The investigation pertains to the syllabus of Option G: Urban Environments and, more specifically, noise pollution and pedestrian congestion.
Located in the Kowloon peninsula (Figure 2), Sham Shui Po (SSP) is an urban district within Hong Kong highly populated with low-income earners, low-skilled workers, and the temporarily unemployed. As such, SSP has earned the title of “the centre of poverty in Hong Kong” (Cheng 1). As one of Hong Kong’s earliest industrial and commercial areas, informal businesses and street markets, such as Ap Liu Flea Market (ALFM), have been and continue to be the lifeblood of this neighbourhood. Situated between Nam Cheong and Kweilin Street (Figure 3), Ap Liu Flea is one of the oldest street markets in Hong Kong and a popular destination for cheap, second-hand electronics.
SSP was designated as the fieldwork data collection site due to its physical and socio-economic features demonstrating apparent characteristics of an urban area, thus aligning with this exploration of urban social stresses. Furthermore, the grid-like pattern of this neighbourhood’s roads allows for primary data to be collected and recorded in an orderly manner.
How does proximity to the Ap Liu Flea Market influence the pattern of urban social stresses in Sham Shui Po, Hong Kong?
Urban social stresses will increase with proximity to the ALFM.
The Peak Land Value Intersection (PLVI) is a region within a settlement with the highest land value and accessibility. As a result of its easy accessibility in terms of transport networks and overall walkability, the ALFM may be labelled as one of SSP’s Secondary Land Value Peaks (Figure 3). Hence, one may infer that it is an area with high urban social stress. Despite having a relatively low land value, the ALFM’s accessibility may result in it being heavily and densely populated, thus resulting in higher rates of pedestrian congestion and noise pollution.
Data was acquired on Friday, November 11, 2022, from 10:00 am to 14:30 pm. Prior to arrival, groups of students were assigned field paths for which they were responsible for collecting data. Systematic sampling was used to determine the data collection points for noise pollution (Figure 4) to allow for the consistent observation of changes in urban stress. Convenient sampling was used for pedestrian congestion data.
Investigating noise pollution
Materials used
At all designated points, the Decibel X app was used to calculate the ambient noise at a distance - the average reading over one minute was recorded.
This methodology revealed the areas with heavy pedestrian and or traffic congestion, thus demonstrating its accessibility, one feature that a PLVI and or secondary land value peak must posses. Constant exposure to noise pollution commonly causes health problems including noise induced hearing loss, high blood pressure, heart disease, and stress.
This methodology’s use of convenience sampling revealed the distribution of pedestrian congestion in SSP, thus revealing the locations with higher accessibility which may therefore be labelled as one of SSP’s secondary land value peak (Figure 3).
To determine the strength of the correlations between specific indicators against proximity to the flea market, Spearman’s Rank Correlation Coefficient will be used. To calculate the Rs value from the rankings within the data sets, the following mathematical notation will be used -
\(R_s=1-(\frac{6Σd^2}{n^3-n})\)
Noise pollution will increase with greater proximity to the ALFM.
The bubble map shows that noise levels are highest in the centre sections (S5-8), with S7 being the only section with an average of 79-84 decibels. Contrarily, S9-12 had the least noise pollution, with S10-12 having an average of 61-66 decibels and S9 having an average of 55-60 decibels.