ROAD
HOUSE /
SPOT
ET :
PARCEL LANDSAT TM
L di i J
0 10 20 30
METRES
FIGURE 2: Dimensions of residential features (Sydney) compared
with Landsat TM and SPOT pixel sizes.
(b) traditional clustering techniques for surface classification may also
become more appropriate because within pixel homogeneity will increase,
(c) textural type variables will have an increased potential in surface cover
prediction and housing density studies.
This latter point will be expanded further. For a homogeneous extended surface
the response at a sensor will show little variation. Homogeneity however is
dependent on both pixel size and the size of the elements being viewed.
Variance over a pixel neighbourhood (say 3 x 3) will increase as the pixel
size approaches the size of the elements and will then reduce as the size of
the pixel continues to decrease. This suggests that the resolution of Landsat
D TM and SPOT (in particular) is approaching the optimum for maximum textural
discrimination of surface features typically found in low density cities. It
necessarily follows then, for a constant pixel size, that as housing density
varies from very low to very high, variance will pass through a maximum, as
shown schematically in Figure 3.
The increased number of spectral bands available on Landsat D TM, will also have
advantages in urban monitoring, because of the increased numbers of predictive
surface equations or cluster dimensions that can be formed. Their better
placement and increased radiometric resolution will allow better vegetation
discrimination but in addition should have a number of advantages for other
urban surface materials. While further research is required to determine urban
Spectral response in the new bands, the following tentative conclusions are put
orward.
(a) Concrete surfaces should remain high in the 1.55-1.7 um band (TM 5) (in
a similar way to hydrothermally altered rock) and give enhanced differen-
tiation with vegetation that has a lowered (but local maximum) response.
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