I think Juan is right the morphological properties are better at predicting
the diversity and differentiation of the movement in London.
That said, I think the question comes down to how accurate you need
the numbers.
>In London, gross densities (i.e. sq.m. of building floorplate per sq.m. of
>land) vary greatly, from about 3.5 in the City to less than 0.5 for much of
>Outer London. However, the length of street network per sq.km. does not
>vary that much, being about 27 km per sq.km. for the City and around 24 for
>areas south of the Thames (Southwark, Lambeth), that have much lower
>densities.
intreasting I have heard some speculation on includeing an axial line for
the taller buildings + floors. This would more accuratly reflect the
spacial model and so draw the intergration model into the buildings
with large vertical 'streets'. This might fix the Canary Wharf problem.
Alternatively you might want to consider looking at a multiple
regession over global and local intergration. The global intergration might
well reflect the overall urban density. - this is just a suggestion a
correlation between globle intergration and ubran density would be intresting
to look at.
>
>One way round this problem would be splitting the analysis into a number of
>zones (probably very many), that have a certain degree of uniformity.
>Establish correlations for each zone (for which the correlation equation,
>slope and intercept, would be different) and then aggregate the various
>areas. The problem then is, how do you select the different zones and how
>many you go for. If you decided on a size in the region of 2 sq.km. you
>might end up with about 1,000 zones. But even if you decided to choose a
>fraction of that, say 200 zones, you would still need a good number of
>survey locations for each, covering the spectrum of integration values. I
>would guess that you might want at least 50 (possibly more), which would
result in 10,000 survey locations.
Since the conferance there has been a number of approaches to thinking about
the automatic extraction of such areas. They would establish the local
correlations (raa/rra3) which would make a series of areas of differing
size. You might get one large patch for a suburb but a much smaller one
for say soho.
One way of setting up the observations was something I was thinking of a
few months ago. Using software to look at all the webcams looking at the
streets and borrowing tapes from the security cameras all over London.
This would give you a bias but global picture but automatically collect all
the values.
>Then, by continuously monitoring some links, I can
>estimate total annual person-km walked in London.
If you are looking for problems then think about how many journeys are
multi-mode - people getting the bus,tube,car then walking the
remaining distance to
work. You can pick up a fair amount of data for say tube journeys.
One method to calibrating your model might be to look at the census
data for too/from work by foot the see how that correlates with the bigger
picture.
again it all depends upon how accuratly you need to know.
let me know how it goes.
sheep
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