d de ia ion, maximum, coe icien o a ia ion, heigh s
whe e ce ain pe cen ages o poin s (5, 10, 20, ..., 95) had accumula ed, and pe cen ages o poin s
accumula ed a ce ain ela i e heigh s (5, 10, 20, ..., 95). Only poin s o e 2 m in heigh we e
conside ed in compu a ion o hese a iables. Finally, he pe cen age o poin s o e 2 m in heigh
was included as a a iable.
Remo e Sens. 2011, 3
952
Fo he es ima ion o o es a ibu es, all ae ial image and ALS ea u es we e s anda dized o a
mean o 0 and a s anda d de ia ion o 1. This was done because he o iginal ea u es had e y di e se
scales o a ia ion. Wi hou s anda diza ion, a iables wi h wide a ia ion would ha e had g ea e
weigh in he es ima ion, ega dless o hei co ela ion wi h he es ima ed o es a ibu es.
2.5. Selec ion o Fea u es and Es ima ion o Fo es A ibu es
The k-nea es neighbo (k-nn) me hod was used o es ima ing he o es a iables (e.g., [21–23]).
The es ima ed a iables we e o al olume o g owing s ock; he olume o Sco s pine, o No way
sp uce, and o deciduous species; basal a ea; mean diame e ; and mean heigh . The alue o k was se
o 5 in bo h s udy a eas, which was a comp omise be ween he es ima ion accu acy and he a e aging
allowed in he es ima ion esul s. The k-nn es ima ion me hod ypically has an inc easing end in
accu acy when one aises he alue o k om 1 o 10 (e.g., [23,24]), bu la ge alues o k ypically
esul in e aining less o he o iginal a ia ion in he es ima ion esul s, as well as disappea ance o he
a e s a a in he s udy ma e ial.
Euclidean dis ances we e used o measu e he closeness in he ea u e space, and he nea es
neighbo s we e weigh ed wi h he in e se squa ed dis ances. The accu acy o he es ima es was
calcula ed ia lea e-one-ou c oss- alida ion by compa ing he es ima ed o es a iable alues wi h
he measu ed alues (g ound u h) o he ield plo s. The accu acy o he es ima es was measu ed in
e ms o he ela i e oo mean squa e e o (RMSE) (see Equa ion (1)).
y
RMSE
RMSE *100%
(1)
whe e:
1
)
ˆ
(
1
2





n
yy
RMSE
n
iii
yi = measu ed alue o a iable y on plo i
ŷi = es ima ed alue o a iable y on plo i
y
= mean o he obse ed alues
n = numbe o plo s.
Au oma ic ea u e selec ion was ca ied ou by means o a simple gene ic algo i hm p esen ed by
Goldbe g [25] and implemen ed in he GAlib C++ lib a y [26]. The eason o selec ing his me hod
was i s success in an ea lie s udy by Haapanen and Tuominen [27]. The GA p ocess s a s by
gene a ing an ini ial popula ion o s ings (ch omosomes o genomes), which consis o sepa a e
ea u es (genes). The s ings e ol e du ing a use -de ined numbe o i e a ions (gene a ions). This
e olu ion includes he ollowing ope a ions: selec ing s ings o ma ing by applying a use -de ined
objec i e c i e ion ( he be e , he mo e copies in he ma ing pool), allowing he s ings in he ma ing
pool swap pa s (c oss o e ), causing andom noise (mu a ions) in he o sp ing, and passing he
esul ing s ings o he nex gene a ion.
In he p esen s udy, he s a ing popula ion consis ed o 300 andom ea u e combina ions
(genomes). The leng h o he genomes co esponded o he o al numbe o ea u es in each s ep, and
he genomes con ained a 0 o 1 a posi ion i, deno ing he absence o p esence o image ea u e i. The
Remo e Sens. 2011, 3
953
numbe o gene a ions was 30. The objec i e a iable o be minimized du ing he p ocess was a
weigh ed combina ion o ela i e RMSEs o k-nn es ima es o mean olume, olume o Sco s pine,
No way sp uce olume, olume o deciduous species, mean diame e , and mean heigh , wi h mean
olume ha ing a weigh o 50% and he emaining a iables weigh ed a 10% each. Genomes ha we e
selec ed o ma ing swapped pa s wi h each o he wi h a p obabili y o 80%, p oducing o sp ing.
Occasional mu a ions ( lipping 0 o 1 o ice e sa) we e added o he o sp ing (wi h a p obabili y o
1%). The s ings we e hen passed o he nex gene a ion. The o e all bes genome o he cu en
i e a ion was always passed o he nex gene a ion, also. Fou successi e s eps (all including 30
gene a ions) we e aken, o educe he numbe o ea u es o a easonable minimum. Only ea u es
belonging o he bes genome in each s ep we e included in he nex s ep. Fea u e selec ion was un
sepa a ely o bo h a eas and each ea u e ex ac ion uni (G id, Seg350, and Seg1000). The lis o
selec ed ea u es o all ex ac ion uni s is p esen ed in he appendix.
3. Resul s
In bo h s udy a eas, he ea u es ex ac ed om squa e g id elemen s wo ked be e in es ima ion o
he o es a ibu es han he ea u es ex ac ed om image segmen s did (see Tables 2 and 3).
Fu he mo e, ea u es om image segmen s de i ed wi h a minimum size o 350 m2 pe o med be e
in he es ima ion han did ea u es ex ac ed om la ge segmen s (minimum size: 0.1 ha).
S udy a ea 2 had gene ally be e es ima ion accu acy in compa ison o he da a se s o S udy a ea 1.
The main eason o his is p obably he highe numbe o sample plo s in S udy a ea 2, which yields a
highe numbe o po en ial nea es neighbo s o each sample plo in he k-nn es ima ion.
The e we e la ge di e ences be ween he s udy a eas in he es ima ion accu acy o olumes o he
ee species g oups. Typically, he highes es ima ion accu acy was seen wi h he dominan ee species.
Howe e , he olume o deciduous ees showed be e es ima ion accu acy in compa ison wi h he
mino i y coni e ous ee species g oup, since he p esence o he deciduous ees is mo e easily
ecognizable in he ae ial images.
Table 2. Es ima ion esul s o he ea u e se s: RMSE (%) ela i e o a e age (RMSE
a g.) and s anda d de ia ion (RMSE s d.) o S udy a ea 1.
G id
Seg350
Seg1000
RMSE
A g.
RMSE
S d.
RMSE
A g.
RMSE
S d.
RMSE
A g.
RMSE
S d.
To al olume
27.8
43.0
34.0
52.6
36.6
56.7
Volume o Sco s pine
74.2
59.6
77.1
61.9
99.9
80.4
Volume o No way sp uce
83.9
56.3
87.5
58.7
103.3
69.2
Volume o deciduous species
85.3
68.8
88.7
71.6
93.9
76.3
Basal a ea
25.8
49.8
30.1
58.1
29.8
57.7
Heigh
18.5
46.9
22.4
56.7
25.5
64.7
Diame e
25.5
57.2
27.7
62.1
32.0
71.9
Remo e Sens. 2011, 3
960
 Combined s anda d de ia ion o pixel blocks (1 × 1, 2 × 2, 4 × 4, 8 × 8) o ae ial image NIR
band
 Angula second momen (45° angle) o ae ial image ed band
 Angula second momen (45° angle) o ae ial image g een band
 Homogenei y (135° angle) o ae ial image g een band
 Maximum o i s pulse hi s
 S anda d de ia ion o i s pulse hi s (below 2 m hi s excluded)
 Heigh , whe e 20% o i s pulse hi s ha e been accumula ed (below 2 m hi s excluded)
 Heigh , whe e 80% o i s pulse hi s ha e been accumula ed (below 2 m hi s excluded)
 Pe cen age o i s pulse hi s below 70% o maximum heigh (below 2 m hi s excluded)
 Pe cen age o las pulse hi s abo e 2 m heigh
 Heigh , whe e 20% o las pulse hi s ha e been accumula ed (below 2 m hi s excluded)
 Pe cen age o las pulse hi s below 95% o maximum heigh (below 2 m hi s excluded)
Seg1000
 A e age o ALS heigh
 S anda d de ia ion o ALS in ensi y
 S anda d de ia ion o 2 × 2 pixel blocks o ALS in ensi y
 Con as (135° angle) o ALS heigh
 S anda d de ia ion o ae ial image NIR band
 Con as (135° angle) o ae ial image NIR band
 Con as (90° angle) o ae ial image ed band
 Con as (135° angle) o ae ial image g een band
 Heigh , whe e 90% o i s pulse hi s ha e been accumula ed (below 2 m hi s excluded)
 Heigh , whe e 10% o las pulse hi s ha e been accumula ed (below 2 m hi s excluded)
 Pe cen age o las pulse hi s below 30% o maximum heigh (below 2 m hi s excluded)
S udy a ea 2.
G id
 A e age o ALS heigh
 A e age o ALS in ensi y
 Con as (135° angle) o ALS heigh
 En opy (0° angle) o ALS heigh
 A e age o ae ial image NIR band
 En opy (135° angle) o ae ial image g een band
 En opy (90° angle) o ae ial image NIR band
 Heigh , whe e 10% o i s pulse hi s ha e been accumula ed (below 2 m hi s excluded)
 Heigh , whe e 40% o i s pulse hi s ha e been accumula ed (below 2 m hi s excluded)
 Heigh , whe e 90% o i s pulse hi s ha e been accumula ed (below 2 m hi s excluded)
 Pe cen age o i s pulse hi s below 80% o maximum heigh (below 2 m hi s excluded)
 Pe cen age o las pulse hi s abo e 2 m heigh

Remo e Sens. 2011, 3
961
Seg350
 A e age o ALS heigh
 Angula second momen (135° angle) o ALS in ensi y
 Homogenei y (90° angle) o ALS heigh
 S anda d de ia ion o 4 × 4 pixel blocks o ae ial image blue band
 A e age o ae ial image NIR band
 Angula second momen (90° angle) o ae ial image ed band
 angula second momen (0° angle) o ae ial image NIR band
 En opy (0° angle) o ae ial image g een band
 En opy (0° angle) o ae ial image NIR band
 Pe cen age o i s pulse hi s abo e 2 m heigh
 S d o i s pulse hi s (below 2 m hi s excluded)
 Heigh , whe e 10% o i s pulse hi s ha e been accumula ed (below 2 m hi s excluded)
 Heigh , whe e 40% o i s pulse hi s ha e been accumula ed (below 2 m hi s excluded)
 Heigh , whe e 80% o i s pulse hi s ha e been accumula ed (below 2 m hi s excluded)
 Heigh , whe e 30% o las pulse hi s ha e been accumula ed (below 2 m hi s excluded)
 Pe cen age o las pulse hi s below 10% o maximum heigh (below 2 m hi s excluded)
 Pe cen age o las pulse hi s below 90% o maximum heigh (below 2 m hi s excluded)
Seg1000
 A e age o ALS heigh
 A e age o ALS in ensi y
 Angula second momen (0° angle) o ALS in ensi y
 En opy (135° angle) o ALS heigh
 Homogenei y (0° angle) o ALS heigh
 Homogenei y (90° angle) o ALS heigh
 A e age o ae ial image ed band
 A e age o ae ial image NIR band
 S anda d de ia ion o ae ial image NIR band
 A e age o ae ial image blue band
 S anda d de ia ion o 8 × 8 pixel blocks o ae ial image blue band
 Homogenei y (0° angle) o ae ial image g een band
 Pe cen age o i s pulse hi s abo e 2 m heigh
 Heigh , whe e 50% o i s pulse hi s ha e been accumula ed (below 2 m hi s excluded)
 Heigh , whe e 80% o las pulse hi s ha e been accumula ed (below 2 m hi s excluded)
 Pe cen age o las pulse hi s below 10% o maximum heigh (below 2 m hi s excluded)
 Pe cen age o las pulse hi s below 20% o maximum heigh (below 2 m hi s excluded)
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