Geography Urban Fieldwork

What were our hypotheses?

1. Environmental quality decreases as distance from the CBD increases

2. Land use changes with distance from the city centre and allows us to see distinct zones, CBD core and frame.

Why was Birmingham suitable?

Has a clear core-frame structure

Wide range of land uses

Small enough city that we could collect data along a transect through different urban zones

Safe and accessible site

Why did we choose these sites?

Along a transect from urban fringe to city centre

Representative of different zones- allows comparison

Range of land uses and environment

Safe and accessible

What secondary data did we use & why?

Commercial building rents- shows where land value is greatest, indicating demand for land and explaining land use patterns

OS map- shows our transect and some land uses, showing that it varies

Commercial building rents analysis

Shows that rents are highest in the city centre and decrease away from the CBD. This suggests land values are greatest in the city centre where accessibility, pedestrian flow and business activity is highest, so businesses are willing to pay higher for premium locations. Further out, demand decreases so rents are lower.

Commercial building rent concusion

Supports the enquiry question, showing that one important urban characteristic, land value, changes with distance from the CBD. Particularly supports Hypothesis 2, land use, as it helps explain why the CBD has higher density commercial land uses, whilst areas further away have lower value land uses.

OS map analysis

Shows the investigation followed a transect, passing through areas with different land uses, including the CBD.

OS map conclusions

Shows Birmingham is a suitable location as the transect passed through different zones, representing a range of locations from CBD to frame, increasing the validity of the investigation.

What was our primary qualitative data collection method?

Annotated photographs

Method for annotated photographs?

At every site, we used a camera/mobile phone to take a photo then annotated the evidence of land use, environmental quality, pedestrian activity and building characteristics. We coded the annotations positive and negative, making it easier to compare.

Annotated photos justification

Provides accurate visual representation of each site.

Quicker than a sketch.

Can help reinforce and explain our other data.

Annotated photos conclusion

Showed that sites in the CBD had more positive characteristics (e.g. more well maintained, pedestrianised, pedestrian safety measures, wide pavements, evidence of investment in infrastructure). Further out there were more negative features (e.g. graffiti, vacant buildings). There were some anomalies, like unusually positive areas in the frame, but most locations fit the trend. These findings supported higher levels of pedestrian activity and commercial land use in the CBD.

Limitations of annotated photos

Only captures one angle/snapshot, so may not represent the whole area.

The was bias in choosing which part of the site to photograph.

Annotated photos suggested improvements

Take a panorama to represent more of the area or multiple photos of the area.

Revisit at different times of day/week/year for greater reliability.

What were our two Primary quantitative methods

Environmental quality survey

Pedestrian count

EQS method

Data was collected electronically using the survey123 app at each site so results were geo-located. We scored litter, graffiti, noise, traffic, greenery and building condition to produce an overall score for each site.

What presentation method did we use for EQS and why?

Proportional circles map using survey123 app.

It allowed us to compare the circle sizes/ratings and spot patterns.

EQS conclusion

The environmental quality was much higher in the core than the frame. This could be because the businesses and the council invest more money in maintaining busy central areas in order to attract customers.

EQS justification

Allowed us to collect a lot of information in a consistent and time effective way.

Quantitative so easy to present and compare

Survey123 app geolocated data so it was easy to present

EQS limitations

Subjective- reduced reliability

May vary lots at different times of day/week/year

The first few were hard to rate as we had no comparison/point of reference.

EQS improvements

Revisit at different times of day/week/year to increase reliability.

Discuss as a group to increase reliability.

Land use method

Onto printed large-scale versions of maps, we identified our location then recorded the ground floor use of every building along the transect using codes/abbreviations for each category of land use.

How did we present land use data and why?

Pie chart- We tallied up the different categories at each section of the transect, and presented each section’s data as its own pie chart.

Clearly shows proportion and allows clear visual comparison between sites.

Was easy/quick to make using excel.

Land Use justification

Recorded every building- good reliability

 

Mostly objective

Land use limitations

Slightly subjective as some were hard to categorise (reduces reliability).

Only includes ground floor uses so not fully representative (reduces accuracy).

Land use improvements

Record every visible use of the building, including upper floors (could use google maps to help).

Categories could be more specific to help categorise all the uses more easily.

Land use conclusion

The most prevalent categories in the frame were local independent retailers and caterers, and some derelict sites, whereas the core contained mostly major chain retailers and caterers. This could be because the cost of the land in the centre was highest (backed up by secondary data) as the land was most favourable so only the largest chains could afford to pay premium prices, while smaller businesses are forces to locate further from the core.

What was our overall sampling method and why?

Systematic sampling

We measured at set intervals along the transect, ensuring data was collected consistently without bias, to make the patterns more trustworthy.

Overall strenghts

Systematic sampling method- consistency

We collected both qualitative and quantitative data, so we could use the different sets of data to reinforce the patterns we found.

+ individual strengths for all collection methods

Overall limitation

Data was only collected once so may not reflect different times of day/week/year (particularly photos and EQS)

(+ individual method limitations)

Overall improvements

Repeat at different times of day/week/year to improve reliability.

Sample size could be increased to reduce anomalies and improve reliability, by extending the transect into the inner city or collecting data along more than one transect.

(+ some individual suggested improvements for each method)