square
ons
| physical
a local
' in areas
ial and of
"section.
4.2.1: Validation of Mapping: In order to validate the
results. 102 control points were selected using stratified sample
to compare the produced maps with reality.
All the control points were correctly represented in the map.
This means that. in spite of some deficiencies. the model
mirrors the reality and the environmental problems.
Table 2 - Urban Land Use Classes and The Relation With
the Physical Potential Classes
Urban Land Use
(percentage of each class considering the
physical potential of the study area)
physical Residen. | Con Expos. | Other Total
potential Ind/Ser | Soil
Suitable areas || 0.3% 0.6% 0.4% 0.2% 0.3%
Some 7.4% 8.9% 5.8% 0.8% 6.9%
restrictions
Favourable 32.4% 37.8% | 21.4% 15.1% | 29.1
areas %
Severe 41.7% 40.8% | 39.5% | 27.2% | 41.3
restrictions %
Inadequated 18% 119% | 32.5% | 309% | 20%
arcas
Outcrop 0.2% 0.0% 0.4% 258% | 2.4%
Here are some examples: an area classified as favourable to be
occupied is an industry (an oil refinary). which is located in an
arca where could be found other human activity, like a
residential district: an area classified as inadequate in terms of
human occupation is an upper-class suburb located in a hill of
high slope associated to Podzolic soil. which means that this
area could not be occupied: another example of that class is a
“favela” (slum) located in a hill near a spring (figures 5. 6. and
7. respectively).
4. CONCLUSION
This rescarch tested a methodology to make easy the
metropolitan areas studies. It also tested the integration between
remote sensing and GIS technologies applied to urban planning.
Considering this. the methodology. developed and
tested. showed that the integration may be used by planners
who work with urban areas. and also be used to evaluate the
urban growth process ant its consequences.
Although limitations exist in the methodology.
mainly associated to the data collected. its use relatively simple,
has been demonstrated within acceptable accuracy expectations.
ACKNOWLEDGEMENTS
The authors are thankful to Dr. Bruce Forster.
associated professor of the University of New South Wales.
Sydney. Australia, for giving valuable contributions. which
helped to solve many problems. This research was partially
supported by Conselho Nacional de Desenvolvimento
Científico e Tecnológico - CNPq.
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