Find out if the number of pedestrians increases when moving toward the C.B.D of Kidderminster.

We took down information about the environment around us, this information was then recorded on a score sheet which was contained in the booklet given to us by our teachers. The information recorded was shop or house quality on a scale of 0-5 (five being of highest quality), the environmental factor was measured on the same scale. This information was then recorded at different locations on our survey (points) to see if there was an environmental change the closer we got to the CBD. Altogether there were 10 different Survey points. From the information I recorded I found out that as we progress towards the CBD the quality of shops and the general environment actually improved.

The information that was recorded on each building we walked passed was.

* Frontages (Width of house in steps)

* Building Type (e.g. Flats, detached, semi-detached, and terraced)

* Number of floors (How many storeys)

* Building name (e.g. House number or Shop name)

* Land use Classification

*

The information was recorded on the Urban Transect Held Sheet. Furthermore the eastern transect group was split into 2 groups one recorded one side of the road while the other recorded the other side (Of Comberton Hill). Buy doing this we covered more ground and quicker.

The frontages were hard to measure because of the difference in stride between the people I was working with, and taking strides were very time consuming. Corner buildings were hard to measure as the frontages were a lot longer than the other buildings. Therefore this method was not very accurate. Another reason why it wasn't accurate because it was tiring which affected the stride towards the end and start of the field trip. The weather was also dull which might has affected the moral of the students which then therefore affected the results. An improvement to this method could be using a meter wheel which gives you a more accurate result quicker.

The number of pedestrians were recorded on home made sheet beforehand. On the sheet we recorded the number of men, women, and under 16 year olds visible and then the total number of pedestrians -this was done at 10 different transects.

DATA PRESENTATION

0 -No shops

-Wide variety of shop types, convenience goods dominant

5 - Dominated by department Stores/Variety stores, or shops selling comparison goods.

The graph indicates that the closer you are to the C.B.D the greater the population density. This is what I hypothesised. Unusual results occurred at transect 8 the reason for this could have been that there was a human error in recording the results or there may have been a place such as a school which is highly populated.

The Higher the transect number the closer it is from the C.B.D

0-No shops.

-Very few shops-dominated by houses/industry

2-Mainly offices.

4- Shops and banks/building societies.

5- Mainly shops.

The graph pattern shows that the closer you get to the C.B.D the higher the building score. This is what I predicted earlier on. Unusual results occurred at transect 1 where you would expect to find a lower shop quality because it is further away from the C.B.D although shop quality is higher is obviously higher than transect 2 and 3. The reason for this could be that the land at transect 1 is in the suburbs and the buildings may be of a better quality because of urban expansion has taken place.

5-National chain stores dominant.

3-Mixed-some national and independent.

-Small, independent shop units

0-No shops.

The Higher the transect number the closer it is from the C.B.D

We can interpret from this graph that the closer we get to the Kidderminster town centre the more national chain stores are dominant although transect 10 is an anomaly and doesn't quite support this conclusion. This was my hypothesis. Strange results occurred at transect 10 this could be because land is a lot more expensive in the heart of the town centre so national chain stores locate slightly further away to get a cheaper price.

The Higher the transect number the closer it is from the C.B.D

5-Very Safe

3-Busy street with pelican crossing

-High risk busy street with no crossing

0-Extremely high risk

The closer we get to the central business district the greater the safety for pedestrians crossing the streets. I expected to find this. Unusual results occurred at transects 6 and 7 the reason for these patterns are that there are not as many cars pass through this area and therefore there isn't any need for a pelican crossing.

5-Well maintained property attractive

-Poorly maintained very drab

The Higher the transect number the closer it is from the C.B.D

The exterior appearance of buildings gets better the closer we get to Kidderminster town centre as shown in the graph above. This is as I expected. Anomalies in results occurred at transect 1 and 2 this may be due to the building being newer because of urban expansion. These results show a link between the shop quality graph.

5-All premises occupied

-Many vacant premises/cleared sites

The Higher the transect number the closer it is from the C.B.D

The graph in general shows us the further away you are from the C.B.D the more vacant premises and the closer you are the less vacant premises.

This is as I predicted. Strange results occurred at transect 10 where it has just as many vacant premises as transect 1. This may be due to the price of property being too expensive so firms locate slightly further away and get a cheaper price. This result shows a link between the retail organisations graph.

5-Pedestrianised street/precinct

4-Buses only route, no through road.

3-Open to all traffic-no parking.

2- Open to all traffic-limited parking.

-Main traffic route-no parking restrictions

The Higher the transect number the closer it is from the C.B.D

The closer you get to the C.B.D the greater the traffic/pedestrian segregation. This is shown in the graph above this is what I expected as the closer you get to the town centre the greater the population density (as shown in the population density graph) and the smaller the roads resulting in traffic congestion. Unusual results occurred at transect 10 where the traffic score is lower than transect 9. This may due top the fact that firms decide to locate slightly outside this location due to expensive property prices and therefore less jobs are available in that area resulting in less people trying to travel there which intern means less traffic congestion. These results show a link between retail organisations graph where less national chains located at transect 10.

5-Very clean no litter

-Very dirty-serious litter problem

The Higher the transect number the closer it is from the C.B.D

What we can interpret from this graph is that the closer you get to the C.B.D the higher the street cleanliness, this is what I hypothesised. There is one anomaly that does not support this idea.e.g. transect 7. The reason for this may be that the outside of the buildings may not be visually appealing as shown in the exterior appearance of buildings graph and therefore the council might not bother cleaning up that area.

EVALUATION

Overall I think my fieldwork investigation went quite well. This is because I collected sufficient data, which is presented in the form of graphs and later analysed. Although I did have some difficulty measuring the frontage of houses because me and my partner Gurpreet had a different length in our stride, this methods could be improve by used a metre wheel. I also found difficulty in deciding the score of street cleanliness, traffic/pedestrian segregation, vacant premises, exterior appearance of buildings, safety for pedestrians crossing the street, retail organisations and shop quality. This is mainly due to the fact that you have to give each transect a score from 0-5 which means it is often opinion based and I often had a clash in view with my partner. A way to improve the traffic/pedestrian segregation method would be to stand at each transect point look around and count how many pedestrians are visible around you.

Although I collected sufficient data I think my results would have been more accurate if I took more readings and averaged them out.

CONCLUSION

The results above support my hypothesis that the closer you get to the C.B.D the greater the population density. This is due to the fact that as you move towards Kidderminster town centre the appearance of buildings gets better, the street cleanliness increases, not to mention the shop quality and the increase in national chain stores, which sell product of a higher quality at cheaper prices. Because there is an increase in national chain stores there will also an increase in banks because they would like to locate near an area where money can be withdrawn to by goods. Due to the increase in banks and national chain stores there will an increase in jobs and therefore an increase in people. I have found that all my results support my hypotheses.