IB GEOGRAPHY
INTERNAL ASSESSMENT
To what extent do symptoms of urban stress change as you travel away from
the CBD of Lausanne, Switzerland?
STUDENT CODE: jnv597
004417-0022
WORD COUNT: 2500
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A study on the impact of urbanization on noise pollution and pedestrian movement in lausanne, switzerland. The study uses data collected from two transects and analyzes the correlation between traffic congestion, pedestrian infrastructure, and green spaces. The results show a significant impact of traffic congestion on noise pollution and a weak correlation between pedestrian infrastructure and pedestrian movement.
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IB GEOGRAPHY
INTERNAL ASSESSMENT
To what extent do symptoms of urban stress change as you travel away from
the CBD of Lausanne, Switzerland?
STUDENT CODE : jnv 004417 - 0022 WORD COUNT: 2500
TABLE OF CONTENTS
- I: GEOGRAPHICAL CONTEXT AND RESEARCH QUESTION
- I.I: GEOGRAPHICAL CONTEXT
- I.II: THEORETICAL BACKGROUND
- I.II.I: DISTANCE DECAY MODEL
- I.II.II: CORE-FRAME MODEL
- I.III: RESEARCH QUESTION
- I.II: HYPOTHESES
- II: SAMPLING METHODS
- II.I: LOCATION AND DISTANCE
- II.II: TIME
- II.III: METHODS
- II.III.I: BIPOLAR STUDY
- II.III.II: NOISE STUDY
- II.III.III: PEDESTRIAN STUDY
- II.III.IV: TRAFFIC STUDY
- II.III.V: LAND-USE
- II.IV: SPEARMAN RANK
- III: DATA PRESENTATION AND ANALYSIS
- III.I: HYPOTHESIS 1 โ INCREASING NOISE POLLUTION DUE TO HIGHER TRAFFIC CONCENTRATION
- INFRUSTRUCTURE III.II: HYPOTHESIS 2 โ INCREASING PEDESTRIAN CONCENTRATION DUE TO MORE DEVELOPED PEDESTRIAN
- III.III: HYPOTHESIS 3 โ INCREASE IN PRESENCE OF GREEN SPACES DUE TO CHANGE IN LAND-USE
- IV: CONCLUSION
- IV.I: HYPOTHESIS 1 โ ACCEPTED
- IV.II: HYPOTHESIS 2 โ PARTIALLY ACCEPTED
- IV.III: HYPOTHESIS 3 โ ACCEPTED
- V: EVALUATION........................................................................................................................................
- VI: REFERENCES........................................................................................................................................
- VII: APPENDICES.......................................................................................................................................
Lausanne is the largest city of Canton Vaud, with an estimated population of 137'810, making it the fourth most populous city in Switzerland.^2 (^2) โLausanne Population 2021 (Demographics, Maps, Graphs).โ WorldPopulationReview , 2021, worldpopulationreview.com/world-cities/lausanne-population. Accessed 22 Nov. 2021. Figure 2 : Map of Switzerland (map taken from DMaps and annotated using GoodNotes)
I.II: THEORETICAL BACKGROUND
I.II.I: DISTANCE DECAY MODEL
Distance decay is used to describe the effect of distance on interactions between two separate locations. This concept is essential to spatial analysis and is commonly represented graphically by a curved line swooping downward with increasing distance along the x-axis.^3 This concept links to our exploration as we aim to explore the effect of distance on the symptoms of urban stress as we move away from the CBD of Lausanne. (^3) Pun-Cheng, Lilian S.C. โDistance Decay.โ The Hong Kong Polytechnic University, 23 Feb. 2016. Figure 3 : Diagram illustrating the Relationship of Interaction Intensity with Increasing Distance to model Distance Decay (created using Goodnotes)
I.III: RESEARCH QUESTION
The research focus of this assessment will be on topic G, Urban Environments, more specifically Urban Stress, leading to the following research question: To what extent do symptoms of urban stress change as you travel away from the CBD of Lausanne, Switzerland? I.II: HYPOTHESES
1. As we move away from the CBD, there will be lower traffic congestion and concentration of vehicles, resulting in decreases levels of noise pollution. 2. As we move away from CBD, we will observe lower levels of pedestrian movement, thus the pedestrian infrastructure available will decrease in quality and concentration. 3. As we move away from CBD, commercial land-use will decrease, consequently increasing environmental quality due to an increase in residential areas, allowing a higher proportion of green spaces. II: SAMPLING METHODS A range of primary data points was collected using a sampling method to investigate the relationship between urban stress and distance. We narrowed it down to stratified line sampling, dividing the population into groups and systematically sampling each group. It was selected since it is very flexible, allowing for examining correlations between subsets, which may help answer our research question.^5 (^5) โRoyal Geographical Society - Geography Resources for Teachers.โ Rgs.org , 2021, www.rgs.org/schools/teaching-resources/sampling-techniques/. Accessed 28 Nov. 2021.
II.I: LOCATION AND DISTANCE
The investigation started at Lausanne-Flon, the PVLI, where we travelled North on the first day and South-West on the second day, allowing us to collect data in different areas to help establish a more accurate general trend. II.II: TIME The investigation occurred on the first day during the afternoon and during the morning rush on the second day, during a working week. Our investigation was performed over two days^6 to allow each route to be investigated fairly and to measure the effect of the distance across the whole working day, increasing the reliability of the further analysis. (^6) 8th and 9th of November 2021 Figure 5 : City of Lausanne with study transects showing route for both days (Google Maps 2021, annotated using GoodNotes)
Figure 6 : Example of Bipolar Survey (Transect 1 โ Stop 1, Croisettes)
II.III.II: NOISE STUDY
Due to rapid urbanisation, noise exposure is increasingly perceived as a risk factor for various health issues. The average noise decibels were measured using a mobile application, 'Decibel X', based on a 1-minute period. It allowed us to collect each stop's minimum, maximum, and average noise level values to examine the environmental aspect of urban stress. This was done by moving away from the rest of the group to a more isolated area to reduce external noise, which could bias our results. Figure 7 : Example of Noise Study with screenshot from โDecibel Xโ Application (Transect 1 โ Stop 1, Croisettes)
Interpretation of various types of transportation provides more insight into traffic movements. II.III.V: LAND-USE The land-use observations allowed us to get insight into the types and quality of infrastructure in CBD and its suburbs. We categorised infrastructure and graded it according to a scale of 0 (not present) to 5 (present). We would choose a starting point within our collection area to ensure a clear direction to follow when looking for buildings, reducing the chance of miscounts. We walked 200 paces in the chosen direction while tallying land use and estimating building height. Figure 9 : Example of Traffic Study (Transect 2 โ Stop 3, UNIL Sorge)
II.IV: SPEARMAN RANK
The Spearman's Rank Correlation Coefficient value is a statistical measure of the strength of a relationship between two data sets. This data analysis helped us analyse the relationship between variables and distance from CBD factually instead of personal interpretation. The coefficient (๐ ๐ ) is calculated using the formula: ๐ ๐ = 1 โ ( 6 โd^2 ๐^3 โ ๐
The answer will always be between 1.0 (a perfect positive correlation) and - 1.0 (a perfect negative correlation). An ๐ ๐ of 0 indicates no association between ranks. Figure 11 : Spearman Rank Correlation Coefficient Value Scale Figure 10 : Example of Land-Use Survey (Transect 1 - Stop 1, Croisettes)
III: DATA PRESENTATION AND ANALYSIS
III.I: HYPOTHESIS 1 โ INCREASING NOISE POLLUTION DUE TO HIGHER TRAFFIC
CONCENTRATION
Nearby areas of the CBD are experiencing increased congestion, leading to numerous urban stresses, including noise pollution. Experiencing the impacts of urban stress on humans and the environment is harmful when noise pollution levels exceed 85 decibels. With the concentration of traffic, we can expect levels of noise pollution to rise as we move closer to the CBD. Figures 12 and 18 illustrate traffic concentration and noise pollution using tri- variable charts. Figure 12: Graph of Noise Pollution according to Traffic for Transect 1
As we approach the CBD along Transect 1, noise levels and vehicle numbers show an overall positive trend. Stops 1 to 3 are residential areas, so do not have high traffic levels. Although low congestion is seen, the noise level is relatively high at stops 2 and 3. It is accounted for by construction at stop 2 and noise coming from lawnmowers, kids on afternoon break, and a large highway near stop 3. There is an anomaly along stops 6 and 8 as noise levels and traffic concentration decrease. Traffic is heavy at stop 6, as it is one of the main roads entering and exiting Lausanne's CBD, with many commercial buildings, schools, and other transport lines that all contribute to a noise level of 66.4dB. Stop 7, even with much lower traffic concentration, has an almost equal noise level, 64.3dB, to stop 6. The spatial organisation of buildings around the road creates an echo, increasing the noise level. Stop 8 is a mainly pedestrian area with only one road. Due to the buildings around the square and the non-busy time of day, the square has a quieter sound level than previous stops. Figure 13 : Photo taken during data collection at Vennes (Stop 2, Transect 1) Figure 14 : Photo taken during data collection at Fourmi (Stop 3, Transect 1)
Stops 2 and 3 have relatively high noise level values (57.8-62dB), while traffic concentration is low. Both sites are close to the metro, which passes by frequently, increasing the noise level. Stop 3 is located close to a highway connecting three main cities along the Lac Lรจman. Stop 4 is located in a closed-off residential area next to a highway and metro station. The plastic screens separating the areas from the highway reduce the noise level by absorbing part of it, explaining the drop in noise levels despite the increase in cars. At stop 8, noise levels measure 60dB while vehicles are fewest due to several buildings under urban renewal, contributing to the elevated noise level that hides the one-lane road. Figure 19: Map comparing the Number of Lanes per stop with Noise Pollution Levels (Google Maps 2021, annotated using Goodnotes)
Figure 1 9 (Key) Figure 19 is a map showing a correlation between the number of lanes at each stop and noise, which conceptualises the trend. A road with more lanes typically indicates it is used often and is part of many routes, meaning a higher traffic concentration and noise pollution. It generally follows the hypothesis, especially for Transect 1, where the noise level gradually increases as you get closer to CBD. Null Hypothesis ๐ป 0 : There is no correlation between traffic congestion and the level of noise pollution at 5% significance. Alternate Hypothesis H 1 : There is a correlation between traffic congestion and the level of noise pollution at 5% significance. Total Vehicle Concentration compared to Noise Level Spearman Coefficient Value
P-Value 0. Table 3 : Spearman Rank Coefficient and Probability Values for Total Vehicle Concentration and Noise Level