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ESTIMATION OF PINE PLANTATIONS PHYTOMASS OF MARI
ZAVOLZHYE BY SATELLITE IMAGES OF LANDSAT -7 (ETM+)
E.А. Kurbanov1, О.N. Vorobyev1, L.S. Moshkina 1, А.V. Gubaev1, С.А. Lezhnin1
1
Mari State Technical University, 424000, Yoshkar - Ola, Lenin Sq, 3.
Ph. (8362) 455412, Е-mail: rts@marstu. mari. ru.
The issues of pine phytomass stock estimation in Mari forest Zavolzhye by satellite images of Landsat-7(ETM+) with the help of satellite image processing program Multispec are considered in the work. Three dimensional model of phytomass dependence on
4 and 5 spectral bands of satellite images which makes it possible to improve the process of pine forest stock estimate on large areas is obtained.
Introduction
It is necessary to have information about
aboveground biomass stock for estimation and
prediction of ecosystem productivity, carbon
budget and state of forest plantations during
joint implementation (JI) projects aimed at realizing the Kyoto protocol [1-4]. Besides, biomass is an important indicator of the forest
state and structure depending on the environment.
Field studies of the sample plots (SP) are the
most reliable material to estimate biomass, define tree volume and forest stand composition.
The accumulated experimental data are now
widely used for compiling biomass maps of
forest plantations using satellite information
data. Relationships have been developed between forest biomass and vegetation indices
using Landsat Thematic Mapper [2]. In India
the maps of forest types were created by the
forest stand canopy with the help of satellite
IRS-1 for biomass mapping [5]. Interdependence of normalized vegetation index AVHRR
(Advanced very high resolution radiometer)
and tree biomass was used for creating biomass maps of boreal forests of the Northern
hemisphere [6].
A lot of work aimed at the estimate of inventory indicators of the forest stand (age, density
of canopy, height) with the help of remote
methods is conducted [7].
The purpose of our work was the estimate of
phytomass relations of Mari forest Zavolzhye
pine plantations by satellite images. To
achieve this, the following tasks were set:
 To allocate SP for pine plantation phytomass study by satellite images.
 To find out spectral values of the studied
plots in the images of Landsat -7 (ETM+).
 To prepare the models of pine stands phytomass dependence on spectral values in 4
and in 5 infrared image bands of this satellite.
Research technique
Estimation procedure of plantation parameters
and indicators when dealing with satellite data
was conducted in two stages: field and laboratory work. Field work involved:
а) Obtaining satellite images from GLCF –
Global Land Cover Facility website (Maryland
University project, the USA).
b) Plot selection was conducted after preliminary estimate of objects in the Landsat -7
(ЕТМ+) satellite images and available forest
estimation records of Mari Zavolzhye forest
plantations.
c) Allocation of sample plots.
Experimental material on the research issue
was obtained during the field season from May
to October 2006 with the use of sampling plot
technique allocation taking into account the
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theory of forest inventory and forest management (Forestry standard 5669-83). The area of
every sample plot was over 0.5 hectares.
Estimate of inventory indicators (average indices of diameters, total cut areas, relative density, volume, etc) was conducted by standard
method of SP card data processing in accordance with forestry standard. Defining the age
of forest major element was done by calculating annual growth layers on core samples obtained with the help of age auger. The average
age of a pine plantation is defined as the
arithmetic average form the data by the measured trees.
Satellite images were processed by the program Multispec (http://cobweb.ecn.purdue.
edu), meant for computer processing of multi
spectral images and developed by the scientists
from American university Perdue. A corrective
estimate of coordinate shifts of laid sample
areas obtained with the help of GPS receiver
“GARMIN” and the area measurement data to
the nearest reference points was performed
(fig. 1).
To obtain valid data concerning spatial location
of reference points within the forest stand the
pixel center with corresponding coordinates in
degrees or meters was taken as the coordinate
basic value. Spectral values (SV) estimate of
every studied pixel (30×30 м) of satellite image
Landsat-7(ETM+), located within the sample
area of the pine plantation under study for the
close 4 (0,75 – 0,90 micrometer) and average
infrared 5 (1,55 – 1,75 micrometer) bands was
done in the program “Multispec”.
Table. Spectral values of pixels in 4 and 5 bands
№ of pixels
1
2
3
4
5
6
7
8
9
10
4 band
93
96
99
101
99
109
99
96
93
104
5 band
71
78
73
80
91
73
77
82
93
87
Phytomass stock of the plantation under study
for every allocated pixel of SP was defined by
the tables of biological productivity of standard pine plantations of the studied region [3].
As the input data for the table we used the average height and diameter of wood stand on
every allocated plot. Phytomass stock was adjusted to the relative density of pine plantation
corresponding to every pixel of sample area
which was defined by the total basal area with
the use of inventory tables.
Modeling the dependence of pine mature
stand phytomass on spectral values
The obtained data of pine phytomass volume
and the band’s spectral values of the corresponding pixels were processed in statistical
packages of Statgraphics Plus and Statistica.
Interconnection of pine plantation phytomass
pixels of SP with spectral values was conducted separately for each band.
The relations obtained are represented in model and diagram form. Data analysis of pine
phytomass dependence (Phyto) on spectral
values of 4 band (S4) proved that the best relations can be expressed by the following equation:
Phyto  1/(0,16026 7 - 7,94132/S4 )
In this case the standard error was unessential
(0,04), while the coefficient of determination
R2 was 7,42%.
The analysis of phytomass stock relation with
the 5 band’s spectral values proved closer linear relationship (R2 = 55%):
Phyto  37,40 - 0,30 * S5
Fig. 1. Delimitation of SP on the image in MultiSpec
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The best approximation of the experimental
data to the modeled ones was proved by three
dimensional model (Fig. 2) of pine plantation
phytomass dependence on 4 and 5 spectral
bands (R2=71%) of Landsat-7(ETM+) image:
Phyto  - 58,76 - 0,14 * S4  2,22 * S5  0,003 * S 2 
- 0,01 * S4 * S5 - 0,01 * S5 2.
Conclusion
As a part of the study we collected and processed the material of SP allocated on the territory of MarSTU Mari El scientificexperimental forestry enterprise which made it
possible to define pine plantation phytomass
of every studied pixel of Landsat-7(ETM+)
satellite image. Processing of satellite information and matching the area of SP in the image was performed with the help of Multispec
program.
Fig. 2. Dependence of pine phytomass on 4 and 5 satellite image Landsat-7(ETM+) spectral bands
The obtained data were used for finding out
pine phytomass dependence on spectral values
of 4 and 5 bands of images pixels, located on
the territory of SP. For studies we used the images in 4 and 5 bands of the Landsat7(ETM+), as these are the most reasonable in
such estimates.
As a result of the analysis conducted we obtained a three-dimensional model, demonstrating interrelation of pine phytomass of moss
group of forest types and the spectral values of
the corresponding pixels.
After including the obtained model into GIS
data base on forest plantation matched with
satellite images it is possible to define phytomass stock volume in pine plantations of moss
group Mari El in the most effective way. Besides the use of interrelations of phytomass
and spectral values of images can be widely
used when realizing carbon sequestration projects of the Kyoto protocol. Estimate of the
sequestrated carbon by the space images will
build confidence in relation to such projects on
the territory of Mari Zavolzhye and make the
defined certified emissions of greenhouse gas
more accurate.
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