6B Urban Environments Fieldwork Flashcards
State the title of your human geographical fieldwork enquiry
To investigate how and why is Brick Lane changing?
What were your 3 hypotheses?
1) Brick Lane’s distinct and historic Bengali cultural character is still in evidence, but it is stronger in the south than the north where the street meets Shoreditch.
2) The economic health of Brick Lane is stronger in the north than the south as investment trickles in from Shoreditch and the redeveloped Spitalfields market.
3) The quality of the built environment is better in the northern part of Brick Lane as a result.
Name 3 risks associated with the enquiry and how you managed them
- One risk we potentially faced was muging. We managed this by staying in groups of at least 3 and having no valuables on show.
- Getting lost however had school contact number and maps of phone.
- Risk could have been heat stroke or hypothermia. We looked at the weather report in advance and made sure we had the appropriate clothing and footwear.
What primary and secondary data collection methods did you use?
Primary (quantative):
- Environmental Quality Survey
- Building Upkeep Survey
- Land Use Survey
- Questionaire
Primary (qualitative):
- Photo survey
Secondary:
- Google Street View analysis
- Report on change in a local urban community
- Historical maps and images, compared with today
Describe the process of collecting questionaire data and its postives and negatives
Method (Opportunistic):
- We first created the questionnaire by discussing the type of information we wished to collect. We decided we wanted to collect data on people’s use of the area and their views on the changes in both cultural and economic activity along Brick Lane. This would therefore provide us with data relevant for all three hypotheses.
- We created mainly closed questions (can only choose certain answers) with a few areas for ‘other’ ideas which are semi-closed questions.
- We put these questions into a table with a tally section.
- On the day we took an opportunistic sampling approach and asked passers by when it felt appropriate and safe to do so. We approached them and politely introduced ourselves before asking for the participant to answer our questionnaires and we tallied the answers down. We repeated this process as many times as was possible within our time constraints of an hour and a half, alongside collecting other data.
- We always collected questionnaire data when in pairs or threes for safety purposes.
Positives:
- Allowed us to gather data from a range of different perspectives.
- Some perspectives may have more historical knowledge of Brick Lane in the past and have also visited more frequently than ourselves so they may have directly witnessed change over time in the area which we would not have.
- It gives people opinions and qualitative data, not just numbers
- We can see the change by using a questionnaire because it gives us a better understanding of change over time.
Negatives:
- Closed question don’t give people freedom to give any answer they want therefore it forces people to choose an option that does not represent their actual views and shoehorns into a category. This may affect the accuracy of our data and validity of the conclusion we fraw from this data.
- May introduce bias because our sampling strategy meant we chose people we felt safe around and this may mean we got a bias in the type of person and opinion would get on the area which would affect the reliability and validity of our conclusions.
Describe the process of collecting EQS data and its postives and negatives
Method (Systematic - every 150m):
- We recorded x2 EQS in each Zone along our transect. Roughly every 150m. An EQS measures the quality of buildings, transport and public space by requiring the researcher to fill in 15 question questionnaire based on what they can see from a 360 perspective from where they’re stood.
- Each Q can be scored +2 to -2, which gives a total score that can range from -30 to +30.
- We would expect the quality of the built environment to be higher if gentrification is occurring; higher quality building upkeep, better kept public space.
Positives:
+ By completing two EQS in each zone we able to create an average score for each zone, so our data should represent the areas along our transect well.
+ By having equal spacing along our transect we could show how changes progressed along our transect.
Negatives:
- As it is heavily opinion based and everyone can have very different views of the environment around you as well as people could be basing it off of different parts of what they see.
- We collected our EQS data on one day in June, so the weather, traffic patterns etc on that day can influence our results and findings.
Describe the process of collecting BUS data and its postives and negatives
Method (Systematic - every 150m):
- After each section we would stop and observe everything that we saw and fill out our table which included rankings on whether we thought things like the doors, windows and driveways were Poor all the way up to High quality.
- We had discussed this amongst the group to make sure everyone agreed so that our results were most accurate.
Positives:
+ Since we all did it separately we could combine our results for an average.
+ We were able to cover wide areas and it was quick since we weren’t stopping for every 10m.
+ It gives a good general representation of areas despite looking over smaller areas and we had a good field of vision where we stopped so good representation of each section.
Negatives:
- 150m is quite a big distance so there may have been smaller areas we passed by with different statistics to the places we judged which could impact our results.
Describe the process of collecting LUS data and its postives and negatives
Method (100% smapling):
- We walked along our transect between the North and South of Brick Lane (Whitechapel High Street/Aldgate East in the South and Shoreditch to the North For every building we gave the ground floor a score from 0-5 using our land use key where 5 was a high order commercial HQ, 4 high order retail, 3 medium order retail like a chain store, 2 a low order shop such as a corner shop or takeaway.
- Using the standardised descriptions in the key we ensured accuracy from person to person. We also recorded a G where we saw a business which was clearly gentrified (deli, independent coffee shop, hipster barber etc) and a B where we could clearly identify visible Bengali culture community (Bangladeshi restaurant / cafe, textile shop, mosque etc).
- We were trying to prove that the closer you are to Shoreditch the higher the order of retail and the more likely you are to identify a gentrified business. The further south you move the more likely that the retail order is lower and the greater likelihood of ethic influence ad commercial land use
Positives:
+ 100% sample; we surveyed every building along our transect at ground floor level It gives us a large amount of data to make strong conclusions from making our conclusions more representative and accurate.
Negatives:
- Although we used a standardised key, there was some room for subjective interpretation of whether a shop might be a 2 or a 3, or a G or an B.
Describe the process of collecting photos and its postives and negatives
Method (Systematic - every 150m):
We took a photo at each sample site, to reflect the view of the area we are taking our EQS and Building Upkeep survey. This means we will have a photo for every 150m along our transect. We will also be taking opportunistic photos, these will be taken where we see evidence which helps us confirm or deny our hypotheses, such as evidence of specific cultural character.
Positives:
- It is photo evidence so it stops biasness and mistakes. It helps us to maintain first hand information which we can use to compare with the data and arguments that we create later on.
- Because a photo will have much better definition and you can look at it and analyse after being in Brick lane. A photo also lasts forever.
Negatives:
- It is relatively objective since we took photos of where we took our EQSs and we cannot edit the photos however the angle where we took the photo from could be subjective.
What are the different sampling strategy for primary data collection methods?
Random:
- In random sampling each point or individual in the study area as an equal chance of being selected. This method is usually done by randomly generating number or coordinates to choose location or subjects, which helps to reduce bias
Pros:
- Objective and removes unbiased
Cons:
- Time consuming and can give nonlinear results
- May not should representative progression if sites are clumped together for example groyne analysis and beach profile
Systematic
- Systematic sampling involves points at regular, fixed interval (e.g. every 10 meters along a beach). This method ensures an even spread of data collection across the study area making it easier to cover a large area consistently.
Pros:
- Highly representative of progression - good for BP and G
- Easy to cover a large area consistently
- Not as unbiased as random as you choose the interval
Cons:
- May miss natural variation between the sample sites which satisfied
Stratified
- Stratified sampling is used when the study area or population is divided into distinct groups or “strata” (such as different coastal zones). Sampling is then conducted within each stratum, which ensures that each key area or characteristic is represented proportionally in the results.
Pros:
- Allows us to see the variations and can be more representative as different groups/categories are proportionally represented.
Cons:
- More biased as we choose the categories and intervals
- Time consuming - beach profile, beaches with varying profiles - bias
Opportunistic
- Opportunistic sampling means choosing sample points or individuals that readily available or easy to access. It’s often used when time or resources are limited, although it may introduce bias since the sample isn’t entirely representative of the whole study area
Pros:
- Easy and simple to collecting which could making it more time efficient if time constrained
- Useful in an environment where safety could be compromised - tide/rockfall
Cons:
- Not fully representative for all data
- Most biased as you are choosing when and where suits
Evaluating secondary data sources
Google Street View analysis (online data source):
We went on to street view to look at the sites
- Really useful to look at changes over space because you can go along the whole road in street view. Can help us with landuse patterns we noted and provide a visual understanding of potential changes in cultural characteristics between the north and south of Brick Lane.
- Relatively recent which means that changes over time are harder to tell. Images can be quite blurred so may not be as helpful when checking land use.
Report on change in a local urban community (online data source):
We read this news article and analysed it to pull out information regarding changes in cultural characteristics.
- This is useful because it adds depth to our understanding of peoples’ perception of place which is difficult to collect data on the day. It also gives us background to try and understand some of the patterns we might notice within our data. It was also written quite recently which means this perspective is up to date.
- Journalistic work is always written with some internal bias and subjectivity. Therefore we cannot say this is completely representative of everyones’ views of Brick Lane. In terms of accuracy, the subjectivity means we must question how accurate information is that we collect from here.
Historical maps and images, compared with today (online data source):
We collected historic records on transport maps and street images of the Brick Lane to be able to consider what changes we have seen over time.
- Historical maps and images are helpful to understand changes over time. This is particularly useful for considering economic change to the environment in relation to BUS, land use and EQS. Might be better over time than space.
- We cannot always get photos of the same place we looked at and therefore comparison of changes can be quite difficult. Times in between photos/maps can be quite significant so might be difficult to see progression of changes.
How did you present your data and why?
Questionnaire:
We decided to use a tally chart.
- It is easy to create for both presentation and also collection so is very time efficient.
- As most questions only had one or two responses chosen it meant that a tally chart was visually very simple to analyse.
- Although most of our questions were closed, some were semi-open. Therefore with a tally chart we could also see the additional responses added in which was not possible
EQS:
We decided to use a radial diagram.
- The benefit of radial diagrams is that it allows us to look at a large amount of data in a compact format.
- It also allows for easy comparison of all three sectors for each individual variable and pick out trends.
- Additionally, it is easy to see where an individual sector does well or poorly.
- Radial diagram is the most visually effective form of presentation for easy analysis. This is much harder to compare with such a large amount of data, when looking at a bar graph or table.
LUS:
We decided to use pie charts.
- We can use a pie chart for land use survey coding because we are looking at what percentage of all the buildings surveyed had each different code. Having percentage comparisons when looking at land use is helpful because it provides accurate comparisons between different sectors due to it being proportional and it is easy for others to understand because we can all comprehend percentages and how significant that makes different codes to each other.
- As different sectors had different numbers of buildings, it meant comparing raw totals for each code made it hard to pick out patterns. Whereas by using pie charts it allowed for more accurate analysis through comparing proportions of different codes in each sector.
- With the land use profile pie charts the use of different colours for each code makes it very easy to compare proportions between the different sectors. This is helpful because it allows clear visual distinctions and makes it really fast and easy to see noticeable changes between the different sectors for example site A has no yellow compared to B and C which allows us to see easily that Bangladeshi cultural coding is not present in A.
BUS:
We decided to use a bar graph.
- A bar graph is an appropriate method because we are dealing with discontinuous data so a line graph would not be appropriate as we are not looking at something changing over time or something where the last data point influences the next.
- A comparison bar graph allows us to see how each sector compares with each other for each factor on the BUS. This is useful because it allows us to see the difference and changes across brick lane
Photo analysis:
- Annotating photographs as part of presentation rather than just having the photo by itself means that key aspects can be highlighted and then analysis is faster when looking at a range of photos.
- The use of photos within our data presentation is helpful because it provides a accurate visual representation that doesn’t fade like our memory.
What was your overall conclusion for hypothesis 1?
Overall conclusion:
Overall we can conclude that there is still strong evidence of Bengali cultural character in the south of Brick lane however this tapers off quickly as we move up the high street towards shoreditch
Justification:
- Overall we can see there is a clear change in the cultural characteristics in the buildings between sector A and C in regards to ethnic characteristics. 0% of buildings have a coding of B for evidence of Bangladeshi character in sector A, whereas in sector C, 50% of buildings were recorded with a B code and with sector B almost directly in between with 20%. This clearly suggests a progression of increasingly Bangladeshi character the further south we go. - However, as each sector is based on an average it is harder to see to what extent this changed across each sector and whether this created a distinct north to south divide, particularly in sector B
- When looking at the data from the questionnaire we found that it was Inconclusive because nobody stated any visible changes so we have no evidence to make any assumptions.
What was your overall conclusion for hypothesis 2?
Overall conclusion:
Overall we can conclude that the economic health of brick lane is stronger in the north than the south however the economic health in central brick lane is just as strong if not stronger than the north.
Justification
- When analysing the land use data we can see there is significantly more gentrification in A( 29.6%) than C ( 7.7%) which suggest more economic investment and health and there are slightly more high value building codes in A than C. Therefore suggesting greater economic health based on new investment, the further north you go along the Brick Lane. However, the building codes and amount of graffiti show there is some inconclusive aspects to this hypothesis.
- However when looking at building upkeep sector B has the highest scores overall with 20 as the average total score. However, sector A gained 16 whereas sector C only gained 8. This suggests that whilst we cannot completely support our hypothesis, we can suggest that in terms of upkeep, the further south sector is significantly lower than sectors further north. As upkeep is often closely correlated to the amount of money available for maintenance and improvements, this could suggest that the south is the least economically healthy sector, which does fit our hypothesis.
What was your overall conclusion for hypothesis 3?
Overall conclusion:
Similar to hypothesis 2, overall we can conclude that the built environment is better in the north than the south however the built environment in central brick lane is just as strong if not stronger than the north.
Justification:
- In regards to the the building upkeep survey we can see that the total average score of sector A (16) is double that of Sector C(8). however Sector B has the highest total of 20. This suggests that whilst we cannot completely support our hypothesis, we can suggest that in terms of upkeep the further south sector is significantly lower than sectors further north.
- However based on the EQS results we can see that we cannot agree with the hypothesis. This is because sector C overall has the highest score for EQS with -9 average which is furthest south whereas the further north you go the worse the EQS average score becomes, from -10 in sector B and -12.5 in sector A.
