Residential Areas
How do Basingstoke’s residential areas change, improve and reflect different urban models?

Applied Understanding

For my geography coursework I am going to study the different types of residential areas throughout Basingstoke; working from the Central Business District and following the main route through Basingstoke in a south westerly direction. When my coursework is complete I am hoping to come up with a conclusion about whether Basingstoke follows the concentric model or if it fits more to the criteria of the sector model.

The central place theory is a geographical theory that tries to explain the size and spacing of humans, however, this theory only works when certain criteria are met, which in reality, aren’t met, for instance: an isotropic, limitless amount of space, an evenly distributed population, evenly distributed resources, consumers all have same purchasing power and no provider of goods can earn excess profit.

The concentric ring model (also known as the Burgess Model) is slightly more realistic than the central place theory and is actually based on a city, Chicago, Illinois. The theory puts forward that a settlement grows evenly (see Figure 1 below) , with the CBD in the middle, then light manufacturing, working class housing, middle class housing and then on the outskirts of the settlement, the high-class housing. At this stage I can see that Basingstoke does, to a certain extent relate to this model.

The sector model also known as the Hoyt model (see Figure 2) explains that the strict growth patterns of the concentric model is wrong and settlements do not grow to an exact plan. It explains that there are reasons for growth in a certain way. It shows that working class housing is generally situated around various transport routes into the CBD, i.e.

Maisonette  

Sarum Hill

10

0

0

0

0

Bounty Road

4

2

2

1

1

Penrith Road

3

1

4

1

1

Cumberland Avenue

1

2

7

0

0

Vivaldi Close

10

0

0

0

0

The Beaches

10

0

0

0

0

For the above data I have created a percentage stacked bar chart, it is the easiest way to show this data. There is a lot there and so I need to use a technique that is going to break it down as much as possible so I can see if there is any kind of correlation that shows terraced houses are being faded out and the production of post 1900 semi-detached Victorian houses are being developed.

Figure 13
A stacked percentage bar chart

This percentage bar chart shows clearly how, from the centre of town where the cramped together terraced housing that dates back to the industrial revolution begins to fade out as you move away from the CBD. In Bounty Road we see the introduction of detached housing and then in Penrith Road semi-detached hold 40% of the housing there. From Sarum Hill to Cumberland Avenue terrace housing is significantly faded out then when we reach the newer part of the town that has been built in the last twenty to thirty years we see the re-introduction of terrace housing. Both Vivaldi Close and The Beaches are situated in the part of Basingstoke according to both the concentric and Hoyt models where the middle-class housing is found, thus, it is private but small and convenient for first time buyers – hence the reason for the mass terraced housing. However, although terraced like Sarum Hill the quality of housing here is on a much better scale and is clean and tidy and had been planned by developers and accepted by the council.

1. The intangible factors will have a higher rating on the outskirts of Basingstoke compared to the inner city areas.

Above is the hypothesis that I have just finished investigating. Basically this hypothesis is true and I have backed it up with evidence. I compared the intangible factors with the the time the resident have lived in the area and found the higher the intangible factor the longer the average time a resident had lived in the area. Also with this hypothesis I investigated whether residents wanted to continue living in the area and the type of housing they live in.

So far, with evidence from this hypothesis I have to say that Basingstoke minimally relates to the concentric model. I have evidence for this as Figure 12 shows that residents want to get away from the CBD which is known for its poor class housing and cramped conditions. Figure 13 shows that Basingstoke has developed according to the concentric model in a southwesterly direction.

In conclusion, when leaving the CBD you find that the intangible factors get better and they do end with the highest rating being nearer the outskirts of the town. Secondly, the time people have lived in an area relates to the intangible score – higher intangible score, longer the average time a resident has lived in the area. Thirdly, residents wanting to stay in their area of residents increases as you make your journey from CDB to outskirts. Lastly, the types of housing relates to the concentric theory and terraced housing does fade out when moving from CBD to the outskirts then there is a sudden growth in the amount of terraced properties on the estates built in the last twenty to thirty years.

2. Index of decay will be higher in the inner city areas.

In this hypothesis I will investigate whether there is a relationship between where residents reside and if the index of decay is higher in the CBD and gets better as you work your way out from the centre. In theory, the newer, planned houses are on the outskirts of the town, thus they will have a lower index of decay. However, the nineteenth century, older, unplanned houses in the more central part of town should have a higher index of decay.

In this hypothesis I will use every street that I have surveyed. For the first part of the hypothesis I will only be using the ‘external’ questionnaire – this is the survey I did myself of the area.

Table 6
Index Of Decay

At first look, it is easy to tell that as we move away from the CBD the index of decay is dropping – this is what I’d expect to find when referring to both the urban models. Penrith Road’s index of decay increases by 3 points, removing it from the decreasing pattern that starts from the centre of town. This could be due to a number of factors; 1) a higher crime rate, 2) older houses than Bounty Road (this would mean that Basingstoke does not relate to the concentric theory) or 3) the residents to not have enough disposable income to spend on their home to keep it tidy etc.

We also see a significant increase in decay in Cumberland Avenue. When I surveyed this street I noticed that these houses were a lot older than the actual area they are situated in. The houses are older so this explains why the street has a higher index of decay. The rest of the streets that I have surveyed you can see that the index of decay decreases as the distance from the town centre increases.

To evaluate this data I am going to use a cumulative frequency graph – this will enable me to find the lower quartile, upper quartile and median. With these values I can plot a box plot and then I will be able to appraise the spread of the data.

On the next page is a table which is the beginning of the stages of creating a cumulative frequency graph and then a box plot.

Table 7
Cumulative Frequency

I will now plot the ‘Cumulative Frequency’ data from this table onto a graph and then using that graph I will come up with the upper quartile, median and lower quartile.

Using the cumulative frequency graph, I have found the following figures:

Upper Quartile: 32

Median: 20

Lower Quartile: 12

With these figures I can draw up a box plot which enables me to evaluate the spread of the data.

I am now going to calculate the mean of the values and indicate it on the box plot with a red cross. To calculate the mean I use all the data from Table 6 and divide it by the number of streets.

236 / 10 = 23.6

The box plot shows that Basingstoke’s index of decay has a negative skew which means there is less streets with lower index of decay. This means that Basingstoke has an overall high index of decay – you can also see this in the box plot above as right of the median is bigger than left of the median indicating the fact I just indicated. The street with index of decay that has a result of plus twenty is more towards the CBD in Basingstoke – 20 being the median we can see that there is a split between working class and middle class housing and this split seems to come apparent at Portacre Rise.

This data proves my hypothesis correct; the inner city does in fact have a higher index of decay compared to the outer parts of Basingstoke. Also as we move out of Basingstoke along the southwesterly route we expect the index of decay to get better – my data analysis has proved this.

Secondly within this hypothesis I want to know whether or not people own their properties or rent the properties. I will then use a scatter graph to see if there is correlation between index of decay and the amount of people who actually own their homes. I expect to find the higher the index of decay – the less people own their homes.

Table 8
Rent or Own

Figure 16
Line Graph

As you can see from the line graph above there is no real patter between where the resident is situated and whether they own their home. Portacre Rise and Cumberland Avenue both have the most owned properties, and the other streets vary.

I will now combine the data that shows whether people own the homes with the index of decay data to see if there is any correlation between the two. The two sets of data I want to investigate are very different and the only suitable way to find if there is a correlation is to use the statistics calculation of Spearman’s Rank. Using a scatter graph or something similar with this data would not give me accurate or clear results – so although I am repeating something I have done already in hypothesis one, I am doing it for a good reason.

Null Hypothesis: There is a weak correlation between residents owning their homes and having  
                      a low index of decay rating.

Table 9
Spearman’s Rank

Rs =1-(6∑ d2 / n3-n)

Rs =1-(6∑ d2 / n3-n)
        ∑d2 = 24 therefore 6∑d2 = 744
        n = 10 therefore n3-n = 990
Rs = 1-(744/990)

Rs = 0.25 (correct to 2 significant figures)

Null Hypothesis: Accepted.

My null hypothesis said thatthere is a correlation between the index of decay and whether or not the occupants own their own home. This is true; there is in fact a weak correlation between them. This means that the higher the index of decay the more likely the occupants are to own their own homes.

Over the course of this hypothesis I have found out two main things about Basingstoke. The Index of Decay is higher in the inner city and there is a weak positive correlation between Index of Decay and whether the occupant owns their home.

        2)  Index of decay will be higher in the inner city areas.

In conclusion to this hypothesis I have found that Basingstoke does again (as in hypothesis one) minimally relate to the concentric theory because I have found Index of Decay actually gets better as you leave the CBD and make your way out of Basingstoke on the southwesterly route. This means the residential areas actually get in a sense better because the way people look after their properties changes and gets better, hence receiving a low Index of Decay rating. Also to conclude, I have found that residents own more homes away from the CBD – this is probably due to them not wishing to buy a family home in the centre of town and property prices in Basingstoke are also higher in the CBD due to supply and demand; there is a lack of nineteenth century properties and people can’t afford to live in them, thus having more rented properties in the area.

I have now finished and completely investigated this hypothesis. I will now go onto investigate hypothesis 3.

3. Externalities will have a higher penalty point in the centre of town compared to the outskirts.

For my third hypothesis I am going to study on the environment in which the residential areas are situated in. I have hypothesized that the externalities will have a higher penalty point in the centre of town compared to that of the outskirts of town because back in the day when settlements first began to expand during the industrial revolution the need for compact housing was high and therefore the amount of green space etc became extremely limited.

So I can examine the correlation of externality features I created the table in Figure 8 which is based on my view of the area. Using this primary evidence and all of the streets I surveyed in my investigation I will examine this hypothesis.

Table 10
Externalities

To increase the reliability of my ‘external questionnaire’ I would most definitely ask a few other people to fill one and out and then I could average the results for each of the sections, i.e. intangible factors, externalities etc. This would give me an un biased view of the area and it would not be to my personal values, but to a selection of people’s values thus giving me more of a spread of results.

To increase the validity of my conclusions throughout the investigation I need to follow the steps in the last two paragraphs because there is no way I can improve their validity without the data to do so; I can only base my conclusions on the data I have collected. Doing the above two steps outlined in the above paragraphs, I may find that my conclusions would be very different and therefore making them more valid because of the sample size they have been based on.

I have now come to the end of my geography investigation and have found many things out about my town in which I personally reside and I have also learnt a lot about the environment I live in and how it actually changes as you move away. Although this coursework is long I feel it is to a high standard and has been finished extremely well.