The simple answer is to save time having to measure everything,
a very lengthy exercise called a census. If we want to know what kind of
social, environmental or economic changes are happening in a particular urban
area, it is usually impossible to go and count or measure the total number
of items under consideration, known as the population.
This problem is usually solved by taking a number of samples
from within the area.
It is necessary to ensure that these samples are representative
of the urban area in general. In order to be reasonably sure that the results
from the samples do represent the different characteristics of the urban area as
closely as possible, careful planning beforehand is essential. At least four
different representative zones can be identified in the El Raval inner city
district of Barcelona. These representative zones differ from each other in some
or all of their social, economic and environmental characteristics.
SAMPLE SIZE AND SHAPE
The usual sampling unit is a quadrat or square area. The
purpose of using a quadrat is to enable comparable samples to be obtained from
areas of consistent size and shape. It does not really matter what shape of
quadrat is used, provided it is a similar sized sampling unit and its shape and
measurements are stated in any write-up.
PROBLEM WITH SIMILAR SIZED SAMPLING UNITS
Does not take into account variations in street density. For many urban
studies, the primary data collection is based on data collected in the public
street and not the area as a whole. One solution is to base the size of the
sampling unit on street length or street area.
MINIMUM SAMPLE SIZE
The size of the sample will usually be dictated by the time
availability. The larger the sample, the more likely it is to give a true
picture of the population you are sampling.
The minimum number of samples which should be taken to be truly
representative of a particular area, can be calculated by graphing the number of
features recorded, as a function of the number of samples examined.
figure at the left is an example of this, obtained from a survey of residential
decay in an area of El Raval, Barcelona. The first sample gave an index score of
9. With the second sample, the index had increased to 13. After 5 samples had
been examined, the cumulative index had risen to 21. By the time 7 samples had
been taken, the index had stabilised. At this point, further sampling is
becoming unnecessary. This graph therefore shows us that for this particular
representative area, we need to undertake at least 7 samples. Further sampling
beyond this will merely waste time and duplicate results.
A statistical technique is also available that calculates the
minimum sample size required, depending upon how reliable you wish your data to
be. This makes use of the standard deviation of your sample data. The
standard deviation is a measure of the spread of your data from the mean (or
average). Two sets of data can have similar means, but very different spreads.
The data set with the smallest spread is the more reliable of the two. As your
sample size increases, the spread around the mean becomes smaller, as does the
standard deviation, and your results become more reliable.
One problem with sampling is the tendency to work in the most
accessible area or the area you feel most comfortable with. Your selection of
sampling zone is therefore biased and your results will not be reliable. This
means another researcher undertaking a similar study may get very different
results to yours. It is this need to be reliable that lies at the heart of
There are statistical techniques available that tell you how
reliable your work is. The techniques involve formulae that show how close your
sampled result is to the result you would obtain if you measured everything.
There are three main sampling methods that help to avoid bias
in the selection of your sampling sites:
Systematic sampling (which includes line transects)
1. RANDOM SAMPLING
Random sampling is usually carried out when the area under
study is very large, or there is limited time available. When using random
sampling techniques, large numbers of samples/records are taken from different
positions within the area. A numbered grid should be overlaid over a map of the
area. A computer generated random number table is then used to select
which squares to sample in. For example, if we have mapped a representative zone
in El Raval , and have then laid a numbered grid over it as shown below, we
could then choose which squares we should sample in by using the random number
A numbered grid map of an area to be sampled
The advantage of using random numbers is that no human is
involved in the selection process.
2. Systematic Sampling
Systematic sampling is when samples are taken at fixed
intervals, (e.g. every tenth building), usually along a line. This normally
involves doing transects, where a sampling line is set up across areas where
there are clear changes. For example you might use a transect to show how
gentrification or the price of a convenience item changes with increasing
distance from a zone of inner city redevelopment.
Line Transect Method
A transect line is laid across the area you wish to study. The
position of the transect line is very important and it depends on the direction
of the environmental gradient you wish to study. It should be thought about
carefully before it is placed. You may otherwise end up without clear results
because the line has been wrongly placed. For example, if the area of
redevelopment was wrongly identified in the example given above, it is likely
that the transect line would be laid in the wrong area and the results would be
A line transect is carried out by drawing the transect line
along the gradient identified. For example, the price of a convenience item,
e.g. a can of coca cola, may be recorded along the whole length of the line.
This is called continuous sampling. Alternatively, the presence, or absence of a
particular service or feature at each marked point, (e.g. every 100 metres), may
be recorded. This is called systematic sampling. Other factors that could affect
your results, such as the time of day or the type of retail outlet, can also be
inserted onto the profile.
Belt Transect Method
This is similar to the line transect method but gives
information on abundance as well as presence, or absence of a particular urban
feature. It may be considered as a widening of the line transect to form a
continuous belt, or series of quadrats.
In this method, the transect line is laid out across the area
to be surveyed and a quadrat is located on the first marked point on the line.
The features inside the quadrat are then identified and their abundance
Quadrats are sampled all the way down the transect line, at
each marked point on the line, or at some other predetermined interval (or even
randomly) if time is short.
An example of the type of results that can be obtained from a
belt transect survey is shown in the figure below.
figure illustrates the distribution and abundance of gentrified services along a
belt transect line. The oldest area of redevelopment in this example would be
quadrat 6, with gradients falling to the periphery at quadrat 4. Quadrats 1-3
are areas with no services. Quadrat 9 is an area of very recent radical
redevelopment, where gentrification is consolidating.
3. STRATIFIED SAMPLING
Stratified sampling is used where there are small areas within
a larger study location which are clearly different. For example, an area with
more elderly and very young people. We would therefore make sure that our sample
included a representative proportion of the elderly and very young. Sampling
would still be carried out either randomly, or systematically within each
separate 'stratum' identified. This recognizes major differences within
communities before sampling begins.
Stratified sampling has the advantage that it helps to reduce
any bias which might arise if samples were chosen completely at random. The
problem is identifying in advance what the strata (such as age divisions) should
Adapted from Ecological Sampling Techniques presented by
Offwell Woodland & Wildlife Trust