Symposium on Remote Sensing for Resources Development and Environmental Management / Enschede / August 1986
425
The use of SPOT simulation data in forestry mapping
S.J.Dury, W.G.Collins & P.D.Hedges
Remote Sensing Unit, University of Aston, UK
ABSTRACT: The composition of a forest is constantly changing, either
by natural or man-made means. Satellite data may provide a cheaper
and less time-consuming method of forest inventory and
map-production compared with more traditional methods.
The area of study is located within the Forest of Dean,
Gloucestershire. Numerous digital enchancement techniques are
applied to SPOT simulation imagery and visually assessed to give the
best descrimination of the tree types within the forest. A maximum
likelihood classification is then performed on a suitably enhanced
image.This proves reasonably successful in distinguishing not only
different species but also different age classes of certain species.
A major source of error within the classification results from the
high spectral variance of urban areas within the forest. Proposed
methods of overcoming this problem are outlined.
The digital format of the data facilitates integration into a
geographical information system,
be derived in assessing the
operations.
1 INTRODUCTION
This paper describes work investigating the
potential usefulness of the SPOT satellite
for providing data of use in forestry
management.
One of the most critical problems in
forestry is the developing shortage of wood.
Schery (1972) predicted a ten-fold increase
in timber quantity demand by the year AD
2000, and even the vast forests of northern
latitudes and of the tropics will be unable
to meet these demands. In 1978 the Eighth
World Forestry Congress stated that; "On
present knowledge the tropical moist forest
.... may cease to exist as usable forest in
40 to 50 years" (Grainger, 1980).
The problems of shortening supply highlight
the need for good inventory information. Our
knowledge of the exact extent of the world's
forest resources was described by Grainger as
of cheap, repetitive inventory information:
to monitor the decline of forested areas, to
provide accurate estimates of current supply,
and to monitor the effect of various
management policies.
Holmes (1980) argues that a steadily
increasing proportion of the world's growing
demand for wood will be provided by
high-yielding, even-aged plantations. Such
plantations can increase yields by 8-10
times the world average of approximately
lm^/ha; whereas natural forests can be made
to increase their yield only two or
threefold, given sufficient inputs of
capital, manpower and research. Plantations
can also be developed on land that is
relatively poor from the point of view of
agricultural production. This would take the
pressure off virgin tropical forest to supply
commercial and non-commercial demands, and
could ultimately change the world balance in
favour of the supply side.
from which further information may
feasibility and impact of forest
The Forest of Dean is an example of an
intensively managed forest. The initial
objectives of this study were to determine
precisely what level of detail can be
attained by interpretation of the SPOT
simulation data. Previous work (Buchheim et
al 1984) was unable to achieve discrimination
to level III - species level - of the
Anderson System (Anderson et al 1976). This
study attempted to differentiate species not
only to species level but for certain species
to different age-levels.
2 METHODS AND MATERIALS
2.1 Study site
The Forest of Dean is located in
Gloucestershire. The area administered as
the Forest of Dean by the Forestry Commission
is around 11, 900 ha with 9,700 ha under
productive crops. The Forest is
characterized by a mosaic of small blocks of
species and ages of woodland.
The Forest of Dean was chosen since it
contains a mixture of both broadleaved and
coniferous trees, and good ground truth
already exists in the form of Forestry
Commission stock maps. The dominant species
found in the forest are: Oak (Quercus robur),
Douglas Fir (Pscudotsuga Menziesii), Norway
Spruce (Picea abies), Corsican Pine (Pinus n
v maritima), European Larch (Larix decidua),
Japanese Larch (L Kaempferi), Hybrid Larch (L
eurolepis), Scots Pine (Pinus Sylvestris) and
Sweet Chestnut (Castanea sativa).
