© Acta hydrotechnica 21/35 (2003), Ljubljana
ISSN 1581–0267
105
UDK/UDC: 556.52:630*1 Prejeto/Received: 20. 8. 2004
Izvirni znanstveni članek – Original scientific paper Sprejeto/Accepted: 15. 12. 2004
DOLO ČANJE INDEKSA LISTNE POVRŠINE LISTNATEGA GOZDA NA
POVODJU DRAGONJE – 1. DEL: METODE IN MERITVE
ESTIMATING LEAF AREA INDEX OF THE DECIDUOUS FOREST IN
THE DRAGONJA WATERSHED – PART I: METHODS AND MEASURING
Mojca ŠRAJ
V raziskovalni študiji so bile narejene natan čne meritve in analize posameznih komponent
hidrološkega kroga gozda in parametrov vegetacije s sodobno mersko opremo na
eksperimentalnem povodju Dragonje. V ta namen sta bili v sodelovanju z univerzo Vrije
Universiteit iz Amsterdama konec leta 1999 v listnatem gozdu na povodju Dragonje izbrani dve
merski ploskvi, ena na severnem (1419 m
2
) in druga na južnem pobo čju hriba (615 m
2
) nad
soto čjem Dragonje in Rokave. Gozda na severni in južni strani se opazno razlikujeta, tako v
strukturi, gostoti in velikosti dreves kot v sami sestavi. Na obeh ploskvah so bile natan čno dolo čene
lastnosti vegetacije. Na severni strani skoraj polovico dreves predstavlja kraški gaber (Carpinus
orientalis croaticus) (47%), sledi pa mu hrast puhovec (Quercus pubescentis) (34%). Na tej strani
najdemo še jesen (Fraxinus ornus, javor (Sorbus torminolis) in rumeni dren (Cornus Mas). Na južni
strani ve č kot polovico dreves predstavlja jesen (54%), sledi pa mu hrast puhovec (26%). Na tem
pobočju so v manjši meri zastopani še kraški gaber, javor in rumeni dren. Meritve so se za čele
jeseni 2000. Indeks listne površine LAI se je dolo čal po treh metodah: neposredni metodi zbiranja
odpadlega listja, metodi hemisferi čnega fotografiranja in metodi merjenja fotosintetskega
aktivnega sevanja (PAR). Na vsaki ploskvi posebej so se v desetih posebnih košarah redno zbirale
koli čine odpadlega listja, v istih to čkah se je izvajalo tudi hemisferi čno fotografiranje krošenj in 3
serije meritev fotosintetskega aktivnega sevanja PAR. Za potrebe dolo čanja indeksa listne površine
je bila najpogostejšim vrstam dreves dolo čena specifi čna površina listov SLA.
Klju čne besede: indeks listne površine (LAI), specifi čna listna površina (SLA), gozdna hidrologija,
Dragonja
In the research study detailed measurements and analyses of components of the forest hydrological
cycle and vegetational parameters were performed, using up-to-date measuring equipment on the
experimental Dragonja watershed. Within the research project carried out in co-operation with the
Vrije Universiteit, Amsterdam, two plots were selected at the end of 1999 in the deciduous forest of
the Dragonja watershed, one on the north-facing slope (1419 m
2
) and the other on the south-facing
slope (615 m
2
) on the hill above the confluence of the Dragonja River and Rokava River. There are
considerable differences between the forests on the northern and southern slopes, i.e. in terms of
structure, density, tree height and composition. On both plots the characteristics of vegetation were
specified in detail. On the north plot almost half of the trees are hornbeam trees (Carpinus
orientalis croaticus) (47%), followed by pubescent oak (Quercus pubescentis) (34%). The forest
also includes ash (Fraxinus ornus), maple (Sorbus torminolis) and cornelian cherry dogwood
(Cornus Mas). On the south plot more than half of the trees are represented by ash (54%), followed
by pubescent oak (26%). On the plot hornbeam, maple and cornelian cherry dogwood are also
found. The measurements started in autumn 2000. Leaf area index (LAI) was estimated with three
methods: direct litterfall collection method, method of hemispherical photography, and method of
photosynthetically active radiation (PAR). On each plot, litterfall was collected in 10 baskets, and
at the same points the hemispherical photography of canopy and 3 sets of PAR measurements were
performed. For establishing the LAI index the specific leaf area was established for the most
frequent trees.
Key words: leaf area index (LAI), specific leaf area (SLA), forest hydrology, Dragonja

Šraj, M.: Dolo čanje indeksa listne površine listnatega gozda na povodju Dragonje – 1.del: Metode in meritve –
Estimating Leaf Area Index of the Deciduous Forest in the Dragonja Watershed – Part I: Methods and Measuring
© Acta hydrotechnica 21/35 (2003), 105–127, Ljubljana
106
1. UVOD
Hidrologija je veda, ki preu čuje kroženje
vode v naravi, njene pojavne oblike,
razporeditev na zemlji, njeno gibanje ter
fizikalne in kemi čne lastnosti (Chow, 1964).
Ukvarja se predvsem s kroženjem vode na
kopnem, torej z izmenjavo vode med
atmosfero, površino zemlje in vodnimi sistemi
na njej (Brilly in Šraj, 2000).
Gozdna hidrologija preu čuje kroženje vode
na z gozdom poraš čenih površinah. Preu čuje
poti in na čine prehajanja vode iz atmosfere
skozi gozdni ekosistem v tla, podtalnico in
površinske vode ter vra čanje vode nazaj v
ozra čje (Smolej, 1988).
Padavine so glavni vir vode hidrološkega
kroga v gozdu (slika 1). Ve činoma
predstavljata padavine dež ali sneg, v
obmorskih in goratih gozdnih predelih pa se
pojavljajo tudi horizontalne padavine – megla.
Ponavadi velik del padavin, padlih nad
gozdom, prestrežejo drevesne krošnje, manjši
del pa jih pade skozi odprtine med krošnjami
in listi naravnost na tla – prepuš čene padavine.
Koli čina prestreženih padavin (Mikoš et al.,
2002) je odvisna od vegetacijskih in
meteoroloških parametrov:
1. Kapacitete krošnje, le-ta pa je odvisna od
vrste, velikosti, oblike in starosti
vegetacije, površine in orientacije listov
(iglaste vrste dreves prestrezajo 20–40 %,
listnate pa 20–25 % padavin, z ve čjo
starostjo vegetacije delež prestreženih
padavin naraš ča (Geiger et al., 1995)).
2. Gostote vegetacije (z gostoto dreves
prestrežene padavine naraš čajo).
3. Intenzitete, trajanja in pogostosti padavin
(manjša intenziteta ali kratko trajanje
omogo čata večje izhlapevanje s krošenj,
intenziteta izhlapevanja je najve čja na
za četku nevihte, pogostejše padavine
zmanjšujejo prestrežene padavine).
4. Vrste padavin (pri iglastih vrstah dreves
vodni ekvivalent prestreženih snežnih
padavin presega koli čino prestreženih
teko čih padavin).
5. Klimatskih pogojev (višja temperatura
omogo ča ve čje izhlapevanje, veter lahko
znatno vpliva na izhlapevanje).
1. INTRODUCTION
The hydrological science studies the
circulation of water in the nature, its
phenomena, distribution on the earth,
movement and physico-chemical
characteristics (Chow, 1964). It mainly deals
with circulation of water between the
atmosphere, surface of the earth and its water
systems (Brilly and Šraj, 2000).
Forest hydrology studies the circulation of
water in forested areas. It studies the course
and ways of transition of water from the
atmosphere through the forest ecosystem into
the ground, groundwater and surface waters
and its return back to the atmosphere (Smolej,
1988).
Precipitation is the main source of water in
the hydrological circle (Figure 1). Mostly it is
represented by rain and snow, however, in the
coastline and in mountainous, forested areas
horizontal precipitation occurs, i.e. fog.
Usually, most of the precipitation above the
forest is intercepted by canopy, and a smaller
part falls through the gaps between canopy and
leaves to the ground – throughfall. Intercepted
precipitation (Mikoš et al., 2002) depends on
vegetational and meteorological parameters:
1. Canopy capacity, which depends upon the
class of species, size, shape and
vegetational age, area and leaf orientation
(coniferous trees intercept 20–40 %, and
decidous trees 20–25 % precipitation; the
higher the vegetational age, the higher the
intercepted precipitation (Geiger et al.,
1995)).
2.Vegetational density (interception
increases with tree density).
3. Intensity, duration and frequency of
precipitation (smaller intensity or short
duration result in higher evaporation rate
from canopy, intensity of evaporation rate
is highest at the beginning of storms,
frequently occurring precipitation reduces
interception).
4. Precipitation type (with coniferous species
the water equivalent of intercepted snow
exceeds the value of intercepted liquid
precipitation).
5. Climate conditions (higher temperatures
cause higher evaporation rate, the wind can
have high influence over evaporation).
6. Periods in the course of the year (growing

Šraj, M.: Dolo čanje indeksa listne površine listnatega gozda na povodju Dragonje – 1.del: Metode in meritve –
Estimating Leaf Area Index of the Deciduous Forest in the Dragonja Watershed – Part I: Methods and Measuring
© Acta hydrotechnica 21/35 (2003), 105–127, Ljubljana
107
6. Časovnega obdobja v letu (obdobje rasti,
obdobje mirovanja vegetacije).
Ovington (1954) je na podlagi raziskav
zaklju čil, da je koli čina prestreženih padavin
lahko od 6 do 93 odstotkov oziroma da je
glede na zelo razli čne pogoje možen zelo
razli čen delež prestreženih padavin.
Eden pomembnejših parametrov vegetacije
pri procesih, kot so prestrezanje padavin,
izhlapevanje, transpiracija, evapotranspiracija
in kroženje energije, je indeks listne površine.
period, dormant period).
Based upon research, Ovington (1954)
concluded that the quantity of intercepted
precipitation may vary between 6 and 93
percent, i.e. in different conditions a very
different interception rate may be achieved.
The leaf area index is one of the most
important parameters of vegetation in terms of
processes, such as precipitation interception,
evaporation, transpiration, evapotranspiration
and energy circulation.
Slika 1. Gozdni hidrološki krog.

Šraj, M.: Dolo čanje indeksa listne površine listnatega gozda na povodju Dragonje – 1.del: Metode in meritve –
Estimating Leaf Area Index of the Deciduous Forest in the Dragonja Watershed – Part I: Methods and Measuring
© Acta hydrotechnica 21/35 (2003), 105–127, Ljubljana
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Figure 1. Forest hydrological cycle.
2. METODE DOLO ČANJA
INDEKSA LISTNE POVRŠINE
(LAI)
Indeks listne površine (LAI, angl. orig. leaf
area index) je definiran kot skupna enostranska
površina zelenih listov na enoto površine tal
[m
2
/m
2
] (Watson, 1947; Chen et al., 1997;
FAO, 2002). To čnost dolo čitve indeksa listne
površine je lahko kriti čna pri razumevanju in
modeliranju obnašanja posameznega
ekosistema. Medtem ko so za posamezne
vegetacije nizke rasti, kot so npr. poljedelske
rastline, indeksi listne površine že zelo
natan čno določeni (van Dijk in Bruijnzeel,
2001b), pa ostaja dolo čitev listnega indeksa
naravnih gozdnih sestavov še vedno velik
logisti čni problem. Za LAI je zna čilna
prostorska in časovna spremenljvost, ki je v
2. METHODS FOR
ESTIMATING THE LEAF AREA
INDEX (LAI)
Leaf are index (LAI) is defined as the total
one-sided leaf area per unit ground area
[m
2
/m
2
] (Watson, 1947; Chen et al., 1997;
FAO, 2002). Accuracy in estimating LAI may
be critical in understanding and modelling of
the behaviour of a single ecosystem. While
LAI has been quite accurately estimated for
low growing vegetation, such as agricultural
plants (van Dijk in Bruijnzeel, 2001b), the
estimation of leaf area index of natural forest
compositions remains a big logistic problem.
Characteristic of LAI is the spatial and time
variability, which primarily depends on the
type of vegetation and climate. In estimating

Šraj, M.: Dolo čanje indeksa listne površine listnatega gozda na povodju Dragonje – 1.del: Metode in meritve –
Estimating Leaf Area Index of the Deciduous Forest in the Dragonja Watershed – Part I: Methods and Measuring
© Acta hydrotechnica 21/35 (2003), 105–127, Ljubljana
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najve čji meri odvisna od vrste vegetacije in
podnebja. Za dolo čanje LAI raziskovalci
uporabljajo razli čne metode, ki jih v splošnem
delimo na neposredne in posredne.
Neposredne metode so zanesljivejše, vendar
zahtevajo veliko časa in laboratorijskega dela.
Posredne metode, pri katerih se indeks listne
površine dolo či preko merjenja in analize
nekih drugih parametrov, pa so hitrejše in zato
omogočajo tudi zajem večjega prostorskega
vzorca. Ve čina jih temelji na metodi dolo čanja
deleža odprtin v krošnji. Njihova
pomankljivost pa je, da ne lo čijo površine
listov od površine vej in debla.
Neposredne metode za dolo čanje LAI so:
1. Zbiranje in dolo čanje koli čine odpadlega
listja.
2. Sekanje rastlin in dolo čanje celotne listne
površine rastline.
Med posrednimi metodami dolo čanja LAI
pa so najpomembnejše:
1. Merjenje koli čine prehajanja son čnega
sevanja skozi krošnje s posebnimi senzorji.
2. Hemisferi čno fotografiranje krošenj.
3. Alometri čne metode.
4. Dolo čanje LAI s pomo čjo satelitskih
posnetkov.
2.1 METODA ZBIRANJA IN
DOLO ČANJA KOLI ČINE ODPADLEGA
LISTJA
Je zelo natan čna metoda, vendar zahteva
ogromno časa in zamudnega laboratorijskega
dela. Ponavadi se uporablja v kombinaciji z
eno od posrednih metod in služi za njeno
kalibracijo. Uporabljena je bila v mnogih
raziskavah (Bartelink, 1998; Chason et al.,
1991; Clough et al., 2000; Maass et al., 1995;
Nebel et al., 2001, Šraj, 2003). Metoda je
najprimernejša za listopadni gozd, ki ima
omejeno obdobje odpadanja listov. Temelji na
predpostavki, da v košare za zbiranje listja
lovimo naklju čne vzorce odpadajo čega listja
nad njimi. Indeks listne površine se izra čuna iz
mase posušenih listov na enoto površine in
prej dololo čene specifi čne površine listov SLA.
2.2 SEKANJE RASTLIN IN DOLO ČANJE
CELOTNE LISTNE POVRŠINE
RASTLINE
Metoda je uni čevalna in iz tega razloga
LAI, researchers have used several different
methods, which are generally divided into
direct and indirect ones. Direct methods are
more reliable, but they are time-consuming
and require more laboratory work. Indirect
methods, where LAI is established through
measurements and analyses of some other
parameters, are faster and thus enable the
coverage of a larger spatial sample. Mostly,
they are based on the method of estimating the
canopy gap fraction. Their primary weakness
is that they do not distinguish between leaf
area and area of branches and trunks.
Indirect methods for establishing the LAI
are:
1. Litterfall collection and estimation.
2. Destructive sampling method and
estimating the entire leaf area of a plant.
Among the indirect methods of estimating
LAI, the most prominent include:
1. Measuring the transition of solar radiation
through canopy with special sensors.
2. Hemispherical photography of the canopy.
3. Allometric methods.
4. Estimating LAI with satellite imaging.
2.1 LITTERFALL COLLECTION
METHOD
Litterfall collection method is a very
accurate method, but it takes a lot of time-
consuming laboratory work. It is used in
combination with one of the direct methods
and serves for the calibration of the other
methods. It was used in numerous studies
(Bartelink, 1998; Chason et al., 1991; Clough
et al., 2000; Maass et al., 1995; Nebel et al.,
2001, Šraj, 2003). The method is best
applicable in deciduous forests, where there is
a limited period of leaves falling off. It is
based on assumption that random samples of
leaves are collected in the baskets. The LAI is
calculated from the mass of dried leaves over
area unit and previously determined specific
leaf area SLA.
2.2 DESTRUCTIVE SAMPLING
METHOD
This is a destructive type of method and
thus undesirable. It is suitable for example for

Šraj, M.: Dolo čanje indeksa listne površine listnatega gozda na povodju Dragonje – 1.del: Metode in meritve –
Estimating Leaf Area Index of the Deciduous Forest in the Dragonja Watershed – Part I: Methods and Measuring
© Acta hydrotechnica 21/35 (2003), 105–127, Ljubljana
110
nezaželena. Primernejša je recimo za
poljedelske rastline (Chen et al., 1997;
Leuning et al., 1994; Levy in Jarvis, 1999;
Whitford et al., 1995), za gozdove pa
takoreko č neuporabna, saj je koli čina biomase,
ki bi jo bilo treba uni čiti, nedopustno velika.
2.3 MERJENJE KOLI ČINE
PREHAJANJA SON ČNEGA SEVANJA
SKOZI KROŠNJE S POSEBNIMI
SENZORJI
Metoda (Chason et al., 1991; Chen, 1995;
Le Dantec et al., 2000; Law et al., 2001;
Martens et al.; 1993; Maass et al., 1995;
Nilson, 1971; Kodani et al., 2002; McPherson
in Peper, 1998) temelji na dolo čanju deleža
odprtin v krošnji in je zasnovana na štirih
predpostavkah (Li-Cor, 1990):
− listje je črno in kot tako ne odbija in ne
prepuš ča svetlobe;
− posamezni listi so majhni;
− listje je porazdeljeno naklju čno;
− listje je orientirano azimutsko naklju čno.
Delež odprtin zavzema vrednosti med 0
(popolnoma prekrito nebo) in 1 (popolnoma
odprto nebo). Seveda v naravi nobena
vegetacija ne more v celoti izpolnjevati
zgornjih predpostavk. Listje navadno ni
razporejeno naklju čno, temve č je zbrano okrog
vej. Lahko pa govorimo o neki naključni
razporeditvi v sami krošnji. Res pa ima listje
majhno prepustnost in odbojnost. Vse te
ugotovitve so upoštevane pri metodi dolo čanja
LAI s pomo čjo razli čnih senzorjev. Najbolj
razširjen instrument iz te skupine med
raziskovalci in eden novejših je LAI-2000
Plant Canopy Analyser (Li-Cor, 1990). To je
opti čno-elektronska naprava, ki deluje na
principu opti čnega senzorja in simulira
širokokotni objektiv "ribje oko" (angl. orig.
fish-eye). Poleg širokokotne le če ima vgrajen
tudi detektor sevanja. Instrument izra čuna LAI
iz meritev sevanja pod in nad krošnjami.
Uporablja se lahko tudi Ceptometer, ki meri
fotosintetsko aktivno sevanje (angl. orig.
Photosynthetically Active Radiation ali PAR).
PAR je del spektra son čnega sevanja, ki ga
lahko uporabijo zelene rastline, in sicer med
380 in 710 nm valovne dolžine (Diaci, 1999).
LAI se lahko izra čuna iz razmerja med PAR
pod krošnjami in nad krošnjami, koeficienta
pojemanja svetlobe pri prehodu skozi krošnje
posamezne vegetacije ( κ , angl. orig. canopy
crops (Chen et al., 1997; Leuning et al., 1994;
Levy in Jarvis, 1999; Whitford et al., 1995),
but practically unusable for forests, since the
biomass quantity that needs to be destroyed is
inadmissably large.
2.3 MEASURING THE TRANSIMISSION
OF SOLAR RADIATION THROUGH
FOREST CANOPY WITH SPECIAL
SENSORS
The method (Chason et al., 1991; Chen,
1995; Le Dantec et al., 2000; Law et al., 2001;
Martens et al.; 1993; Maass et al., 1995;
Nilson, 1971; Kodani et al., 2002; McPherson
and Peper, 1998) is based on establishing
canopy gap fraction, and has been based on
four assumptions (Li-Cor, 1990):
− the foliage is black and thus does not
reflect or transmit any light;
− the foliage elements are small;
− the foliage is randomly distributed;
− the foliage is azimuthally randomly
oriented.
Canopy gap fraction is estimated from 0
(fully covered sky) to 1 (fully open sky).
Notably, in nature no vegetation can ever fit
into the extreme-type assumptions. The foliage
is usually not random but is collected around
branches. However, we can assume that there
is random distribution in the canopy itself. The
foliage has little transmittance or reflection.
All these observations are taken into
consideration in establishing LAI with
different sensors. One of the most widely used
and recently introduced instruments is LAI-
2000 Plant Canopy Analyser (Li-Cor, 1990).
This is an optical-electronic device functioning
on the principle of an optical sensor and
simulating the fish-eye wide-angle lens.
Besides the wide-angle lens it has a built-in
radiation dector. The instrument calculates LAI
from measurements of radation below and
above the canopy. A Ceptometer can also be
used, measuring the Photosynthetically Active
Radiation (PAR). PAR is part of the solar
radiation spectrum between 380 and 710 nm of
wave length, which can be used by green
plants (Diaci, 1999). LAI can be calculated
between the ratio of incident and transmitted

Šraj, M.: Dolo čanje indeksa listne površine listnatega gozda na povodju Dragonje – 1.del: Metode in meritve –
Estimating Leaf Area Index of the Deciduous Forest in the Dragonja Watershed – Part I: Methods and Measuring
© Acta hydrotechnica 21/35 (2003), 105–127, Ljubljana
111
light extinction coefficient) in Beer-
Lambertovega zakona (Pierce in Running,
1988). Pojemanje son čnega sevanja pri
prehodu skozi vegetacijo je odvisno od
razporeditve in gostote listov ter njihove
prepustnosti:
PAR, canopy light extinction coefficient ( κ )
and the Beer-Lambert law (Pierce in Running,
1988). The canopy light extinction during
transmission through vegetation depends on
distribution and foliage density as well as its
transmittance:
LAI
i p
e Q Q
⋅ −
⋅ =
κ
(1)
Posamezni členi ena čbe so:
p
Q prepuš čeno son čno sevanje,
izmerjeno pod krošnjami [nmol/m
2
/s];
i
Q vpadlo son čno sevanje, izmerjeno nad
krošnjami [nmol/m
2
/s];
κ koeficient pojemanja [-];
LAI  indeks listne površine [-].
Single elements in the equation are:
p
Q transmitted solar radiation, measured
below canopy [nmol/m
2
/s];
i
Q incoming solar radiation, measured
above canopy [nmol/m
2
/s];
κ light extinction coefficent [-];
LAI leaf area index [-].
2.4 HEMISFERI ČNO
FOTOGRAFIRANJE KROŠENJ
Je dolo čanje deleža odprtin v krošnji s
posebno obdelavo in analizo fotografij (Frazer
et al., 2001; McPherson in Peper, 1998; Walter
in Torquebiau, 2000; Chen et al., 1991; van
Gardingen et al., 1999; Levy in Jarvis, 1999;
Hale in Edwards, 2002). Najpogosteje se v
raziskavah uporablja posebna širokokotna le ča
"ribje oko" (fish-eye) z vidnim poljem 180
0
,
lahko pa se uporabijo tudi druge le če. Osnovni
princip metode je, da nebesni svod, ki je
prekrit s krošnjami dreves, projiciramo na
ravno podlago. Pri fotografiranju je zelo
pomembna osvetlitev, da dobimo dober
kontrast med listjem in nebom. Chen s
sodelavci (1991) priporo ča tako nastavitev
osvetlitve, da dobimo belo nebo. Dobili naj bi
jo z osvetlitvijo, pove čano za 1 do 2 stopnji
(1+, 2+), relativno glede na avtomatsko
dolo čeno osvetlitev fotoaparata. Priporo čljivo
je, da slikamo ob jasnem vremenu. Izra čun
LAI iz meritev deleža odprtin preko
hemisferi čnih fotografij so podali mnogi
avtorji, med njimi tudi Nilson (1971) ter Lang
in Yueqin (1986). Delež razpršenega sevanja,
ki pride skozi krošnje, – () θ T – lahko
izrazimo kot razmerje med razpršenim
sevanjem pod krošnjami in nad krošnjami pri
dolo čenem kotu. () θ T imenujemo prepuš čeno
sevanje ali delež odprtin v krošnji. Če so
2.4 HEMISPHERICAL PHOTOGRAPHY
OF CANOPY
Hemispherical photography is a method of
establishing the gap canopy fraction by way of
special processing and photography analysis
(Frazer et al., 2001; McPherson & Peper,
1998; Walter & Torquebiau, 2000; Chen et al.,
1991; van Gardingen et al., 1999; Levy &
Jarvis, 1999; Hale & Edwards, 2002). In
studies, mainly the fish-eye wide-angle lens is
used with 180
0 
field-of-view. The basic
principle of the method is to project the sky
covered with tree canopies onto a level base.
The brightness is of utmost importance in
photography in order to achieve good contrast
between the foliage and sky. Chen et al.
(1991) suggest such settings of brightness, so
that the sky is white. It should be achieved
with brightness plus 1 to 2 levels (1+, 2+),
with regard to the automatic settings of
brightness of the instrument. It is advisable to
take pictures in clear weather conditions.
Calculation of LAI from measuring canopy gap
fraction through hemispherical photography
was proposed by several authors, among
others Nilson (1971) and Lang & Yueqin
(1986). The diffused radiation fraction that
transmits through canopy ( ) θ T can be
expressed as the ratio between diffused
radiation below canopy and above canopy at a
specific angle. ( ) θ T is called transmitted solar
radiation or canopy gap fraction. If the gaps
are large and equally distributed, as with

Šraj, M.: Dolo čanje indeksa listne površine listnatega gozda na povodju Dragonje – 1.del: Metode in meritve –
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© Acta hydrotechnica 21/35 (2003), 105–127, Ljubljana
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odprtine velike ali enakomerno razporejene,
kot npr. pri iglastih drevesih ali pri vegetaciji,
ki raste v vrsti, je prepuš čeno sevanje ve čje kot
skozi listje naravnega gozda, kjer so listi
razporejeni na enaki površini naklju čno, zato
so tudi ena čbe, ki se uporabljajo za razli čne
vrste vegetacij, druga čne. Za naravni listnati
gozd je delež odprtin v krošnjah odvisen od
gostote in orientacije listov ter dolžine poti
skozi krošnje. S pomo čjo Beer-Lambertovega
zakona dobimo:
coniferous trees or with vegetation growing in
a straight line, the transmitted radiation is
higher than the radiation through the foliage of
natural forests, where the foliage is randomly
distributed, thus the equations for different
types of vegetation are different. For natural
deciduous forests the canopy gap fraction
depends on density and orientation of the
foliage as well as on the pathlength through
the canopy. The Beer-Lambert Law proposes
as follows:
                         ()
() () () θ µ θ
θ
H G
e T
⋅ ⋅ −
=             ali/or           ( ) ( ) ()( ) θ µ θ θ H G T ⋅ ⋅ = − ln                  (2)
V ena čbi (2) je:
() θ T delež prepuš čenega son čnega sevanja
ali delež odprtin v krošnji [-];
() θ G delež listov projeciranih v smeri kota
θ [-];
() θ H dolžina poti skozi krošnjo za vsak kot
θ [m];
θ zenitni kot [
0
];
µ gostota listja [m
2
/m
3
].
In Equation (2):
( ) θ T is the fraction of beam penetration or
gap fraction [-];
( ) θ G is the fraction of foliage projected
towards angle θ [-];
( ) θ H is pathlength through the canopy for
each view angle θ [m];
θ is zenith angle [
0
];
µ     is foliage density [m
2
/m
3
].
Ena čbo za gostoto listja je podal Miller
(1967):
Equation for foliage density was proposed
by Miller (1967):
( ) ( )
()
∫
⋅ − =
2
0
sin
ln
2
π
θ θ
θ
θ
µ d
H
T
(3)
Če je () θ H znan, lahko ena čbo (3)
uporabimo za katerokoli obliko krošenj. Za
krošnjo višine (z) velja:
If ( ) θ H is known, then Equation (3) can be
applied to any canopy shape. For a canopy of
size (z) stands:
()
θ
θ
cos
z
H = (4)
z LAI ⋅ = µ (5)
Ena čbo (5) lahko sedaj zapišemo: Equation (5) can be expressed as:
() () θ θ θ θ
π
d T LAI sin cos ln 2
2
0
∫
− = (6)
2.5 ALOMETRI ČNE METODE
Temeljijo na dolo čanju LAI preko osnovnih
2.5 ALLOMETRIC METHODS
Allometric methods are based on estimating
the LAI through the basic physical

Šraj, M.: Dolo čanje indeksa listne površine listnatega gozda na povodju Dragonje – 1.del: Metode in meritve –
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fizikalnih lastnosti vegetacije, kot npr. premer
debla na dolo čeni višini, višina dreves,
biomasa ipd. s predhodno natan čno dolo čenim
odnosom med posameznimi parametri (Chen
et al., 1997; Jackson, 2000; Karlik in McKay,
2002; McPherson in Peper, 1998; Nowak,
1996). Ta odnos se dolo či na reprezentativnem
manjšem vzorcu z eno od neposrednih metod.
2.6 METODA DOLO ČANJA LAI S
POMOČJO SATELITSKIH POSNETKOV
Metoda (Birky, 2001; Fassnacht et al.,
1997; Myneni in Running, 1999) temelji na
analizi satelitskih merjenj IR svetlobe (slika
2). Z naraš čanjem LAI odboj IR svetlobe
zaradi absorbcije pada.
characteristics of vegetation, such as trunk
diameter at certain height, tree size, biomass
etc. with previously accurately determined
relationship between parameters (Chen et al.,
1997; Jackson, 2000; Karlik & McKay, 2002;
McPherson & Peper, 1998; Nowak, 1996).
The relationship is established on a small
representative sample with one of the direct
methods.
2.6 METHOD OF ESTIMATING LAI
WITH SATELLITE IMAGING
The method (Birky, 2001; Fassnacht et al.,
1997; Myneni & Running, 1999) is based on
analysis of satellite measurements of IR light
(Figure 2). By increase of LAI the reflection of
IR light decreases due to absorption.
Slika 2. Globalni LAI, dolo čen s pomo čjo SeaWiFs (angl. orig. sea-viewing wide field-of-view
senzor) za september in oktober 1997 (Myneni in Running, 1999).
Figure 2. Global LAI estimated by SeaWiFs sea-viewing wide field-of-view sensor for September
and October 1997 (Myneni & Running, 1999).
2.7 SPREMENLJIVOST LAI
Med posameznimi ekosistemi se indeks
listne površine zelo spreminja, od manj kot 1
m
2
/m
2
 (aridni predeli) (Scurlock et al., 2001)
do ve č kot 10 m
2
/m
2 
(nekateri iglasti gozdovi)
(Scurlock et al., 2001; Maass et al., 1995;
Roberts, 2000). Dolo čanje indeksa listne
površine je tema mnogih raziskovalcev po
2.7 VARIABILITY OF LAI
Between ecosystems leaf area index has a
high degree of variability, from less than 1
m
2
/m
2
 (arid land) (Scurlock et al., 2001) to
more than 10 m
2
/m
2 
(some coniferous forests)
(Scurlock et al., 2001; Maass et al., 1995;
Roberts, 2000). Estimation of LAI is the
research topic of many researchers around the

Šraj, M.: Dolo čanje indeksa listne površine listnatega gozda na povodju Dragonje – 1.del: Metode in meritve –
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© Acta hydrotechnica 21/35 (2003), 105–127, Ljubljana
114
svetu (preglednica 1). Najve č študij je bilo
narejenih za iglaste gozdove v razli čnih
podnebnih pogojih (Chen et al., 1991; Law et
al., 2001; Thomas in Winner, 2000), manj pa
za listnate (Chason et al., 1991; Le Dantec et
al., 2000; McPherson in Peper, 1998) in
tropske gozdove (Clough et al., 2000; Maass
et al., 1995; Nebel et al., 2001; Schellekens,
2000). Indeks listne površine se lahko zelo
spreminja, tako časovno kot prostorsko. Za
listnati gozd se npr. LAI spreminja sezonsko in
je najve čji v rastni dobi ter najmanjši v
mirujo čem obdobju vegetacije (v Sloveniji
pozimi). Upoštevanje časovnega spreminjanja
je zelo pomembno za razumevanje dobljenih
razlik pri raznih fizikalnih in bioloških
procesih ekosistema (npr. izhlapevanju).
Prostorska spremenljivost indeksa listne
površine je predvsem posledica razli čnih
pogojev za rast. LAI se spreminja tudi znotraj
posameznega ekosistema, odvisno od danih
pogojev. V ve č študijah je bila dokazana
povezava med indeksom listne površine in
razpoložljivimi koli činami vode (Le Dantec et
al., 2000; Maass et al., 1995). Pomanjkanje
vode ne zmanjša le površine listov, temve č
tudi njihovo število. Suša vpliva na površino
listov neposredno z vplivom na rast in
posredno na ravnotežje ogljika, ker zmanjšuje
asimilacijo ogljikovega dioksida skozi
stomatalne pore. Indeks listne površine je po
najnovejših dognanjih (van Dijk in Bruijnzeel,
2001a; b) eden od pomembnejših parametrov
modeliranja izhlapevanja prestreženih padavin.
world (Table 1). Most studies were carried out
for coniferous forests in different climates
(Chen et al., 1991; Law et al., 2001; Thomas
& Winner, 2000), fewer for deciduous forests
(Chason et al., 1991; Le Dantec et al., 2000;
McPherson & Peper, 1998), and tropical
forests (Clough et al., 2000; Maass et al.,
1995; Nebel et al., 2001; Schellekens, 2000).
Leaf area index is highly variable in terms of
time and space. For the deciduous forest the
LAI changes seasonally and is highest during
the growing period and during dormant period
(in Slovenia in winter). Considering the time
variability is important in understanding the
differences in physical and biological
processes of the ecosystem (such as
evaporation). Spatial variability of leaf area
index is mainly the result of different
conditions for growth. LAI also changes within
any ecosystem, depending on the given
conditions. The connection between leaf area
index and available water capacity has been
proven in several studies (Le Dantec et al.,
2000; Maass et al., 1995). The lack of water
does not only reduce the leaf area, but also the
abundance of leaves. Drought exerts a major
influence on leaf area directly by influencing
growth and indirectly on the carbon balance,
since it reduces the assimilation of carbon
dioxide through stomatal pores. According to
latest studies (van Dijk & Bruijnzeel, 2001a;
b), leaf area index should be considered as one
of the most important parameters of modelling
of evaporation of intercepted precipitation.
Preglednica 1. Pregled vrednosti LAI iz razli čnih raziskovalnih študij.
vrsta vegetacije LAI metoda lokacija avtor
listopadni gozd (hrast)
listopadni gozd (bukev)
0,5–7,0
2,9–8,1
opti čna Francija Le Dantec et al. (2000)
listopadni gozd 4,9 neznana Nizozemska Lankreijer et al. (1993)
listopadni gozd (bukev) 7,4 PAR Nizozemska Bartenlink (1998)
listopadni gozd (hrast) 7,6 PAR Nizozemska Bartenlink (1998)
listopadni gozd (hrast) 1,7–2,0 fotografiranj
e
Škotska van Gardingen et al.
(1999)
listopadni gozd (hrast,
hikori)
4,9
3,8
2,9
zbiranje listja
PAR
opti čna
Tennessee Chason et al. (1991)
listopadni gozd (javor,
hrast)
4,4–8,4 zbiranje listja Wisconsin Fassnacht et al. (1997)
listopadni gozd (hrast) 4,4 sekanje Kalifornija Karlik & McKay (2002)

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© Acta hydrotechnica 21/35 (2003), 105–127, Ljubljana
115
listopadni gozd
(odprti)
3,1–3,7
3,3
0,9
3,7
3,4
sekanje
opti čne
PAR
fotografiranj
e
alometri čna
Kalifornija McPherson & Peper
(1998)
listnati gozd (nasad) 3,3
3,2–5,2
2,1–3,2
2,7–6,6
zbiranje listja
PAR
opti čna
fotografiranje
Kalifornija Martens et al. (1993)
listnati gozd
(mangrovec)
3,3–4,9 zbiranje listja Vietnam Clough et al. (2000)
mešani gozd 1,6–4,4 zbiranje listja Wisconsin Fassnacht et al. (1997)
nasad oljk 0,3–4,8 zbiranje listja Španija Gomez et al. (2001)
listnati zimzeleni gozd
(evkaliptus)
2,7 neznana Portugalska Valente et al. (1997)
listnati zimzeleni gozd
(evkaliptus)
1,1
1,1
sekanje
alometri čna
Avstralija Whitford et al. (1995)
listnati zimzeleni gozd
(lovor)
7,8 neznana Tenerife Aboal et al. (1999)
iglasti gozd 5,1–7,6 PAR Nizozemska Bartenlink (1998)
iglasti gozd 2,3 neznana JZ Francija Gash et al. (1995)
iglasti gozd 1,5–4 neznana Francija Loustau et al. (1992)
iglasti gozd 2,3 neznana Francija Lankreijer et al. (1993)
iglasti gozd 3,2 neznana Portugalska Valente et al. (1997)
iglasti gozd 4,8–9,0
3,3–5,3
2,9–7,0
PAR
opti čna
fotografiranje
Kalifornija Martens et al. (1993)
iglasti gozd 3,6–4,8 fotografiranje Kanada Frazer et al. (2001)
iglasti gozd 1,6–4,8
2,0–6,3
opti čne
alometri čne
Kanada Chen et al. (1997)
iglasti gozd 1,5–2,5
1,7–3,3
sekanje
opti čna
Kanada Chen (1996)
iglasti gozd 3,8–4,6
3,8–4,5
opti čna
fotografiranje
Kanada Chen et al. (1991)
iglasti gozd 8,2–9,3 alometri čna Washington Thomas & Winner
(2000)
iglasti gozd 1,3
1,7
3,7
3,5
opti čna
PAR
alometri čna
zbiranje listja
Oregon Law et al. (2001)
iglasti gozd 1,4–2,5 zbiranje listja Wisconsin Fassnacht et al. (1997)
tropski listnati gozd 4,2
5,1
zbiranje listja
PAR
Mehika Maass et al. (1995)
tropski gozd (akacija) 6,8–8,1 neznana Indonezija Bruijnzeel & Wiersum
(1987)
tropski deževni gozd 4,2–4,4 zbiranje listja Peru Nebel et al. (2001)

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© Acta hydrotechnica 21/35 (2003), 105–127, Ljubljana
116
Table 1. Overview of LAI values from different research studies.
Forest type LAI Method Location Author
Deciduous forest
(oak)
Deciduous forest
(beech)
0,5–7,0
2,9–8,1
LAI-2000 France Le Dantec et al. (2000)
Deciduous forest 4,9 unknown Netherlands Lankreijer et al. (1993)
Deciduous forest
(beech)
7,4 PAR Netherlands Bartenlink (1998)
Deciduous forest
(oak)
7,6 PAR Netherlands Bartenlink (1998)
Deciduous forest
(oak)
1,7–2,0 photography Scotland van Gardingen et al. (1999)
Deciduous forest (oak,
hickory)
4,9
3,8
2,9
litterfall
PAR
optical
Tennessee Chason et al. (1991)
Deciduous forest
(maple, oak)
4,4–8,4 litterfall Wisconsin Fassnacht et al. (1997)
Deciduous forest
(oak)
4,4 destructive California Karlik & McKay (2002)
Deciduous forest
(open)
3,1–3,7
3,3
0,9
3,7
3,4
destructive
optical
PAR
photography
allometric
California McPherson & Peper (1998)
Deciduous forest
(orchard)
3,3
3,2–5,2
2,1-3,2
2,7-6,6
litterfall
PAR
optical
photography
California Martens et al. (1993)
Deciduous forest
(mangrove)
3,3–4,9 litterfall Vietnam Clough et al. (2000)
Mixed forest 1,6–4,4 litterfall Wisconsin Fassnacht et al. (1997)
Olive trees orchard 0,3–4,8 litterfall Spain Gomez et al. (2001)
Deciduous evergreen
forest (eucalyptus)
2,7 unknown Portugal Valente et al. (1997)
Deciduous evergreen
forest (eucalyptus)
1,1
1,1
destructive
allometric
Australia Whitford et al. (1995)
Deciduous evergreen
forest (laurel)
7,8 unknown Tenerife Aboal et al. (1999)
Coniferous forest 5,1–7,6 PAR Netherlands Bartenlink (1998)
Coniferous forest 2,3 unknown SW France Gash et al. (1995)
Coniferous forest 1,5–4 unknown France Loustau et al. (1992)
Coniferous forest 2,3 unknown France Lankreijer et al. (1993)
Coniferous forest 3,2 unknown Portugal Valente et al. (1997)
Coniferous forest 4,8–9,0
3,3–5,3
2,9–7,0
PAR
optical
photography
California Martens et al. (1993)
Coniferous forest 3,6–4,8 photography Canada Frazer et al. (2001)
Coniferous forest 1,6–4,8
2,0–6,3
optical
allometric
Canada Chen et al. (1997)

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© Acta hydrotechnica 21/35 (2003), 105–127, Ljubljana
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Coniferous forest 1,5–2,5
1,7-3,3
destructive
optical
Canada Chen (1996)
Coniferous forest 3,8–4,6
3,8–4,5
optical
photography
Canada Chen et al. (1991)
Coniferous forest 8,2–9,3 allometric Washington Thomas & Winner (2000)
Coniferous forest 1,3
1,7
3,7
3,5
optical
PAR
allometric
litterfall
Oregon Law et al. (2001)
Coniferous forest 1,4–2,5 litterfall Wisconsin Fassnacht et al. (1997)
Tropical deciduous
forest
4,2
5,1
litterfall
PAR
Mexico Maass et al. (1995)
Tropical forest
(acacia)
6,8–8,1 unknown Indonesia Bruijnzeel & Wiersum
(1987)
Tropical rain forest 4,2–4,4 litterfall Peru Nebel et al. (2001)
3. MERITVE LAI NA
RAZISKOV ALNIH PLOSKV AH
V sodelovanju z univerzo iz Amsterdama
sta bili konec leta 1999 izbrani dve merski
raziskovalni ploskvi v gozdu, ena na severnem
pobo čju v podpovodju Rokave (1420 m
2
),
druga na južnem pobo čju v podpovodju
Dragonje (615 m
2
), obe približno enako (2500
m) oddaljeni od vasice Labor, na nadmorski
višini približno 200 m in v majhni medsebojni
oddaljenosti (400 m) (slika 3). Na obmo čju
platoja Pleševica, med vasico Labor in
izbranima merskima ploskvama je lepo viden
časovni potek zaraš čanja z gozdom. Z
oddaljevanjem od Laborja sre čamo tako na
platoju 4–5, 10, 15–20 let stare sestoje in na
koncu 30–35 let star gozd na strmih pobo čjih
(okrog 30
0
), ki se spuš čajo do dolin Rokave in
Dragonje in na katerih sta bili izbrani
omenjeni merski ploskvi (Šraj, 2003).
Zaradi dolo čitve lastnosti in sestave obeh
gozdnih ploskev, so bila na vsaki od njiju
oštevil čena vsa drevesa s premerom na višini
1,35 m (DBH, angl. orig. tree diameter at
breast height) ve čjim od 3 cm. Vsakemu
drevesu posebej je bila nato dolo čena vrsta in
premer na višini 1,35 m z merskim trakom
natan čnosti 0,1 cm (te Linde, 2001). Dolo čene
so bile štiri najpogostejše vrste dreves: hrast
(Quercus pubescentis), gaber (Carpinus
orientalis croaticus), javor (Sorbus torminolis)
in jesen (Fraxinus ornus) in kasneje dodan še
3. MEASURING LAI ON
RESEARCH PLOTS
In co-operation with the Vrije Universiteit,
Amsterdam, two measuring research plots
were chosen at the end of 1999, one on the
northern slope of the subwatershed of the
Rokava (1420 m
2
), the other on the southern
slope in the subwatershed of the Dragonja
(615 m
2
), both situated approximately the
same distance from the village of Labor, at an
altitude of 200 m and short mutual distance
(400 m) (Figure 3). In the area of the Pleševica
plateau, between the village of Labor and the
chosen plots the temporal course of forestation
is well evident. By increasing the distance
from Labor, forests are 4–5, 10, 15–20 years
old and in the steepest slopes (around 30
0 
) 30–
35 years old, descending into the valleys of the
Rokava and Dragonja Rivers and into the sites
of the chosen plots (Šraj, 2003).
Due to establishing the features and
composition of both forest plots, all trees with
a diameter of more than 3 cm at 1.35 m breast
height (DBH) were numbered. Each tree was
classified according to its species and diameter
at the height of 1.35 m measured with
measuring tape of 0.1 cm accuracy (te Linde,
2001). The four most frequent tree species
were estimated: pubescent oak (Quercus
pubescentis), hornbeam (Carpinus orientalis
croaticus), maple (Sorbus torminolis), and ash
(Fraxinus ornus); cornelian cherry dogwood

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© Acta hydrotechnica 21/35 (2003), 105–127, Ljubljana
118
rumeni dren (Cornus Mas). Na severni ploskvi
je bila vsakemu drevesu s klinometrom in
merskim trakom izmerjena tudi višina. Na
južni ploskvi pa je gostota vegetacije
prevelika, zato ni bilo mogo če lo čiti
posameznih drevesnih krošenj. Povpre čna
višina dreves na južni strani je bila ocenjena
vizualno.
(Cornus Mas) was added later. On the north
plot, height was measured with clinometer and
measuring tape. On the south plot, however,
vegetation density was too high, thus tree
canopies could not be distinguished from one
another. Mean tree height on the south plot
was estimated visually.
Slika 3. Položaj raziskovalnih ploskev (vir: Interaktivni atlas Slovenije).
Figure 3. Position of research plots (source: Interactive Atlas of Slovenia).
3.1 SEVERNA RAZISKOVALNA
PLOSKEV
Severna gozdna ploskev ima površino 1419
m
2
. Na površini je bilo septembra 2000
naštetih 117 dreves s premerom (DBH na
1,35m) ≥ 3 cm (preglednica 2). Gostota dreves
je torej 0,08 drevesa na kvadratni meter.
Skoraj polovico dreves predstavlja kraški
gaber (Carpinus orientalis croaticus) (47%),
sledi hrast puhovec (Quercus pubescentis)
(34%), jesen (Fraxinus ornus) (5%), javor
(Sorbus torminolis) (3%) in ostale vrste (11%).
Med ostalimi vrstami prevladuje rumeni dren
3.1 THE NORTH PLOT
The surface area of the north plot is 1419
m
2
. There were 117 trees with a diameter at
breast height (DBH at 1.35 m) ≥ 3 cm, counted
in September 2000 (Table 2). This resulted in
a stem density of 0.08 trees per square metre
of forest floor. Hornbeam (Carpinus orientalis
croaticus) represents almost half of all trees
(47 %), followed by pubescent oak (Quercus
pubescentis) (34 %), ash (Fraxinus ornus)
(5 %), maple (Sorbus torminolis) (3 %), and
other species (11 %). Among other species,
cornelian cherry dogwood (Cornus Mas)

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(Cornus Mas), ki je bil izlo čen naknadno. Kot
podrastje se v ve čji meri pojavlja bode ča
lobodika (Ruscus aculeatus). Povpre čna višina
dreves je 12,3 ( ± 5,1) m in povpre čen premer
vseh vrst dreves (DBH na 1,35 m) 13,8 ( ±
7,83) cm (preglednica 2). Povpre čen premer
hrastovih dreves je 17,6 ( ± 10,3) cm in
gabrovih 10,9 ( ± 4,3) cm (te Linde, 2001).
prevails, which was added subsequently. The
undergrowth is dominated by butcher’s broom
(Ruscus aculeatus). Mean tree height was 12.3
m ( ± 5.1) and mean DBH of all species 13.8 ( ±
7.83) cm (Table 2) (Te Linde, 2001). The
mean DBH of oak trees was 17.6 ( ± 10.3) cm
and hornbeam trees 10.9 ( ± 4.3) cm (te Linde,
2001).
Preglednica 2. Zna čilnosti posameznih vrst dreves na severni raziskovalni ploskvi.
hrast gaber javor jesen drugo skupaj
št. dreves 40 55 3 6 13 117
št. dreves [%] 34.19 47.01 2.56 5.13 11.11 100.00
gostota dreves
[dreves/m
2
]
0.0282 0.0388 0.0021 0.0042 0.0092 0.0824
povp. višina [m] 13.82 10.78 13.75 11.02 14.46 12.32
st.dev. višine [m] 5.74 4.18 8.16 1.27 5.05 5.06
povp. DBH [cm] 17.67 10.92 15.12 11.03 15.07 13.80
st.dev. DBH [cm] 10.25 4.30 8.73 4.93 7.10 7.83
Table 2. Characteristics of trees on the north plot.
oak hornbeam maple ash other total
No. of trees 40 55 3 6 13 117
No. of trees [%] 34.19 47.01 2.56 5.13 11.11 100.00
Stem density
[trees/m
2
]
0.0282 0.0388 0.0021 0.0042 0.0092 0.0824
Mean height [m] 13.82 10.78 13.75 11.02 14.46 12.32
St. dev. of height [m] 5.74 4.18 8.16 1.27 5.05 5.06
Mean DBH [cm] 17.67 10.92 15.12 11.03 15.07 13.80
St. dev. of DBH [cm] 10.25 4.30 8.73 4.93 7.10 7.83
3.2 JUŽNA RAZISKOVALNA PLOSKEV
Južna gozdna ploskev ima površino 615 m
2
,
kar je približno polovica velikosti severne
ploskve. Kljub manjši površini pa število
dreves na južni ploskvi (191) presega število
dreves na severni ploskvi (preglednica 3).
Gostota dreves je ve č kot trikrat ve čja (0,31
dreves na kvadratni meter) od gostote na
severni ploskvi. Višina vsakega posameznega
drevesa ni bila izmerjena zaradi prevelike
gostote dreves, bila pa je ocenjena na 8 m v
povpre čju. Ve č kot polovico dreves predstavlja
jesen (Fraxinus ornus) (54 %), sledi hrast
(Quercus pubescentis) (26 %), kraški gaber
3.2 THE SOUTH PLOT
The south plot has an area of 615 m
2
 or
approximately half the size of the north plot.
Nevertheless, the number of counted trees on
the south plot (191) exceeded the number of
trees in the north plot (Table 3). The stem
density was about three times higher (0.31
trees per square metre) than in the north plot.
The tree height could not be measured for each
separate tree because of the high tree density
but it was estimated at 8 m in average. More
than half of the trees are ash trees (Fraxinus
ornus) (54 %), followed by oak (Quercus
pubescentis) (26 %), hornbeam (Carpinus

Šraj, M.: Dolo čanje indeksa listne površine listnatega gozda na povodju Dragonje – 1.del: Metode in meritve –
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© Acta hydrotechnica 21/35 (2003), 105–127, Ljubljana
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(Carpinus orientalis croaticus) (4 %), javor
(Sorbus torminolis) (2 %) in ostale vrste
(14 %). Tudi tu med ostalimi vrstami
prevladuje rumeni dren (Cornus Mas), ki je bil
izlo čen naknadno. Povpre čen premer vseh vrst
dreves (DBH na 1,35 m) je 7,14 ( ± 4,84) cm.
Povpre čen premer (DBH) jesenovih dreves je
4,7 ( ± 2,7) cm in hrastovih 13,2 ( ± 4,0) cm (te
Linde, 2001). Višina in premer dreves na južni
ploskvi sta precej manjša kot na severni strani.
orientalis croaticus) (4 %), maple (Sorbus
torminolis) (2 %), and other species (14 %).
Among other species the cornelian cherry
dogwood (Cornus Mas) prevails, which was
added subsequently. The mean DBH (at 1.35
m) of all species was 7.14 ( ± 4.84) cm. The
mean DBH for ash trees was 4.7 ( ± 2.7) cm
and for the oak trees 13.2 ( ± 4.0) cm (te Linde,
2001). Tree height and tree diameter on the
south plot are both lower than in the north plot.
Preglednica 3. Zna čilnosti posameznih vrst dreves na južni raziskovalni ploskvi.
hrast gaber javor jesen drugo skupaj
št. dreves 50 7 4 104 26 191
št. dreves [%] 26.18 3.66 2.09 54.45 13.61 100.00
gostota dreves
[dreves/m
2
]
0.081 0.011 0.007 0.169 0.042 0.311
povp. DBH [cm] 13.17 5.80 6.21 4.69 5.55 7.14
st. dev. DBH [cm] 4.02 3.61 2.57 2.70 3.53 4.84
Table 3. Characteristics of tree species on the south plot.
oak hornbeam maple ash other total
No. of trees 50 7 4 104 26 191
No. of trees [%] 26.18 3.66 2.09 54.45 13.61 100.00
Stem density
[trees/m
2
]
0.081 0.011 0.007 0.169 0.042 0.311
Mean height [m] 13.17 5.80 6.21 4.69 5.55 7.14
St. dev. of height [m] 4.02 3.61 2.57 2.70 3.53 4.84
3.3 MERJENJE LAI NA
RAZISKOVALNIH PLOSKVAH
Na vsaki od merskih ploskev so se poleg
meritev posameznih komponent gozdnega
hidrološkega kroga izvajale tudi tri razli čne
meritve indeksa listne površine.
3.3.1  Dolo čitev specifi čne listne površine
SLA
Za izra čun indeksa listne površine po
neposredni metodi je potrebno najprej dolo čiti
specifi čno površino listov SLA. SLA je odnos
med površino in maso suhih listov oziroma je
površina listov na enoto mase [m
2
/kg]. SLA se
je dolo čila za pet najbolj tipi čnih drevesnih
vrst na vsaki ploskvi posebej (hrast, gaber,
3.3 MEASURING LAI ON RESEARCH
PLOTS
Besides measuring the single elements of
forest hydrological cycle, on each plot three
different measurements of LAI were
performed.
3.3.1 Specific leaf area estimation SLA
For calculating leaf area index, first the
specific leaf area SLA should be determined.
SLA is the relationship between area and mass
of dry leaves, i.e. SLA is leaf area over mass
unit [m
2
/kg]. SLA was determined for five
most typical tree species for each plot
separately (oak, horbneam, mapel, ash,

Šraj, M.: Dolo čanje indeksa listne površine listnatega gozda na povodju Dragonje – 1.del: Metode in meritve –
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© Acta hydrotechnica 21/35 (2003), 105–127, Ljubljana
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jesen, javor, rumeni dren) poleg tega pa tudi za
kategorijo “ostali listi” ter za droben listni
material. Za vsako vrsto dreves je bilo
nabranih približno 100–300 že razvitih svežih
listov. Še svežim listom se je dolo čila njihova
površina. Površina je bila dolo čena s pomo čjo
skeniranja posameznih listov (resolucija 300
dpi) in digitalno obdelavo ter analizo dobljenih
slik. Posamezne zbirke listov so se potem
posušile, najprej na zraku, potem pa še v
sterilizatorju na 70 
0
C (Sterilizator S-45, UL
Biotehniška fakulteta) do konstantne mase.
Posušeno listje se je stehtalo (tehtnica
Sartorius BP 310 S, d = 0,001g, UL
Biotehniška fakulteta) do 0.001g natan čno
(Šraj, 2003). Z izra čunom razmerja med
površino listov in maso posušenih listov pa se
je dolo čilo SLA za vsako vrsto dreves posebej.
3.3.2 Zbiranje in dolo čanje koli čine
odpadlega listja
Zbiranje odpadlega listja se je izvajalo 2
leti, in sicer v sezoni 2000/01 (Vrije
Universiteit Amsterdam) ter 2001/02, pri
čemer so se v drugem letu meritve izvajale
pogosteje in natan čneje. Izlo čena je bila nova
drevesna vrsta, rumeni dren. Listje se je na
vsaki ploskvi posebej zbiralo v 10 košarah
površine 0,2 m
2 
(0,55 * 0,37 m), prekritih z
mrežo (slika 4), in ro čno pobiralo približno
dvakrat mese čno. Mreža je bila rahlo napeta na
košare približno 30 cm od tal, kar je
prepre čevalo dostop razli čnim listojedim
živalim, hkrati pa zagotavljalo tudi dreniranje
padavin, da ujeto listje ni gnilo, in
zmanjševalo možnost odpihovanja listja.
Košare so bile po ploskvah razporejene
naklju čno in se med raziskavo niso premikale.
Vsaka košara je bila oštevil čena, in sicer od 1
do 10 na severni ploskvi in od 11 do 20 na
južni ploskvi. Pri vsakem pobiranju so se
vzorci shranjevali v plasti čne vre čke z oznako
številke košare in datumom. Pobrani vzorci iz
posameznih košar so se vsaki č posušili, najprej
na zraku, nato pa v sterilizatorju pri 70 
0
C
(Sterilizator S-45, UL Biotehniška fakulteta;
slika 27a) do konstantne teže. Posušeno listje
se je potem razvrš čalo po posameznih vrstah
dreves za vsako košaro posebej in stehtalo
(tehtnica Sartorius BP 310 S, d = 0,001g, UL
Biotehniška fakulteta; slika 27b) do 0,001 g
dogwood), and also for the category “other
leaves” and fine foliage material. For each tree
species, around 100–300 of developed new
leaves were gathered. The leaf area was
estimated for fresh leaves. Scanning of fresh
leaves (with 300 dpi resolution), digital
processing and analysis of images was
performed. Collected sets of leaves were then
dried, first air-dried and then oven-dried at
70
0
C (Sterilizer S-45, UL Biotehnical Faculty)
to the constant mass. The dried leaves were
weighed (scale Sartorius BP 310 S, d =
0.001 g, UL Biotehnical Faculty) up to 0.001 g
accuracy (Šraj, 2003). By calculating the
relationshop between leaf area and mass of
dried leaves SLA was estimated for each
species separately.
3.3.2 Litterfall collection and estimation
Litterfall collection was performed for 2
years, i.e. in seasons 2000/01 (Vrije
Universiteit Amsterdam) and 2001/02;
measurements during the second season were
performed more frequently and accurately.
The new tree species, the cornelian cherry
dogwood, was excluded from the
measurements. The leaves were collected on
each plot separately in 10 baskets of an area of
0.2 m
2 
(0.55 * 0.37 m), which were covered
with a net (Figure 4), and manually collected
about twice monthly. The net was slightly
tensioned on the baskets, approximately 30 cm
above the ground, which prevented access to
various foliage consumers and at the same
time ensured drainage to prevent decay and
reduced the possibility of leaves being blown
away. Baskets were randomly distributed on
the plots and were not moved during the study.
Each basket was numbered, i.e. from 1 to 10
on the north plot and from 11 to 23 on the
south plot. During each collection the samples
were stored into plastic bags with an indication
of the basket number and date. Each time, the
collected samples were dried, first air-dried
and then oven-dried at 70
0
C (Sterilizer S-45,
UL Biotehnical Faculty, Figure 27a) to their
constant weight. The dried leaves were then
classified according to their species for each
basket separately, and weighed (scale Sartorius
BP 310 S, d = 0.001g, UL Biotehnical Faculty,

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natan čno. Posebej se je izlo čalo in tehtalo tudi
semena oz. plodove ter odpadle vejice. Iz
koli čine odpadlega listja [kg/m2] in specifi čne
površine listov SLA s e j e i z r a čunal indeks
listne površine LAI (Šraj, 2003).
Figure 27b) up to 0.001 g of accuracy. Seeds,
fruits and twigs were screened and weighed
separately. From the quanity of fallen leaves
[kg/m2] and specific leaf area SLA, leaf area
index LAI was calculated (Šraj, 2003).
Slika 4. Košara za zbiranje odpadlega listja.
Figure 4. Basket for collecting litterfall.
3.3.3 Hemisferi čno fotografiranje
Fotografiranje drevesnih krošenj se je
izvajalo na vsaki ploskvi v istih desetih to čkah,
kjer so bile postavljene tudi košare za zbiranje
listja za dolo čitev indeksa listne površine.
Izvajalo se je 2 leti, in sicer v sezoni 2000/01
(Vrije Universiteit Amsterdam) ter 2001/02. V
prvi sezoni so bile krošnje slikane petkrat v
obdobju od 27. 9. 00 do 26. 10. 00. V drugi
sezoni pa prav tako petkrat le v daljšem
časovnem obdobju (7. 9. 01 do 9. 1. 02).
Uporabljen je bil fotoaparat Minolta z 28 mm
objektivom. Fotoaparat se je pritrdil na stojalo
in v vsaki to čki postavil v vodoravno lego ter
usmeril proti severu. Fotografiralo se je z
osvetlitvijo, pove čano za 2 stopnji (2+),
relativno glede na avtomatsko dolo čeno
osvetlitev fotoaparata pod krošnjami, da bi
dobili čim boljši kontrast med nebom in
krošnjami (Chen et al., 1991).
3.3.3 Hemispherical photography
For estimating LAI, photography of tree
canopies was performed on each plot at the
same ten points, where the baskets for leaf
collection were positioned. The measurements
were performed for 2 years, i.e. in seasons
2000/01 (Vrije Universiteit Amsterdam) and
2001/02. During the first season, the canopy
was photographed 5 times in the period from
Sept. 27, 2000, to Oct. 26, 2000. In the second
season, the canopy was also photographed 5
times, however, during a longer time period
(from Sept. 9, 2001, to Jan. 9, 2002). Minolta
camera with a 28 mm lens was used. The
camera was fixed onto a stand, positioned
horizontally at each point and directed towards
north. To achieve the optimal contrast between
the sky and canopy, the brightness was plus 2
(2+) relative to the automatically set brightness

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© Acta hydrotechnica 21/35 (2003), 105–127, Ljubljana
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V ve čini študij je za hemisferično
fotografiranje uporabljena posebna
širokokotna le ča ″ribje oko" (fish-eye) z
vidnim poljem 180
0
 (Diaci et al., 1999; Frazer
et al., 2001; Martens et al., 1993; Silbernagel
in Moeur, 2001; Walter in Torquebiau, 2000).
Z njo lahko preslikamo krošnje iz poloble v
naravi v krog na ravnini. Ker take le če nismo
imeli na razpolago, smo uporabili le čo z ožjim
vidnim poljem. Kakorkoli pa je Chen s
sodelavci (1997) v svoji raziskavi ugotovil, da
lahko pri velikih zenitnih kotih pride do
podcenjevanja deleža odprtin v krošnji, kot
posledica premajhne kotne resolucije in
temnejšega neba v bližini horizonta. Oboje
skupaj je vzrok, da pri obdelavi fotografije
majhne odprtine pri velikih zenitnih kotih
izgubimo.
Izdelane fotografije so bile potem skenirane
z resolucijo 300 dpi in obdelane s programom
Paint Shop Pro. Na vsaki fotografiji posebej se
je ro čno z razli čnimi orodji programa
postopoma iskala meja med nebom in krošnjo,
na koncu pa se je fotografija spremenila v 1-
bitno sliko ( črno-belo). S pomo čjo histograma
je bil potem dolo čen delež belih oziroma črnih
to čk in s tem delež odprtin v krošnji. Ta se je
potem uporabil za izra čun prepusnosti krošenj
za razli čne zenitne kote. Pri širokokotnih le čah
se ponavadi za izra čun LAI uporabi pet
zenitnih kotov (7, 23, 38, 53 in 68
0
; Chason et
al., 1991; Chen et al., 1991). Ker je bil pri nas
uporabljen 28 mm objektiv, sta bila pri
izra čunu uporabljena le zenitna kota 7
0
 in 23
0
(Šraj, 2003).
3.3.4 Fotosintetsko aktivno sevanje (PAR)
Meritve PAR so bile narejene s Sunflect
Ceptometrom (Vrije Universiteit Amsterdam).
Merilo se je sevanje nad in pod krošnjami na
južni ploskvi oktobra 2000. Na severni ploskvi
meritev ni bilo mogo če izvesti, ker skozi
krošnje dreves ni prehajalo skoraj ni č son čne
svetlobe. PAR pod krošnjami se je merilo v
istih desetih to čkah, kjer so bile posnete tudi
fotografije, nad krošnjami pa na bližnji gozdni
jasi. Narejene so bile tri meritve leta 2000
(Vrije Universiteit Amsterdam), in sicer 16.,
21., in 22. oktobra v jasnih vremenskih
razmerah. Vsaka meritev je v povpre čju
obsegala 80 individualnih meritev na 80
fotodiodah Ceptometra, za 8 azimutnih
of the camera below canopy (Chen et al.,
1991).
In most studies a special wide angle fish-
eye lens is used with 180
0
 field-of-view (Diaci
et al., 1999; Frazer et al., 2001; Martens et al.,
1993; Silbernagel and Moeur, 2001; Walter
and Torquebiau, 2000). The lens helps us copy
the canopy from the hempishere in the nature
into a circle in plane. Since no such lens was at
our disposal, we used a lens with a narower
field-of-view. However, Chen et al. (1997)
established that in large zenith angles an
underestimation of the gap canopy fraction can
occur as a consequence of too small angle
resolution and darker sky near the horizon.
This is the reason that during processing the
small gaps with large zenith angles are lost.
The photographs are then scanned with a
300 dpi resolution and processed with Paint
Shop Pro. By using different program tools, on
each separate photo the border between sky
and canopy was determined manually, and at
the end the photo was changed into a 1-bit
(black and white) photo. With a histogram the
ratio of white and black points (and thus
canopy gaps) was estimated. The ratio was
then used for calculating the transmission of
the canopy for different zenith angles. With
wide-angle lens, 5 zenith angles are usually
used (7, 23, 38, 53 and 68
0
; Chason et al.,
1991; Chen et al., 1991). Since a 28 mm lens
was used in our case, only the zenith angles 7
0
and 23
0 
were used (Šraj, 2003).
3.3.4 Photosynthetically active radiation
(PAR)
PAR measurements were made using
Sunflect Ceptometer (Vrije Universiteit
Amsterdam). Incident and transmitted PAR
was measured in the south plot in October
2000. Measurements could not be performed
on the north plot, since almost no sun light was
transmitted throught the tree canopy.
Transmitted PAR was measured in the same
ten points, where the photographs were taken,
incident PAR was measured on a close-by
forest clearing. Three measurements were
made in 2000 (Vrije Universiteit Amsterdam),
i.e. on October 16, 21 and 22 in clear weather
conditions. On average, each measurement
comprised 80 individual measurements on 80
photodiodes of the Ceptometer, for 8 azimuth

Šraj, M.: Dolo čanje indeksa listne površine listnatega gozda na povodju Dragonje – 1.del: Metode in meritve –
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© Acta hydrotechnica 21/35 (2003), 105–127, Ljubljana
124
orientacij. Vsak izmerjeni podatek predstavlja
torej integracijo 8 x 80 = 640 to čkovnih
meritev (te Linde, 2001).
4. ZAKLJU ČKI
Indeks listne površine se je dolo čal po treh
metodah, in sicer z neposredno metodo
zbiranja in dolo čanja koli čine odpadlega listja
ter z dvema posrednima metodama:
hemisferi čnim fotografiranjem drevesnih
krošenj in z merjenjem fotosintetskega
aktivnega sevanja PAR na vsaki ploskvi
posebej, saj se opazno razlikujeta tako v
strukturi, gostoti in velikosti dreves kot v sami
sestavi.
Vse tri metode so med seboj zelo razli čne.
Pri merjenju PAR s Ceptometrom dobimo
rezultate skoraj takoj. Hemisferi čno
fotografiranje krošenj je v fazi fotografiranja
dokaj hitro, vendar kasnejša obdelava
fotografij zahteva veliko časa in dela. Ima pa
pred merjenjem PAR prednost v tem, da pri
vsaki fotografiji upošteva razli čne zenitne kote
in zajame precej velike površine. Direktna
metoda zbiranja odpadlega listja pa je po
vloženem času in delu najzahtevnejša od vseh
treh, je pa zato tudi najbolj natan čna.
ZAHVALA
Za angleški prevod se zahvaljujem ge.
Mojci Vilfan, za finan čno podporo pa
Slovenskemu komiteju IHP UNESCO in
Ministrstvu za šolstvo, znanost in šport RS.
orientations. Thus, each measured data
represents the integration of 8 x 80 = 640 point
measurements (te Linde, 2001).
4. CONCLUSION
Leaf area index was estimated according to
three methods, i.e. the direct method of literfall
collection and estimation, and two indirect
methods: hemispherical photography of the
tree canopy and method of photosynthetically
active radiation PAR. The measurements were
performed on each plot separately, since they
differ considerably in terms of structure,
density, size and composition.
The three methods differ among each other.
In PAR measurements with the Ceptometer the
results are achieved immediately.
Hemispherical photograpy is fairly fast in the
phase of photographing, but the later
processing is time-demanding and requires
high work input. However, the main advantage
of hemispherical photography over PAR is that
it considers different zenith angles and
includes fairly large areas. The direct method
of litterfall collection is the most demanding in
terms of time and work input, but it also
produces the most accurate results.
ACKNOWLEDGEMENTS
I thank Ms. Mojca Vilfan for the translation
into English, and I greatly acknowledge the
financial support of the Slovenian National
Committee for the IHP UNESCO and the
Ministry of Education, Science and Sport of
the Republic of Slovenia.
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Naslov avtorja – Author's Address
dr. Mojca ŠRAJ
Univerza v Ljubljani – University of Ljubljana
Fakulteta za gradbeništvo in geodezijo – Faculty of Civil and Geodetic Engineering
Katedra za splošno hidrotehniko – Chair of Hydrology and Hydraulic Engineering
Jamova 2, SI-1000 Ljubljana, Slovenia
E-mail: msraj@fgg.uni-lj.si