Dashboards on Urban Health Using the MedSat Dataset

The MedSat dataset provides a rare and valuable view into the intersection of environmental conditions, healthcare trends, and demographics across England. By combining high-resolution satellite imagery with detailed tabular data—including prescription rates, environmental indicators, and sociodemographic metrics—MedSat enables new forms of cross-disciplinary research.

However, the dataset’s scale and complexity pose a significant barrier to accessibility. Covering all of England’s Lower Layer Super Output Areas (LSOAs), it represents a vast and heterogeneous resource that can be difficult to navigate without appropriate tools.

To address this, we are developing interactive web-based dashboards that make MedSat’s data explorable and actionable. The aim is to enable researchers, policymakers, and interested citizens to engage with curated analyses directly in the browser, without the need for technical expertise or specialized software.

The main challenge is designing an intuitive interface that integrates diverse analytical methods, supporting meaningful exploration across multiple data types. Each student project presents a focused case study, which are complex and in-depth analyses at the intersection of health, environment, and society, delivered through an accessible interactive dashboard.

All projects are 2025 final-year MSc dissertation projects in Advanced Computing, conducted within the Department of Informatics at King’s College London, under the supervision of Linus Dietz.

Mapping Health Through Nature: Linking Quantified Park Qualities to Spatially Resolved Prescription Data

Green spaces such as parks are widely recognized to promote public health, offering opportunities for physical activity, social interaction, stress reduction, and overall well-being. Current research explores how specific park characteristics, such as proximity, accessibility, design, and other features, can influence health outcomes, highlighting the importance of evaluating not just the presence of parks but also their quality and usability. More recent studies have also developed a range of methods for quantifying park quality, allowing for more precise analyses of its relationship to health outcomes. While research in this area continues to grow, notable gaps still remain, especially in the integration between quantified park qualities and real-world, spatially resolved health outcome data. Many current studies rely on self-reported health data or broader associations which limit the accuracy of their findings. Moreover, conventional approaches often use static buffer distances to estimate park’s areas of influence, however other evidence suggests that park accessibility is shaped by a broader, more complex range of spatial and environmental factors. This report aims to address these limitations by building upon a recently proposed framework, and further quantifying the health aspects identified in their taxonomy of six health-promoting activity types. The same methodology will be used to score parks within England based on their health-promoting features and qualities. These scores will then be spatially linked to MedSat prescription data to analyze any possible correlations between different park qualities and health outcomes, including depression, anxiety, diabetes, hypertension, and asthma.

Tom Maulding, Advanced Computing

Walkability and Cardiovascular Health in Urban England: An Interactive Dashboard for Public Health Insights

The United Kingdom faces longstanding and persistent public health challenges linked to physical inactivity. Current evidence suggests that neighbourhood environmental characteristics – including walkability, greenspace availability, and air quality – substantially influence health outcomes. However, previous research has often been limited by coarse spatial units and the use of aggregated statistics, as well as by the reliance on restricted sets of urban and environmental variables. This underscores a need for fine-grained, multi-dimensional data to better determine these associations. This investigation will examine how neighbourhood walkability impacts the incidence of obesity and obesity-related illnesses within urban environments. It will capitalise on the recently published MEDSAT dataset, which offers high-resolution spatial data on health and environmental indicators across all Lower Layer Super Output Areas (LSOAs) in England. By integrating detailed socio-demographic data with satellite observation-derived environmental metrics, MEDSAT enables an in-depth analysis of how walkability correlates with community health outcomes in London. By making use of this dataset, this investigation aims to bridge the gap between broad epidemiological trends and the local-level determinants of health. The methodology will involve developing a walkability index for London’s LSOAs by combining MEDSAT variables with additional geospatial data, including street network connectivity, availability of dedicated pedestrian walkways, and accessibility to fundamental amenities, including supermarkets and pharmacies. I will then analyse the relationships between walkability and health outcomes of interest, including proxies for obesity, diabetes, and cardiovascular conditions, whilst accounting for secondary environmental factors, such as green space access and NO2 pollution levels. Finally, the findings will be visualised through an interactive dashboard, enabling urban planners and public health stakeholders to explore spatial patterns and identify areas where improving walkability and environmental conditions could produce significant health benefits.

Benjamin Pike, Advanced Computing