Full text: Proceedings of the Symposium on Global and Environmental Monitoring (Pt. 1)

Simo Poso 
University of Helsinki 
Department of forest Mensuration and Management 
Unioninkatu 40 B, 00170 Helsinki, Finland 
ISPRS Commission VII 
The principles of two-phase sampling procedures for forest resource assessments are described. In the 
first phase, data from auxiliary sources (e.g. maps, satellite imagery, aerial photographs, old forest 
inventory data, forest growth models) are used singly or in combination to form strata. In the second 
phase, actual ground measurement data are then transferred to the first phase units; each plot belong 
ing to the same stratum obtains egual ground truth estimates. 
The problem of using many data sources is that the number of strata tends to grow too high causing 
difficulties in getting a sufficient number of ground truth measurements. The solution introduced in 
the paper is to apply many separate stratifications based on different data sources which produces many 
estimates for first-phase sample units. The final estimates may be based on weighting using of inverse 
of error variance or on a specific expert system. 
KEY WORDS: Forest inventory, Remote sensing, Two-phase sampling 
There is a large number of alternative approach 
es that can be adopted for forest resource as 
sessments. These approaches can be roughly di 
vided into two categories: (1) to mapping for 
area classification and (2) to sampling proce 
dures. The differentiation of the above catego 
ries is not always unambiguous as many combina 
tions may exist. 
In mapping approaches the whole area is divided 
into a certain number of different categories 
such as forests, woodlands, other land uses. 
Different categories, i.e. classes, are diffe 
rentiated by drawing borderlines on maps or oth 
er base material, such as satellite imageries 
and aerial photographs. If remote sensing is 
used distortions should be known and elimina 
ted. The areas of different classes can then be 
measured on the base material. 
Sampling approaches involve locating a number of 
sampling units, usually circular plots or relas- 
cope points, in a systematic pattern in the in 
ventory area. Data are measured or estimated for 
each unit and the inventory results, including 
area distributions and mean values as well as 
reliability estimates, are calculated on the ba 
sis of the samples. 
The principal advantages and disadvantages of 
mapping approach may be listed as follows: 
+ traditional, easy to understand 
+ suitable for overall viewing 
- borderlines between classes are often ambig 
uous and subjective 
- variation within a class is often large 
- classes are often difficult to measure accu 
rately in the field (estimates often based 
largely on ocular estimations) 
- monitoring of changes is difficult if based 
on more or less subjective area delineation 
Generally, it is recommended to use a sampling 
technigue for national forest inventories in 
order to get detailed and non-biased informa 
tion for planning purposes. 
The purpose of this paper is to illustrate an 
application of sampling technigue together with 
the use of remote sensing in order to avoid the 
disadvantages associated with mapping. The tech 
nigue demonstrated is based on two-phase samp 
ling. In the first phase, auxiliary data is ob 
tained from many kinds of sources, such as maps, 
satellite imagery, aerial photographs. In the 
second phase, data are usually measured in the 
field. The sample for the first-phase data is an 
intensive one and the sample for second-phase 
data is a sub-sample of the first-phase sample. 
The final results are the better the higher is 
the correlation between the first- and second- 
phase data. 
A combination of remote sensing and ground truth

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