Congratulations to our winners this year. The SLA Student Awards 2022 reached new goals this year with 21 entries from the following universities: Leeds, University College London, Greenwich, Newcastle, Manchester and Sheffield.

Because we had such a high level or entries this year, we decided to award 1st. 2nd and 3rd place awards for both Masters and Undergraduate categories.

Masters Award winners 2022

  1. Loubna Sasso – University College London
  2. Urmi Shah – Greenwich University
  3. Kexin Peng – University of Manchester

Undergraduate Award Winners 2022

  1. Matthew Browne – University of Leeds
  2. Alexandria Archer – University of Leeds
  3. Gemma Parfitt – University of Leeds

Meet our winners

Masters Award 2022

1st Place – Loubna Sasso, UCL

Dissertation Title: ‘Exploring areas of upgrade based on the 15-minute city concept – A case study of London’

Biography – Loubna is a recent graduate of the University College London with an MSc in Smart Cities and Urban Analytics at the Center of Advanced Spatial Analytics (CASA). She has a passion for urban innovation and the use of data and technology to inform urban strategies, policies and design solutions that address current and future global challenges. With experience in urban design and geospatial analytics, she is currently seeking an opportunity to expand on her passion and put her knowledge and skills in the field of geospatial sciences to practice.

Dissertation Synopsis – In collaboration with Transport for London, the project seeks to address climate change through a long term sustainable decarbonization strategy. This involves rethinking the way cities operate and accordingly how people interact and function within them through the concept of the 15 minute city. The model is tailored to adapt to the context of London’s decentralized urban structure and accordingly every 100m grid spatial unit across the city is analyzed using the measures of proximity, diversity and density.  The methodological approach used R programing language to assesses proximity to groups of clustered services rather than dispersed standalone services. By doing so, the study provides insight on the performance of different areas across London based on their ability to efficiently satisfying multiple needs within a single 15-minute walk. Moreover, the methodological approach advances from other studies by providing a holistic approach that looks at diversity of destination clusters as well as demand accessing these services (i.e., the population density) whilst integrating a walking speed using a network analysis to calculate proximity from origins to destination attraction points. A normalized score between 0 to 1 is then assigned to the outcome of the proximity and diversity measures and the combined scores are plotted against the outcome of the population density to understand areas where demand is unsatisfied by proximity and diversity of services offered. The results can aid policy makers in understanding which areas in London are underperforming and therefore would benefit the most from investment upgrades to ensure equitable and inclusive spaces based on the fifteen-minute city concept.  Moreover, the results of the study can easily be integrated and act as extension to the existing TFL, Web-based Connectivity Assessment Toolkit platform (Webcat). Sharing the finding of this study with TFL can support the implementation of alternative modes of transport that align with the Mayor’s Transport strategy including increasing the number bus journeys to support communities where 15-minute city scores are low.

2nd place – Urmi Shah, Greenwich University

Dissertation Title: ‘Optimal Pedestrian Route Mapping based on Subjective Preferences.’

Biography – My degree as a postgraduate student at the University of Greenwich was centered on software development and data science solutions, including my dissertation on Geographical Information System. I am particularly interested in the use of data science solutions to network planning challenges. I am currently working as a data engineer at Geolytix, a retail location planning consultancy.

Synopsis of Dissertation – This project idea, aimed at both urban planners and policymakers working for creating pedestrian infrastructure, provides information on area and guidance on how to better understand pedestrians’ requirements to give them tailored navigational routes. It is designed to help planners when developing network projects and decision-makers to ensure mobility development.
Currently, major navigation applications do not provide an option for pedestrians to choose routes which are suitable for people who have a disability or want to take the safest route. While there are fewer navigation systems offering routes for physically disabled pedestrians, it is limited to wheelchair users and visually impaired pedestrians. The purpose of this project is to encourage walking by providing ten different route options to pedestrians and allowing to choose more than one route option for traveling. This project is intended to provide customizable route based on pedestrians’ choices (safety, accessibility, attractions, peaceful, etc.), which majority of navigation systems do not offer, and intends to help promote safer routes and walkability in the area by reducing pedestrian vulnerabilities in urban development.

An interactive QGIS Dashboard displays the result of a region’s most important characteristics by drawing attention to markers that each indicate a different attribute (safety, traffic volume, etc.) which could help city planners create a pedestrian road network that is both secure and convenient, for instance, by identifying high-crime areas and avoiding them. A walkability index is defined in the study which include safety, distance, accessibility for wheelchair users and visually impaired, time, points of interests, and four other factors. A new routing algorithm is developed based on Dijkstra which takes into account the ten-walkability index and suggests the most optimal path. The results confirmed that major navigation apps suggest routes which are quick and shortest whereas the algorithm created in the dissertation suggests routes which might be longer but satisfies the choices specified by the user for route selection.

3rd place – Kexin Peng

Dissertation Title:Tracking logging disturbances in the Amazon Forests (Mato Grosso) supported by daily time series of high-resolution Planet satellite imagery‘.

Undergraduate Award 2022

1st place – Matthew Browne, University of Leeds

Dissertation Title: ‘Solar Energy Generation: Assessment of Country Potential Against Performance with a Composite Indicator.’

Biography – I recently graduated in BA Geography from the University of Leeds, which I thoroughly enjoyed. Through this, I developed an interest in GIS which led to the focus of my dissertation and the decision to stay at Leeds to do the MSc GIS programme, which I have just started.

Dissertation summary – My dissertation was focused on solar energy and the determinants and barriers to its deployment at the country level. Through a review of relevant literature, factors influencing solar energy generation were established. These factors were then assembled into a composite indicator which assessed the solar energy potential of a country. A sample of 165 countries was used, which was important as other existing research into country-level determinants of renewable energy has generally used much smaller samples. Standardised results from the index were then compared with standardised data for actual installed electricity capacity from solar technologies, which allowed for a comparison between a country’s potential and current performance. GIS was used to display the results, with global results being explored before an in-depth analysis of Europe, the Middle East, Africa and East/Southeast Asia. For countries performing better than expected, a discussion of policies and reasoning behind their success took place to provide suggestions for the implementation of solar energy for underperforming countries.

A spatial pattern emerged with countries in the Global North generally performing much better than those in the Global South in the index. East Asia was the region having proportionally the most countries exceeding their expected potential, with Vietnam particularly providing a potential pathway for other developing countries. The Gulf countries of the Middle East achieved exceptionally high scores in the index but all fell massively short of these in actuality. The Middle East has the potential to be a global powerhouse in solar energy if it shifts away from its non-renewable intensive energy systems.

2nd place – Alexandria Archer, University of Leeds

Dissertation Title: ‘A Food Desert Framework: Exploring the relationship between food deserts and deprivation in Greater Manchester’.

Biography – As a recent graduate in BA Economics and Geography from the University of Leeds, I enjoyed homing in on my interests of geospatial analysis and welfare economics. Since graduating I have gone on to work as a Junior Analyst at Property Market Analysis.

Dissertation Synopsis – My dissertation builds on literature to quantify food deserts and provide a replicable framework to explore a chosen city’s relationship between food access and deprivation. The framework explores this relationship through creation of a composite index to measure food access, performance of regression analyses, and the interpretation of Lorenz curves. The research is evidenced in Greater Manchester and is designed so it could be applied more widely to other English cities.

Literature concluded that food access and its relationship with deprivation is not homogenous across cities in the UK and globally, prompting the creation of a transferable framework to explore different cities’ correlations. The research follows a quantitative approach using government and accessibility variables at the lowest super output area level to create the index.

No statistically significant correlations were found in Greater Manchester between the index and its variables and deprivation. The outcome concludes that deprived areas in Greater Manchester do not experience significantly worse food access conditions. However, associations implying worse transport access were observed in deprived areas. Interestingly, supermarket access across deprivation deciles was equal.

The use of this framework improves policy makers’ visibility into the factors that are exacerbating healthy food access disparity. This can enable strategies to be implemented to resolve these factors and enhance social equality.

3rd place – Gemma Parfitt, University of Leeds

Dissertation Title: ‘Developing a Premium Grocer Index Through a Scorecard: The Case for Whole Foods Market UK’.

Biography: I recently graduated from the University of Leeds studying BA Economics and Geography. I was particularly interested in the field of Retail Geography and Location Planning whilst at university therefore decided to make this the focus of my dissertation. Since then, I have joined Property Market Analysis as an analyst of the office and industrial market.

Synopsis of dissertation – My dissertation aimed to demonstrate how retail location planning can be used in practice to expand an existing network through using a scorecard. Location planning is an important part of a retailer’s store strategy as it determines where a retailer situates their stores which directly impacts revenue and brand presence. The scorecard is a retail term for an index as it considers key variables to formulate a scoring system and is achieved through looking at existing sites as well as considering significant factors that impact the performance of a store.

I chose to focus on Whole Foods Market in London due to its positioning as a premium grocer focused on healthy products as well as situated in areas characterised by a young and affluent demographic. Therefore, Whole Foods can be identified as a specialist retailer with a target consumer with a scorecard being particularly useful in this case. A scorecard specific to Whole Foods was produced after evaluating the location of their existing seven stores and considering existing literature on the target customer. The scorecard variables included: the London Output Area Classification, Internet User Classification, House Prices, Income, Health, and Transport measured through Public Transport Accessibility Levels. I also considered significant retail brands using Local Data Company data to identify retailers that align with Whole Foods in terms of location and target customer, as well as competitor analysis to avoid competitors in very close proximity to potential sites. Top High Street locations in London were found using GIS through the buffering method and four potential sites were recommended. The findings of this research demonstrate the scorecard technique for retail location planning which is particularly useful for specialist retailers to find locations which best capture their target consumers.

Congratulations to all our winners, we had such a great response of very good quality dissertations this year.