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Title
Proceedings of the Symposium on Global and Environmental Monitoring

The stratification of the first phase units can
be repeated using different kinds of auxiliary
data for as many times as required. Each stra
tification produces a new set of ground vari
able estimates for each first phase sample plot
The result is illustrated in Figure 2.
1,2
1,2
1,2
1,-
1,-
3,4
3,4
3,4
3,4
3,-
1,2
1,2
1,2
1,-
1,-
3,4
3,4
3,4
3,-
3,-
1,2
1,2
1,-
1,-
1,-
3,4
3,4
3,-
3,-
3,-
1,2
1,2
1,-
1,-
1,-
3,-
3,-
3,-
3,-
1,-
1,-
1,-
1,-
1,-
3,-
3,-
3,-
“ У ~
Figure 2. Estimate vectors for the first
phase sample units
The numbers in the Fig. 2 refer to the strati
fications. Each of the 25 first phase plots may
obtain four different sets of estimates when all
stratifications are represented. Some plots are
represented only in one stratification and hence
receive only one set of estimates. If no auxil
iary data exist for a first phase plot it can
not be included in any stratum and it does not
receive any estimate directly. In this case
nearest neighbour techniques, i.e., taking the
estimates from the geographicly nearest neigh
bor plots, may be applied.
In order to estimate the final ground variable
values for a specific first phase plot, the con
cept of the reliability of the estimates has to
be introduced. The final estimates for the
ground variables, e.g. site, mean height, basal
area, volume, tree species distribution, volume
increment, and technical quality of the growing
stock, is calculated by weighting the separate
estimates by the reliability of the estimate.
3. DISCUSSION
The method, based on one stratification using a
combination of satellite imagery and map data,
has been tested in Finnish conditions on several
occasions with positive results. These experi
ences include an inventory of two communes with
forest areas of 18 000 and 120 000 hectares. The
field sample plots were usually relascope points
with a basal area factor of 2 nr/ha.
A study of the relevant possibilities and prob
lems in estimating final ground truth variable
values on the basis of more than one stratifi
cation has been started at the University of
Helsinki as a part of a thesis for a FI.Sc. deg
ree. The study deals with updating of old inven
tory data using remote sensing, forest growth
models, and maps.
The applicability of the approach to the tropics
has not been attempted. The methodology describ
ed may, however, be simple enough for forest re
source assessment and monitoring. In the most
extreme cases only N0AA and some basic map in
formation may be used for stratification. Land-
sat TM or corresponding data can be used when
ever accessible. The major problem would be the
availability of good quality ground truth data
as field inventories in tropical conditions are
very difficult to perform. The need for ground
measurements may be especially demanding in the
tropics if much weight is allocated for tree
species estimation. A single hectare of closed
tropical forest, for example, may include more
than 100 tree species each with its own indepen
dent colony of plants and animals. According to
Birdsey et al. (1986) tropical species tend to
have a clustered distribution. The use of clus
ters as sampling units is recommended (e.g.
Vazquez Soto 1987). Another general recommenda
tion for the tropics is the use of permanent
sampling units (e.g. Schreuder and Singh 1987).
It is important that all data: plots, pixels,
air photos, maps, etc., can be located at the
same coordinate and time system. The correspon
dence of different data should thus be tested.
Studies with satellite imagery have shown that
dislocation of some 20 m may cause a severe de
crease in the usability of remote sensing in
conditions where the average stand size is
small. Problems may also originate from unreli
able maps. Sometimes, it may be advisable to
substitute maps for satellite imagery in the
tropics. The date of the first and second phase
data may differ and procedures for updating se
cond phase data are thus required. Forest data
updating often requires the application of
growth models. The lack of reliable volume and
biomass growth models and change models in land
use emphasizes the need for permanent sample
plots, especially in the tropics.
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