ne. 
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mean 
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100 
irvey methods 
Ificient and 
s reflecting 
It has been 
ibson (1980) 
substantial 
round based 
mes as long, 
lo not locate 
as 
nstrated the 
sing aerial 
of specific 
nain problems 
ncils obtain 
s only. in 
lard (1983) 
l this, ’The 
LI percentage 
but like any 
appreciated 
hanges taking 
iitions'. It 
ty of local 
nd therefore 
a needs to be 
is readily 
al is suited 
es. The use 
umented for 
ses, however 
high spatial 
such as SPOT 
•an studies. 
with the new 
is a brief 
ability for 
:ive urban 
used in the 
with limited 
it studies in 
ate on those 
on, such as 
have realised 
rban land use 
ages over MSS 
at may figure 
lysis. Anuta 
me clustering 
exhibits 42 
from MSS. 
- increased 
to MSS is 
nponent (PC) 
hi (1982 and 
PC images in 
facilitates 
detailed examination of urban structures. 
Additional dimensionality over MSS and the 
ability of the third PC of 4 band data for 
detection/discrimination of built up 
areas/bare soil has been noted by Sadowski 
(1983) . 
Increased spatial and spectral resolution 
do not necessarily mean that this data 
provides an uncomplicated answer to urban 
monitoring problems. The nature of urban 
cover must be considered, Owe et al (1984) 
state that heterogenous urban features often 
cause classification error. The reflectance 
from mature trees, which are often higher 
than residential units, has been found by 
Baumann (1979) to influence classification 
accuracy. Other investigators, Bryant (1971) 
and Forster (1981 and 1982) have highlighted 
the problems presented by abrupt changes of 
urban land use over short distances. These 
take the form of considerable inter and intra 
pixel differences, which seriously alter the 
reflection from one cover class that is 
surrounded by classes giving dissimilar 
readings. The difficulties associated with 
such conditions are summarised by Clark 
(1979) who states 'Physical or spectral 
conditions of a land use do not always divide 
as sharply as the cultural definitions of the 
land use' . 
Boundary definition is very important in 
the urban area, however sharp contrasts are 
infrequently seen. Instead pixels lie along 
boundary lines and introduce cover mixing 
effects. Merickel et al (1984) consider 
that up to 60% of the pixels in some Landsat 
scenes are mixed, whilst Owe et al (1984) say 
that with the TM, more pixels per unit area 
do not lessen the chance of boundary features 
being crossed. A programme, 'CASCADE', 
introduced by Merickel et al (1984), 
specifically to combat the mixed pixel 
effect, assigns pixels to homogenous regions 
in a neighbourhood after judging that region 
responsible for the mixing effect. 
A further influence on category 
discrimination, particularly in heterogenous 
regions, is the sensor Point Spread Function 
(PSF) . Acting over a 3x3 pixel area, this 
seriously affects the signature from cover 
classes with dissimilar neighbours. 
According to Forshaw (1983) a better 
representation of resolution would be a 
deconvolved PSF rather than a pixel only 
estimate. Forshaw considers that as a term, 
'spatial resolution' is 'poorly defined and 
improperly used' and is artificially high in 
order to compensate for the rapid data 
sampling rates of modern satellite systems. 
The views on the increased spatial resolution 
of sensors are as mixed as those on the 
improved spectral range. Irons (1984) 
suggests that a 'stalemate' is evident, where 
increasing resolution does not affect 
accuracy because; a) category spectral 
variability increase hinders classification; 
and b) a decrease in mixed pixels (by up to 
24%) enhances classification. A 'Point of 
diminishing return is reached and 30m IFOV 
should be the best for multispectral 
classification' is the stated view of Clark 
(1979) in an analysis of multi resolution TM 
Simulation data in an urban environment. 
Clark also recognised that as resolution 
decreased, classification accuracy actually 
increased, probably due to the heterogenous 
nature of urban sites being 'smoothed' out. 
Finally, to summarize Forster (1982), 
higher resolutions will, in urban areas; 
1. Reduce mixed pixels 
2. Aid contextual identification 
3. Aid in registration 
4. Reduce the PSF effect 
5. Higher data redundancy will allow more 
accurate judgement of surface percentages 
6. Higher pixel homogenity will aid in 
clustering procedures 
7. Texture studies may be implemented 
The increase in information content of TM 
data has proved problematic, not least in 
terms of data handling, but also regarding 
classification techniques. PC and canonical 
analysis have been used as data reduction and 
feature extraction techniques by a number of 
workers, Brumfield (1981), Jackson (1984) and 
Sadowski (1983), non traditional methods such 
as canonical analysis can result in upwards 
of a 20% improvement in classification 
accuracy. The need for new classification 
algorithms for TM imagery has been recognised 
by Irons (1984), and classification schemes 
currently being developed at the Natural 
Environment Research Council by Jackson et al 
(1984) exploit per-pixel, textural and 
contextual algorithms. Wang (1984) considers 
that such techniques need careful development 
because the 'Averaging process smooths out a 
certain amount of the data's unique 
qualities', while Forshaw (1983) implies that 
resampling may limit resolution to 2 times 
the pixel size. It is evident that although 
significant classification accuracy can be 
obtained with TM data, better results can be 
expected and a hiatus exists with current 
methods unable to realise the full potential 
of TM data. 
Much of the work being done on TM imagery 
and urban environments originated from the 
USA, which features a different urban make-up 
to the UK. Jackson et al (1984) define the 
problem with a statement on the quality of 
the first TM images, 'in rural areas, there 
is a very significant improvement over the 
MSS, whereas in urban areas the improvement 
is much less marked, probably as a result of 
the high density of English urban 
development’. For this reason the 
possibility of incorporating TM data into a 
GIS is currently being investigated with 
regard to derelict land. Although 
cartographic fidelity does not appear to be a 
problem with TM data (Welch et al 1984), data 
transformation does alter pixel values, 
damaging their essential qualities. 
The difficulties in combining digital data 
with different sorts of ancillary information 
are well known, and to quote Brooner (1982), 
'A new generation of information systems 
whose design bridges both cell and polygon 
inputs, characteristics of 'conventional' 
systems is needed'. The problem is 
compounded by the quality of present and 
proposed satellite data, which should not be 
excluded from a comprehensive GIS. 
Clark (1979) suggests 30m resolution as 
the optimum for urban studies, Forshaw (1983) 
considers that 'resolutions rather better 
than 10m will be necessary for consistently 
high recognition accuracies', and Jackson et 
al (1984), in recognition of the dense nature 
of English development states 20m as a 
minimum resolution requirement. Forster's 
(1982) theory is that TM should be used to 
determine surface types, while SPOT 
panchromatic data, 10m resolution, could 
provide high resolution cartographic and 
contextual information. 
It is the authors opinion that while these 
suggestions are valid, it is essential to 
include data from aerial photography in a GIS 
to facilitate the provision of qualitative