17. REMOTE SENSING REQUIREMENTS TO SUPPORT FOREST
INVENTORIES
159
the method is more statistically oriented than the old classification-based
approach to use of satellite images
in principle, all variables can be estimated for each computation unit,
which is not possible with ordinary classification methods
the method preserves the natural dependency structure between forest
parameters
the method can be applied with minor modifications to very different
types of forests
the method can directly be applied using different remote sensing
material.
Airborne imaging spectrometer research is under development and can be
integrated into the system (Mäkisara and Tomppo 1996). The multi-source
inventory method developed by the Finnish Forest Research Institute has
also already been tested in some other countries.
7.
CONCLUSIONS
Inventories have produced large area forest resource information in some
countries since the beginning of the 1920s. The first world wide forest
resource assessment was compiled from national statistics by FAO in 1947.
The requirements for forest inventories have increased during the last
decades. New information sources and new methods make it possible to
increase cost-efficiency of inventories and change them from a field
measurement-based systems into a multi-source monitoring of the whole
forest ecosystem, thereby providing information about the structure of
forests, their health and their biodiversity status for small and large areas.
One of the problems in further utilization of space-borne remote sensing data
is that the advantages of these data are not often perceived. Traditional
classification based approaches, which do not provide sufficient information
for forestry purposes, have been proposed and tested by remote sensing
community. The lack of communication between remote sensing and forest
inventory communities is one of the obstacles in expanding the use of
remote sensing data. Remote sensing has, however, obvious potential in
national and global level forest inventories.
INVENTORIES
159
the method is more statistically oriented than the old classification-based
approach to use of satellite images
in principle, all variables can be estimated for each computation unit,
which is not possible with ordinary classification methods
the method preserves the natural dependency structure between forest
parameters
the method can be applied with minor modifications to very different
types of forests
the method can directly be applied using different remote sensing
material.
Airborne imaging spectrometer research is under development and can be
integrated into the system (Mäkisara and Tomppo 1996). The multi-source
inventory method developed by the Finnish Forest Research Institute has
also already been tested in some other countries.
7.
CONCLUSIONS
Inventories have produced large area forest resource information in some
countries since the beginning of the 1920s. The first world wide forest
resource assessment was compiled from national statistics by FAO in 1947.
The requirements for forest inventories have increased during the last
decades. New information sources and new methods make it possible to
increase cost-efficiency of inventories and change them from a field
measurement-based systems into a multi-source monitoring of the whole
forest ecosystem, thereby providing information about the structure of
forests, their health and their biodiversity status for small and large areas.
One of the problems in further utilization of space-borne remote sensing data
is that the advantages of these data are not often perceived. Traditional
classification based approaches, which do not provide sufficient information
for forestry purposes, have been proposed and tested by remote sensing
community. The lack of communication between remote sensing and forest
inventory communities is one of the obstacles in expanding the use of
remote sensing data. Remote sensing has, however, obvious potential in
national and global level forest inventories.