My investigation took place in Kidderminster. Kidderminster is a town in the Wyre Forest district of Worcestershire, England. It is located approximately twenty miles southwest of Birmingham city centre and has a population of 55,182 in the town. Kidderminster is famous for carpet weaving, there are still large warehouses, many of which are disused and found in the city centre and on outskirts. Map shows Kidderminster in relation to Birmingham. The highlighting shows the route we took to get to Kidderminster
The town centre area has undergone significant redevelopment in recent years, with the commercial retail area of Weaver’s Wharf, which has been redeveloped and now includes shops, restaurants and a college. It attracts many visitors and shoppers. Slingfield Mill, which has been remodelled into a retail area and incorporated into Weavers Wharf has created a large shopping area. We have chosen Kidderminster to study for our project because it is fairly close to our school, and is small enough to surveyed in a day.
Because Kidderminster is not part of the West Midlands conurbation it is therefore not subject to any of the other factors which could make our survey unreliable. These factors could be proximity to major shopping locations such as Merry Hill and Birmingham, which would affect the number of pedestrians found in the central business district (CBD) of Kidderminster. Objectives for the study: 1. The first is to observe the varying pedestrian numbers in Kidderminster.
This is to see if the land use has any affect on the number of pedestrians. 2. The second aim is to examine the different types of land uses in the CBD and the areas surrounding it. It is important to find out how land use changes in different parts of Kidderminster and why it changes. Hypotheses: Based on classwork and my knowledge of Kidderminster I expect the following; 1. Closer to the core of the CBD there will be a higher pedestrian count, further out near the inner cities there will be a lower pedestrian count. I am expecting to find that there are more pedestrians near the core of the CBD. I expect this because it has the most diverse shops and has large department stores.
The shops supply comparison or high-order goods; this creates competition and competitive pricing or special offers. The wide range of shops, along with competitive pricing allures people to the CBD to buy products from the big department stores. There are also entertainment sectors in the CBD where clubs, theatres, restaurants and bars are situated. This attracts as vast number of customers. The fact that there is so much choice of products and entertainment services it is not a surprise that the CBD attracts a large number of people. He customers who shop in the CBD should create large pedestrian count for the CBD.
Further away, there are specialist shops, which also attract a large number of pedestrians, but not more than the multi-functional CBD. This would mean that the pedestrian count would drop as the land gets away from the core of the CBD. On the frame of the CBD will be smaller shops and car parks. I anticipate there to be fewer pedestrians around this area as there is less choice of shops and less functions than in the CBD. Even further will be offices for solicitors, insurance companies etc. fewer pedestrians would be around here as there a no “everyday” services and there is not much leisure activity or shopping choice in the outer frame.
Finally, furthest away from the BD will be the inner cities. The houses will generally be terraced and there will be no shops, this area is purely residential, compared to the purely retail CBD core. Due to there being almost no services in the inner cities I would predict a low pedestrian count as only residents may be out. There is no reason for pedestrians to roam the streets of the inner city as opposed to the core of the CBD where there are plenty of attractions. This theory supports my hypothesis, that there will be fewer pedestrians, as the land is further away from the CBD.
The theory shows a steady decline of pedestrians, along with a steady decline of services, this leads to the conclusion that the services of the CBD are what attract so many pedestrians to it. 2. The CBD there will be many large chain stores, as land gets further away from the CBD, there will be less shops and fewer large chain stores, instead smaller shops will take over, until eventually the land is so far away from the CBD there will be no shops or a very small amount of shops present. I predict that there will be fewer and fewer shops, as the land gets further away from the CBD.
This is because the CBD generally has good transport links and is already built up with department stores; it is an attractive area to start up a big store and to use the already large catchment area of the CBD, to gain more visitors to the store. The CBD has a zone of decay, along with a zone of improvement. The zone of improvement will then be used to build more stores. This continues because some shops, such as jewellers, clothing and shoe tend to cluster together to take advantage of competition. Smaller shops may set up in the CBD, near the zone of decay.
The land further out for the CBD is used for housing, as more and more houses appear, there is less room for shops so they become a scarcity among residential areas. The CBD is well accessible, through transport links and other means, such as new pedestrianized areas, and is close enough to everyone living in Kidderminster. Due to the fact that there are no shopping complexes in residential areas, there are no major shops there either. A closer look at our study area. The starting point was Baxter Avenue and we finished at the town centre. The highlighter marks out our exact route, and the numbers show out transect/survey points.
Method On the trip to Kidderminster we went through a predetermined scheme to ensure an efficient and systematic method of collecting and analysing data. The scheme was devised with the intention of allowing us to collect as much relevant and vital information as we need in order to complete our projects with accuracy and to enable us to have decisive conclusions. I took the north transect route and it spanned from the outskirts of the town centre (inner city) to the CBD. I collected information that would help me establish a link between pedestrian density (the number of people per unit of area e. g. er sq KM) in the CBD and the outskirts of the town centre (inner city) and other attributes of these areas.
On the north transect route there were 10 transect survey points where we would survey. As we went further down the transect points we got closer to the CBD. Firstly, at each transect point I scored the environment quality and shop quality out of five. This was recorded on the ‘Environmental Quality Score Sheet’. For environmental quality there were 5 areas to score: Safety for pedestrians crossing street, street cleanliness, exterior appearance of buildings, traffic/pedestrian segregation and vacant premises.
An area, which was very clean and had aesthetically pleasing buildings, with safe crossing points and almost all or all of the buildings were in use would score very highly. On the other hand an area where it was dangerous for pedestrians to cross, the buildings and surroundings were dirty or unsightly and there was a high number of unused or abandoned vacant premises would score low. The ‘Environmental Quality Score Sheet’ showing the tables for shop quality and environmental quality. It was very important that I filled this in as soon as I reached a new survey point.
We scored the shop quality of each survey point in a similar manner to the environmental quality. Shops were scored in; types of shop, land use groups and retail organisations and this was scored on a scale form 0-5. A survey point with many big department stores selling high and mid order comparison goods (larger, more expensive items bought less frequently) would score high, as opposed to an area without a shop, or an area with a shop only selling convenience goods (cheaper items, necessities, bought very often, e. g. food, paper etc).
Both of these surveys were given a total mark for each transect point. The environmental score survey was done as soon as we reached a new transect point. It was done to help me see the difference between land uses, as we got further towards the CBD. To keep the survey fair and reliable to achieve accurate results I must use the same uniform standard of marking for every transect route that I surveyed. Secondly, after recording the above data, we measured the frontage of 10 buildings in each transect point. This was done by pacing along the front of the building and recording the results.
After recording the frontages for ten buildings an average was found. We did this to get a more accurate representation of the frontage of the buildings and to account for anomalies, rather that just choose one example, which may not be a true depiction of the frontage of most of the buildings on that particular transect route. When measuring the frontages, only one person walked the paces along the front of the building, this was done for accuracy, because different people have different leg spans, which would influence the number of paces needed to walk the full distance of the frontage.
The frontages were measured to hep me establish a relationship between both: 1. Average frontage and pedestrian density, 2. Average frontage and distance from town centre. Before I had my results for my frontages I made the prediction that; “As you move closer to the CBD, the average size of the frontages will increase. ” I predicted this because I had previously made the prediction, “As you move close to the CBD there will be more shops and larger department stores. ” It is logical to assume large shops will need more space, and need a wide floor area for customers and goods.
Thirdly, a record of the buildings at each transect point was taken. This was done by surveying 10 buildings per transect. I took note of the land use classification, type of building, e. g. residential, supermarket etc, and number of stories and use of upper stories. This was done to obsever the changes in land use and number of storeys, as we got closer to the CBD. Houses in the first two transect points were recorded on the ‘urban transect field sheet. ‘ The record of building was continued, but as more and more shops appeared, this was done on a map of the remaining transect routes.
The map of our transect routes, on which we filled land use information. Finally we took a pedestrian count. It was vital to take a pedestrian count because my hypothesis relied on this information being collected. The pedestrian count was take at ever transect route, after we had finished every other part of the fieldwork. I collected data from transect point 8, other groups took data from the other transect points. Every single piece of data I have is primary data, apart form the pedestrian count, which is from other groups and is secondary data.
Evaluation of Method
I think the method used was good enough to give a general idea of land use, size and quality in relation to pedestrian numbers, but the results could have been more precise to give even more accurate results in the end. The scoring of environmental and shop quality is unreliable as it is hard to keep the same standard throughout. Another way in which the fieldwork could be improved is by using a measuring wheel for frontages as opposed to paces, which, again, leaves an opportunity for human error. Despite this the results are reliable enough to show the overall trend of pedestrian numbers when viewed against other factors.
Data Presentation Total E1 E2 E3 E4 E5 E6 E7 E8 E9 E10 – 9 10 40 27 22 65 97 69 113 Graph1 Graph showing the change of pedestrians along the transect routes. The larger the transect number, the closer to the CBD. N. B. No results were recorded for Transect point 1. My hypothesis stated that closer to the CBD the higher the pedestrian density. On my graph this trend is apparent. Although, there are some anomalies, the general pattern of growing pedestrian numbers is still followed. Total N1 N2 N3 N4 N5 N6 N7 N8 N9 N10 – 8 4 – 23 16 49 56 125 106 Graph2 showing the change of pedestrians along the transect routes.
The larger the transect number, the closer to the CBD. N. B. No results were recorded for Transect point 1 and 4. This second graph shows the same pattern as the first one. This provides further evidence of my hypothesis being correct. The closer to the CBD the higher the number of pedestrians. Data Analysis My hypothesis stated that: There will be a higher number of pedestrians closer to the CBD and There will be a larger range of shops closer to the CBD. Graph 1 shows how there is a general trend of increasing pedestrian numbers at each transect point.
This is not true for every reading as there are anomalies but there is defiantly a trend, which is continuing throughout the graph. An example of how this trend is followed by the following figures; At E2 there are 9 people, then at 7 there are 65 people and finally there are 113 people at E10. E9-E10 shoes a very big jump, as suddenly a large number of feature becomes accessible. Graph 2 confirms my thoughts, as this is from a different transect route, but follows the same pattern. This proves my hypothesis to be correct.
Graph 3 compiles all of the information in one graph, were we can clearly see the trend and how it remains the same in both transects. I used the aforementioned hypothesis, as it is typical for most CBD’s, it has been proven to be true for Kidderminster too. This trend is prevalent in the graphs because nearer to the CBD are more attractions. There are more things to do nearer the CBD, there would be no reason for a large congregation of pedestrians to gather outside a row of houses, but it would be expected to see more people near an area with a large number of shops and an area with other venues to occupy time as leisure activities.
Graph 4 includes shop quality into the mix. It shows how as the quality of shops increases a greater number of pedestrians are present. It also shows how there are a greater number and quality of shops closer to the CBD. An example of this trend is at N1 there are no pedestrians and no shops, at N6 there are 16 pedestrians and a total shop quality score of 10. 5 and finally at N10 there are 106 pedestrians and a shop quality of 15. This proves that pedestrian numbers increase with shop quality.
This graph shows the links between shop quality, pedestrian numbers and distance from CBD. It shows that the best and most diverse shops are located in the CBD and many pedestrians are present in the CBD. This helps me to conclude that the CBD is usually an area with many high order shops and the pedestrians are attracted to these features. This graph follows this pattern because, as stated in my hypothesis, pedestrians are attracted to a large number of high order shop selling comparison goods and large department stores.
These shops are generally found in the CBD, so the overall pattern is that pedestrians are gathered at the CBD, to visit the department stores. This patter is typical for most CBD’s. During our investigation, some of the results we gathered were anomalies. The main reason to explain this is that there was very heavy rain, and some area had indoor areas, or roofs in open area, where many people stayed to escape the heavy rainfall. If there were no weather complication, I would expect more streamlined results, following the trend more closely.