ımber
UMZs
for
a of
mber
ause
t-up
1984
reas
that
one
logy
mask
l as
from
an
1991
by
and
mask
ges.
many
the
be
mall
1 to
of
1995
s in
ngle
1984
tant
Chil]
e UMZs existent in Lisboa and Oeiras do
not show a great difference from 1984 to
1995. Notice however that, this does not
mean that there was not a change on the
areas occupied by built-up cover, since
the UMZ also includes non-built-up areas
that are within the same UMZ;
e Loures and Sintra experienced a large
change in the county area covered by
UMZs. In these counties individual UMZs
that were close to the LUMZ connected
themselves to the LUMZ. On the other
hand, in the North part of these
counties many built-up areas that were
in different and small contiguous 1984
UMZs are in a single, and larger, 1995
UMZ, which results from the aggregation
of the 1984 scattered UMZs;
e Amadora and V.F. de Xira experienced a
small expansion of the UMZs, and Cascais
experienced a moderate increase of the
UMZs.
5. CONCLUSIONS
In this study we presented a methodology
for the delimitation of UMZs (as defined by
EUROSTAT) by using satellite data and
methodologies based on automatic
procedures. First, EO and ancillary data
were used to generate a landuse map. Then,
the built-up areas were identified and an
algorithm to identify the UMZs based on the
principle of continuity was developed and
applied to two dates (1984 and 1995) for
the Área da Grande Lisboa (AGL).
An analysis of the UMZs for the two dates
reveals a significant increase of the
built-up areas in AGL from 1984 to 1995.
This expansion of the built-up area was
mainly done by expansion of existent UMZs
rather than on new UMZs.
AKNOWLEDGEMENTS
This study was partially supported by
EUROSTAT, Programme Teledetection et
Statistics (Contract RS/12/031/MF/SW).
REFERENCES
Barnsley, M.J. and Barr, S.L., 1997.
Inferring urban landuse from satellite
sensor images using Kernel-based spatial
reclassification. Photogrammetric Engi-
neering and Remote Sensing, 62, 949-958.
Caetano, M.S., Navarro, A. and Santos,
J.P., 1997a. Improving urban areas
mapping with satellite imagery by
contextual analysis and integration of a
road network map. Proceedings of the 23%
Annual Conference and Exhibition of the
Remote Sensing Society: Observations and
Interactions, University of Reading-
United Kingdom, 2-4 de September 1997,
pp. 106-111.
Caetano, M.S., Santos J.P. and Navarro, A.,
1997b. A multi-strategic approach for
landuse mapping of urban areas by
integrating satellite and ancillary
data. Proceedings of ‘the 1997 IEEE
International Geoscience and Remote
Sensing Symposium (IGARSS'1997),
Singapore, 3-8 August 1997, Vol. I, pp.
240-242.
Campagnolo, M.L. and Caetano, M., 1997.
Expert maps: an alternative for
integrating expert knowledge in
satellite imagery classification.
Proceedings of the 1997 IEEE
International Geoscience and Remote
Sensing Symposium (IGARSS'1997), Singa-
pore, 3-8 August 1997, Vol. I, pp. 680-
682.
CNIG, 1996. Analysis of the dynamic of the
Lisbon Urban Agglomeration - First year
report. CNIG, 101 pp.
Congalton, R.G., 1991. A review of
assessing the accuracy of classi-
fications of remotely sensed data.
Remote Sensing of Environment, 37, pp.
35-46.
Groom, G. B., Fuller, BR. M. and Jones, A.
R.. 1996.
techniques for improving land cover
mapping from remotely sensed images.
International Journal of Remote Sensing,
17, pp. 69-89.
Contextual correction:
He, D.C., Wang, L., Baulu, T., Morin, .D.
and Bannari, A., 1994. Classification
Spectral et Texturale des Données
d' Images SPOT em Milieu Urbain.
International Journal of Remote Sensing,
15, pp. 2145-2152;
Ormsby, J.P., 1992. Evaluation of natural
and man-made features using Landsat TM
data. International Journal of Remote
Sensing, 13, pp. 303-318.
Intemational Archives of Photogrammetry and Remote Sensing. Vol. XXXII, Part 7, Budapest, 1998 697
