# Geography Coursework – Methodology – Centre Of Leeds’ CBD

For my geography project I visited Leeds to try and find the economic centre of the CBD of Leeds. I needed to collect land use data as this would help me investigate the first of my hypotheses which is the nearer to the centre of the CBD, the taller the buildings as I counted the heights of buildings in my area on the geography field trip and with the groups data of the building height of the whole CBD. Also I would have needed to count the pedestrian flow as this would help me investigate the second of my hypotheses which is there will be a higher volume of pedestrians nearer the centre of the CBD .The data collection area was near the centre of Leeds CBD as I collected my data around Briggate as the edge of the Leeds CBD is near the tall office buildings.

The two pieces of individual data that I collected was:

• Traffic count
• Environmental quality assessment

The pieces of group data we collected was:

• Pedestrian flow
• Land use
• Building height

The individual secondary data that I will be collecting is Land values

The structure of the day was that we were going to split the day into two halves. We collected the group data in the morning and the individual data in the afternoon so we had much more time to collect our individual data.

## Group Data

For our group data we split the CBD into grid squares and two people were responsible for recording the building height and land use for the buildings in the given area and to do four pedestrian flows and we did the pedestrians flow outside the Town Hall on Westgate.

We did this so we could cover more area and therefore the data collection techniques had to be the same throughout the whole year.

For the group data we calculated the Pedestrian flow in a certain area at four different times also we calculated of the building height of the buildings in my groups square and started straight after we got out off the coach. Also we did land use of the buildings for this we calculated what particular use a building would be.

We put letters on a map of Leeds that sod for type of the building e.g. a=commerce, b=administration etc.

All the data in the Group Data was to be shared between all the groups.

## Building Height

To collect data for building height I worked with a partner and we counted the number of windows of each building in our grid and used this as the height, we did this because we didn’t have the time or equipment to measure the exact heights. We then collected the whole of the year’s data and have a good number of buildings from each grid to see where the tallest buildings are also the Building Height was fairly easy at times as you had to count the floors on the outside of the buildings, but there were problems counting the building height as we agreed not to count the cellars, but some buildings on slopes had cellars at the back and ground floors at the front of the buildings and we did not agree to count these as well.

## Pedestrian flow

We marked out four points on our maps equally distant apart and took counts of people who pass us. One of our pair counted right to left and the other counted left to right so we could efficiently record everyone. We went to the Town Hall on Westgate and we counted the number of pedestrians who were walking either in or out of the CBD. We thought this was an ideal to do our pedestrian count as we were near the edge of the CBD, so it was an ideal place to count the number of pedestrians walking in and out of the CBD.

## Land Use

For this we used the ground floor land use of each building on our maps; we had certain categories and we put them in the ones which best fitted the land use. We did this because the categories gave an idea of the type of land and what it was used for. We then collected them with the rest of the year’s data on a database to see the different land uses around the CBD. We had filled in the land use of the buildings in a table which has all the number of the buildings. I think that the amount of categories that sort out the buildings was the right amount because if there were more categories it would have made it more complicated to organise the Land use on GIS, if there was less categories then it would have made it hard to organise the different types of buildings in the categories. Luckily we had successfully had no problems classifying the buildings into different categories.

## Individual data

For individual data I collected raw data for the two options I chose. I did this by going round Leeds CBD and recording the data. In the second part of the day we did Individual Data. I did 10 environmental quality assessments and I did 2 traffic counts as they took 5 minutes each and the environmental quality assessments were scattered around the Leeds CBD.

## Environmental quality survey

I did many of these all around the CBD of Leeds as I had done 10 environmental quality assessments and I had done many of these near the centre of the CBD as my investigation is to find the centre of the CBD of Leeds. I did many of the environmental quality assessments around the centre of the CBD (which I think it is near or on Briggate) and I did the rest of the environmental quality assessment sheets around the edges of the CBD. The reason I did the survey in different areas of the CBD was to see the difference of the quality of the environment throughout the CBD of Leeds. I also thought that this survey was important as the centre of the CBD is supposed to have the best quality of environment in the whole CBD of Leeds. As the table shows this is not true and the cleanest area is in Gourmet Pizzeria, St Paul’s Street.

## Traffic Count

Our group did the Traffic count in a busy location. We did our traffic on Bishopgate Street, beside Leeds Train station. The reason of us choosing the location was because it was at the edge of the CBD meaning the traffic that we had counted had been going in and out of the CBD. We did 3 traffic counts at different times but at the same location as we wanted to see the change of the traffic flow throughout the day. In our traffic count we had counted all the vehicles that came passed the road, cars, buses, taxis e.t.c. The most amount of traffic that had come past our point (the highest number of vehicles an hour) was at 2.30 pm and there was 1524 Vehicles an hour.

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