RESEARCH FOR

SOME PECULIARITIES OF LABORATORY MEASURED
HYPERSPECTRAL REFLECTANCE CHARACTERISTICS
OF SCOTS PINE AND NORWAY SPRUCE NEEDLES
spectra for various materials. Developing spectral
libraries is a key to improving the capability to utilize
the full mapping potential based on hyperspectral data
(Zomer at al., 2009).
To date, one may find quite many studies which
have been dealing with hyperspectral data at a single
plant level, indicating that the field or laboratory
taken hyperspectral measurements can significantly
contribute to the discrimination of plants on species
level (Castro-Esau et al., 2004; Manakos, 2003;
Manevski et al., 2011; Vaiphasa et al., 2005; Zhang
et al., 2006).
This paper is aimed to introduce the first attempts
of hyperspectral remote sensing research in Lithuanian
forestry starting with a single plant level reflectance
data study. This study is focused on discrimination
abilities between Scots Pine (Pinus Sylvestris L.) and
Norway Spruce (Picea Abies L.), which are the most
common and commercially important tree species.
Scots pine stands make up 35.3% and spruce 20.8%
of total forest area (State Forest Service, 2011). These
coniferous tree species were selected for our research
since they have always been on the margin between
true and false discrimination on the remotely sensed
images (e.g. digital color infrared aerial photographs)
used in forest inventory in Lithuania, too (Mozgeris,
2004). They were under the focus of spectral
reflectance research in Lithuania using old-fashioned
spectral radiometers providing just an average
reflectance curve for the object being sensed two
decades ago, too. This research mainly was focused
on the spectral measurements of needles and branches
of trees with different defoliation level. Most effective
spectral zones for defoliation assessment were set and
some methodological solutions for improved spectral
measurement process were suggested (Repšys, 1992).
The discussion on the discrimination between
pine and spruce has a long history both in forestry
remote sensing research and methodologies within the
frames of operational forest inventories. The level to
which these tree species can be recognized on aerial
photography is determined by the type of aerial film
or digital sensor, scale of photography and quality of
images, and the methods used for interpretation. Even
there are some differences in color and tone of tree
crown projections, first of all the shape of own shadow
and tree crown projection play the most important role
in identification of these tree species (Mozgeris and
Daniulis, 1997; Mozgeris, 2004). Most of previous
research, e.g. in Lithuania, has focused on theoretical
potential to discriminate between spruce and pine
growing on pure stands. However, identification of the
shares of pine and spruce trees on mixed stands has
always been problematic (Mozgeris, 2004).
The hyperspectral imagery is supposed to
significantly support the tasks of tree species
Gediminas Masaitis, Gintautas Mozgeris
discrimination. It could serve as a new solution in
forest inventory for a remote identification of tree
species, especially in combination with airborne laser
scanning. We suppose that the future of Lithuanian
forest inventory lies in much wider usage of remotely
sensed data. The potential of laser scanned data for
estimation of basic tree or stand parameters, such
as volume, height is already proven by international
and local researchers (Mozgeris and Bikuvienė,
2011; Næsset et al., 2004; Næsset, 2007), but tree
species identification remains problematic so far. The
potential hyperspectral imaging for tasks in Lithuanian
forest inventory and internationally needs to be
investigated because of invention of new generation
of hyperspectral cameras, as is the VNIR400H used
in our study, too.
The aim of current study is to check some
methodological issues in processing of in situ acquired
hyperspectral data. The objectives are as follows:
1. To verify the significance of spectral differences
of Scots pine and Norway spruce using spectral
imaging techniques.
2. To check whether there is a significant spectral
variation among trees of the same species.
3. To check if the spectral response of northern
and southern side of the same tree varies
significantly.
4. To determine the wavebands which best
represent the spectral differences between
Scots pine and Norway spruce.
materials and methods
The samples were taken in 20 years old mixed
Norway spruce-Scots pine plantation. The best
growing trees in the plantation were randomly selected
for taking samples. The middle-upper part of the
crown of each tree was easily reached and the sample
branches were cut from the ground using telescopic
cutter. There were three trees of pine and three trees
of spruce selected totally. For each tree nine sample
branches were cut from the northern side of the crown
and nine sample branches from the southern side
of the crown. Totally 18 samples for scanning were
obtained from each tree, i.e. 54 for each tree species
or 108 samples in total.
Sample acquisition was performed in January,
2012. Cut samples were packed into plastic bags
with some snow added. Bags were labelled, put into a
portable cooler bag and transported to the laboratory
for spectral measurements.
The scanning process was conducted using a Themis
Vision Systems LLC new generation hyperspectral
camera VNIR400H. This device is equipped with
very sensitive VNIR spectrometer, which is capable to
cover the spectral range of 400nm – 1000 nm with the
sampling interval of 0.6 nm, producing 955 spectral
26 ReseaRch foR RuRal Development 2012