Beverly Chan | Critical Cartography: Mapping Vulnerabilities - Who is most at risk in the event of a climate disaster?

This macro-scale project explores IHDI scores and colonial legacies as two possible measures of climate disaster vulnerability. Global datasets are selected, aggregated, and joined for spatial and graphic analyses. To the question, ‘Who is most at risk in the event of a climate disaster?’ I found that there are many ways to answer this, each resulting in a different map. Therefore, this study is equally about familiarising myself with GIS processes generally, learning to work across large datasets from multiple timeframes, as well as understanding how risk maps get made and adopting a more critical approach to GIS for policy and public legibility. Additionally, although global-scale analyses provide a useful overview to study interconnected phenomena (like climate disasters) they must be supplemented with multi-scalar, critical, contextualized analyses if risk assessments are to guide mitigation and migration policies on the ground. Going forward, I hope to link global-scale with city-, neighbourhood/district-, street- scale studies on climate livelihoods and migration patterns of humans (and more-than-humans, if possible), particularly in East and Southeast Asia.

GIS Presentation
Project Methods

William Killian | Mapping Invasive Plant Risk Areas with Land Cover Change Data - 1990 to 2020

This project uses QGIS to assess land cover changes in Connecticut between 1990 and 2020 to identify areas most vulnerable to invasive plant species. Raster data from the National Land Cover Database (NLCD) and vector data from the Connecticut DEEP were processed to detect land use transitions. The methodology included clipping, cross-classification using the Semi-Automatic Classification Plugin, raster-to-vector conversion, and tabular joins to label changes and assign ecological risk. High-risk areas, such as farmland transitioning to shrubland, were identified based on the likelihood of disturbance-driven invasive growth. Final outputs included a color-coded risk map showing high (red) and low (yellow) risk zones, supported by ground truthing through satellite imagery and site observations. Although spatial datasets on invasive species were limited, the project draws on ecological knowledge and peer-reviewed studies to inform risk classification. This work provides a scalable GIS framework for visualizing and prioritizing invasive species threats and highlights the critical role that human land cover changes play in accelerating ecosystem vulnerability.

GIS Presentation
Project Methods

Manuel Bahillo | Mapping Sudan Conflict October 2024 to April 2025

The conflict in Sudan has become the most critical in the world regarding humanitarian assistance. Since the beginning of the war, humanitarian aid has helped millions of people, but the conditions have worsened as the conflict has prolonged for years. In this sense, we identify the most critical points in Sudan to locate humanitarian aid by obtaining data from ACLED and analyzing indicators like location of battles and number of fatalities. Additionally, with satellite images from Sentinel-2 L2A and Google Maps we identify the exact location of battles and selected urban targets from military forces.

GIS Presentation
Project Methods

Alexander Huang | Rent burden in New York City

This project explores the spatial relationship between the severe rent-burden population and affordable housing development in New York City. The project questions whether affordable housing is being built in locations with the greatest need. Using the rent-to-income data from the American Community Survey and the affordable housing data from the New York City Housing Preservation and Development, I was able to develop an index to highlight underserved areas. Results indicate particular zones of mismatch between the supply and demand.

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Project Methods

Mehr Khwaja | New York City’s Facial Recognition Surveillance Landscape

This project explores the correlation between racial demographics and facial recognition surveillance in New York City using QGIS. Two maps were generated: one visualizing racial demographics by community district and another plotting surveillance camera locations from Amnesty International’s dataset. The analysis aimed to assess whether racial composition correlates with increased surveillance. While initial mapping suggested a potential overlap, further investigation revealed that the distribution of surveillance cameras was more closely associated with protest activity and the Lower Manhattan Security Initiative rather than race alone. These findings underscore the importance of considering political and security factors in surveillance infrastructure placement.

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Project Methods

Ian MacPherson | Deforestation in East Kalimantan during construction of the Balikpapan-Samarinda Toll Road

Borneo has long been recognized as a hotspot for the deforestation of old growth forest for the production of timber, paper, and, today, palm oil. In light of Indonesia’s decision to relocate its national capital from Jakarta to a brand new city in East Kalimantan, the region is also now seeing unprecedented urbanization as well. In particular, the construction of the Balikpapan-Samarinda Toll Road was a turning point for the region, symbolizing the intensification of extraction region-wide while also creating the enabling conditions for the eventual construction of the city of Nusantara. I analyzed deforestation in the region by examining land cover change. I found that deforestation was most severe within a 1 km radius of the Toll Road, and was nearly 3 times worse than before construction began. This trend is important to continue following as urbanization in the project area continues to accelerate, with uncertain consequences for East Kalimantan’s future.

GIS Presentation
Project Methods