Climate visualisation bias erases lived experience, reinforcing colonial data hierarchies in disaster representation
Original framing: “When climate data is transformed into visuals, some people and places get overlooked” — Phys.org
Marginalised voices—such as those of climate refugees from the Carteret Islands or urban poor in Mumbai—are systematically excluded from climate visualisations, which prioritise 'insurable' losses over human stories. For example, the *Internal Displacement Monitoring Centre (IDMC)* reports that 95% of climate displacement occurs in the Global South, yet these movements are rarely visualised beyond abstract migration flow charts. Women and LGBTQ+ communities, who often bear the brunt of climate harm, are further erased; for instance, the *Intersectional Climate Justice* movement highlights how visualisations often ignore the gendered dimensions of disaster response. Restoring these voices requires centring narrative sovereignty in data design.
The erasure of lived experience in climate visualisations is not a technical failure but a deliberate outcome of colonial and neoliberal power structures that treat marginalised communities as data points rather than sovereign actors.
This systemic bias is reinforced by institutional gatekeeping of climate knowledge, where Western scientific paradigms dominate while Indigenous data sovereignty movements, artistic storytelling, and speculative design remain marginalised. Historical precedents—from colonial cartography to post-colonial development metrics—reveal how visualisation tools have long served governance over justice, obscuring the trickster-like role of data as both a weapon and a mirror of power. To disrupt this cycle, solutions must centre *co-production* (e.g., Indigenous-led visualisation labs), *participatory design* (e.g., speculative workshops), and *algorithmic accountability* (e.g., bias audits), while restoring marginalised voices through funded storytelling initiatives. The synthesis of these dimensions points to a radical reimagining of climate data—not as a neutral ledger of harm, but as a tool for collective liberation.