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Proceedings of the Symposium on Global and Environmental Monitoring

01le Hagner
Dept, of Biometry and Forest Management, Remote Sensing Laboratory,
Swedish University of Agricultural Sciences, S-901 83 Umea, Sweden
The method described is based on integrated use of digital satellite data, National Forest Inventory (NFI)
sample plots, map information, and subjective field inventory. Forest stands are delineated by using a
digital region growing technique called "t-ratio segmentation" and SPOT satellite data. The segmentation is
guided by digitized map information on landuse and administrative regions. Stand characteristics are
estimated for each stand by combining estimates obtained from both satellite data and field inventory. NFI
sample plots and corresponding spectral signatures are used to construct regression functions for esti
mation of stand variables.
The method was evaluated at five separate test sites in northern Sweden. The t-ratio segmentation method
produced results similar to visual interpretation of aerial photos and field checking. The accuracy of
stand data estimation was comparable to subjective field inventory. A substantial improvement in estimate
precision was obtained when combined estimates were calculated from both satellite data and field inven
Key Words: SPOT, Landsat TM, segmentation, region growing, stand delineation, forest inventory, estimation
of stand characteristics.
1.1 Background
1.1.1 Stand delineation and inventory methods
used in practice. The basic unit in Swedish forest
management planning is the forest stand, which is
a homogeneous region of about 1-20 hectares in
size. Several adjacent stands with similar charac
teristics may be grouped into treatment units, or
compartments. Stands are delineated by means of
visual interpretation of black and white aerial
photos, usually at the scale of 1:30 000 or
1:20 000. The result is checked and corrected
during field inventory. Stand characteristics are
normally estimated by means of ocular field
methods, supported by a few relascope measurements
at subjectively selected spots within each stand.
After field inventory, the final delineation is
transferred to a forestry map with orthophoto
background and, in some cases, the result is
digitized and stored in a GIS. Although field
inventory constitutes the major part of forest
mapping costs today, very few additional sources
of information are used in the estimation of stand
1.1.2 The thematic classification approach.
Several attempts to use the "classic" satellite
remote sensing approach for forest mapping, i.e.
supervised thematic classification, have been made
in the Nordic countries. The results, however,
have usually been of no or limited value to
foresters for management planning. One of the
main reasons is that the information needed is
standwise estimates of several stand character
istics rather than discrete pixel by pixel class
information. Most of the important stand variables
are continuous, e.g., volume/hectare, mean age,
mean diameter, tree species mixture etc. This
information can not be expressed by a few discrete
classes, without large approximations. Some other
limitations of the classic approach are: (1) The
procedure of selecting appropriate training samp
les is laborious and often subjective. (2) Dis
crete class definitions are difficult to match
with other sources of information.
1.1.3 The Finnish approach. Several studies in
Finland have proposed the use of digital satellite
data for standwise estimation of continuous stand
variables. Poso et. al. (1987) used satellite
data, digitized stand boundaries, and clustering
techniques in a stratified two-phase sampling
design. Tomppo (1986) used National Forest Inven
tory (NFI) sample plots and corresponding spectral
signatures from Landsat TM to construct regression
functions. They also used digital satellite data
for delineation of homogeneous regions. The
results were very promising and indicated that
stand characteristics could be estimated almost as
accurately with satellite data, as with manual
ground-only methods. They also demonstrated the
importance of using map information in the analys
is. The segmentation technique used, called "di
rected trees" (Narrendra & Goldberg, 1985), was
considered very promising, although some improve
ments were needed.
1.2 Objectives
Inspired by the Finnish results, a project was
started in 1986 at the Remote Sensing Laboratory
in Umea. The aim was to develop a new integrated
inventory method combining, via statistical tech
niques the potentials of satellite remote sensing,
field inventory methods and geographic information
systems (GIS). The objectives of this study were
to define the method and to test the main parts;
the computer delineation of stands and the esti
mation of stand variables.
2.1 Outline of the integrated inventory design
The basic idea behind the method is to enhance
existing inventory methods by using computer
support to derive new information from digital
satellite data and other sources of information.
The methods should be implementable on mobile
workstations and capable of being operated by
field inventory personnel.
2.1.1 Stand delineation. Segmentation tech
niques and high resolution satellite data are
used (Tomppo 1986), (Hagner 1989) for delineation
of homogeneous stands of approximately 0.5-5
hectares in size. The delineation is guided by map