ship between land-
the image, texels and
= hedge- & tree-
ds ; M = buildings ;
he landscape :
otic volume ; BR =
ace ; S = biotic
cent pixels having
ttern of texels.
atial pattern of
he image correspond
P = polderland ;
; G = region of
W = Land van Waas.
do not contain
landscape. Their
only by adding con-
chieved automatially
lowd in visual inter-
structural informa-
hierarchival rela-
extures and struc-
landscape.
information about the
d truth could be
me :
ification in the
classical methods
d geographical lands-
significant for
s of the landscape
image for the
using mainly tex-
te the proportion
he different land-
3. - use these image attributes in a further typolo
gical classification of the landscapes to ob
tain units which are potential homogeneous
strata for a statistical sampling of landuse
categories using image classification ;
4. - implement these strata in the classification
procedure.
General purpose landclassification methods have
been used since the 1960's (Howard J. & Mitchell C.,
1980 ; Webster R. & Beckett P., 1970, Antrop M.,1983)
The/are based upon a stereoscopic interpretation of
medium to small scale air photographs.
Stereoscopic satellite imagery as the one available
from SPOT, will allow the use of the same methods.
Photomorphic image classification on orbital imagery
of a resolution level of Landsat MSS and TM, results
in a classification of land units on scale levels
of at least a landregion (J.Townsend, 1981 ; M.C.
Pirard & C.M.Girard, 1985 ; V.Ackerson & E.Fish,
1980).
Geography offers techniques for a regional classi
fication of such categorical landunits (A.Kilchen-
mann, 1973).
Landscape analysis offers a set of methods to des
cribe and measure spatial structures in the landsca
pe. Important ones are network analysis, shape and
directional analysis.
The proportion of pure pixels for any kind of ter
rain feature can be based upon an estimation using
a simulation pixel (M.Vauzelle, 1982 ; V.Aurelio,
et.al., 1984 ; M.Antrop, 1985). The use of the 5
groups described is suggested because of their
constancy.
A topological classification, based upon the attri
butes measured, can be achieved by determining si
milarities between the sample sites followed by a
cluster analysis. In this case a mean squared
Euclidian distance was used as similarity index.
Finally, the clusters obtained should be related
to terrain knowledge of the occuring landscapes.
Landscape elements and components which cause im
portant changes in the proportion of pure pixels,
should be used for a chorological classification of
the occuring geographical regions. Across-boundary
similarity can be used for this and thus zones may
be defined which have a constant structure according
to the pixel size used.
Although a small country, Belgium possesses great
diversity of both natural and cultural landscapes.
The long history of the occupation of the land by
man, is characterized by :
-different social groups and cultures acting in a
different manner and different periods for the
different natural regions ;
-specific and drastic adaptations of the natural
environment, which are also reflected in changes
of the soil conditions ;
-drastic changes occured since the early Industrial
Revolution and are still going on today (house
building, industrial land use, re-allotment).
The high population pressure is illustrated by
the average rural population density of 313 inhab./
sq. km, a motorway density of 13 km/100 sq.km, a
railway density of 14 km/100 sq.km. The spatial
differences in land use patterns between the major
administrative regions of Belgium is evident even
from general statistics (table 1.)
In the regions of Flanders and Brussels resp.
21 % and 77 % of the areas are more or less built-
up. Linear constructions such as roads and water
ways, occupy about 7 % and 20 % resp. of the area.
The utmost splitted character of the land use is
obvious.
Table 1. Cadastral landuse in Belgium, the region
of Flanders and Brussels (1980). Proportion (%) of
the area occupied by the main categories (after
H.Van der Haegen, 1982).
Flanders
Brussels
Belgium
agriculture
67
11
61
woodland, heathland
12
12
23
rurban
4
19
3
built-up areas
10
38
7
roads, waterways
7
20
6
Total area in ha
1351143
16178
3051871
About 12 % of the agricultural land has been refor
med by re-allotment, mainly characterized by more
open landscapes and larger fields. Traditional
landscapes, which are given a large historical and
ecological value, still occur more less well con-
servated over an area of about 25 %.
Although a great diversity in landscape typs exists,
it is not possible to distinguish them on Landsat
MMS image, not even by greatly deductive visual
interpretation (I .Vandecasteele, 1979 ; M.Antrop,
1985). In most cases there is no systematic rela
tionship between the image structure formed by the
texels and the landscape structures for the whole
region of Flanders. Only macrostructures can be deli
neated easily by photomorphicimage classification.
They are formed by the settlement pattern at the
scale level of villages and small towns, the pat
terns formed by vast landelements (waterbodies and
woods with an area of at least 1 sqkm), the main
geomorphological units (valleys, polders, cuesta's,
dunes) and the fieldpattern at the scale level of
complexes. The orientation of the latter are espe
cially important in the recognition process for
regions with large fields bordered by ditches and
tree- or hedgerows.
4.2.The analysis based upon a simulated pixel samp
ling
A first analysis was based upon a landscape sampling
using a simulated pixel upon orthophotographs on a
scale of 1/10.000, according to the method already
described. Sample sites have not been selected on
a regional basis but on their structural type,
especially when the structure is fine and complex
(fig.2). Consequentely most sites are taken from
the sandy region of Flanders between Ghent and
Brussels, where the rural landscapehas been affected
strongly by recent unorganized settlement, and
which is also called now a 'rurban' landscape.
The sampling used a simulated TM pixel size of
30mx30m. The results are given in tables 2 and 3.
The great diversity, complexity and the utmost
fine structure of the different landscapes is evi
dent even when only using the rather general cate
gories of biotic volumes (BM, i.e. mainly woods),
abiotic volumes (AM, i.e. mainly buildings), biotic
space (BR, i.e. all the agricultural land and
heathland, abiotic space (AR, i.e. water surfaces
and open (industrial) wasteland and biotic screen
(S, i.e. tree- and hedgerows).
The number of landscape elements/sq.km, is extre
mely high (table 2) and varies between about 1700
(openfield and re-allotment landscapes) to about
3500 (traditional enclosed landscapes with small
fields and regions with open settlement of a high
density). The proportionof estimated pure pixels
(size 30mx30m) is accordingly very low : about
50 %-80 % in the large scale open landscapes to
only about 12 %-25 % in the fine structured enclosed
and rurban landscapes.
4. AN APPLICATION UPON THE REGION OF FLANDERS
(BELGIUM)
4.1.The general setting of the landscape
5
