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Important Notice

This analysis is based on a small, biased sample and should be treated with caution. Results may not be representative of broader patterns. Please interpret all findings conservatively and consider limitations before drawing conclusions.

HeiGIT · GIScience Heidelberg — data explorer

Inequality and the composition of climate-disaster displacement

An interactive companion to a research study. It shows, for sub-national regions of low- and middle-income countries, how unequally wealth is distributed and how much climate disasters displace people — and how the two relate. Explore the map, then read the charts below; every term is explained.

How to read this dashboard (30-second guide)
The study asks a simple question: when a flood or storm hits, does inequality shape not just how much harm occurs, but what form it takes — in particular, how many people are forced to leave their homes (displacement)? Here is what you are looking at:
A region = a province/state (“admin-1”), the level the study works at.
The map colours each region by a measure you pick (top-right of the side panel).
Displacement rate = people forced to move ÷ people exposed — a share, not a raw count.
Hover a region for its value; click it for its full profile; scroll/drag to zoom.
The charts below summarise the study’s statistical findings, in plain language.
Filter the disaster events by year and hazard type (side panel) — map & charts update live.
Scope & caveat: low/middle-income countries only; patterns are associations, not proof of cause.
Scroll to zoom · drag to pan · names appear as you zoom in

Map layer

Filter disaster events years & hazard

Play through the years, one at a time

Region profile hover or click

Click any region on the map to see its full profile — wealth, inequality, development, and its disaster-displacement record.

Finding 1 · Is inequality linked to displacement?

Each row is one statistical result. The dot is the estimated effect of inequality on the displacement rate; the line is its 95% uncertainty range. If the line stays fully right of the dashed zero line (shown in red), the link is statistically clear. “Within-country” compares a country to its own past — the most rigorous test.
Positive = more inequality goes with a higher displacement rate. Source: paper Table 2.

Finding 2 · Which kind of harm does it shape?

The same inequality effect, measured on three different disaster outcomes. It is clearly strongest for displacement (people forced to move) and weaker / uncertain for deaths and for the broad “people affected” count — inequality shifts the composition of harm toward displacement.
Bars = effect of a 1-SD rise in inequality on each outcome’s rate; whiskers = 95% range.

Finding 3 · Seeing it event by event

Every dot is one climate disaster. Further right = it struck a more unequal region; further up = more people were displaced per person exposed. Colour = world region. The red line (averages by inequality group) drifts upward.

Finding 4 · The trend, simplified

Regions sorted into ten equal groups from least to most unequal (left → right). The line shows the average displacement rate in each group — it rises with inequality: more unequal places tend to convert a disaster into proportionally more displacement.

Glossary — what each measure means

Data & provenance. MERGE dataset (DOI 10.5281/zenodo.16837694) · Global Data Lab Area Database (asset-wealth inequality) · IDMC (displacement) · EM-DAT (deaths, affected) · WorldPop (population exposure) · Natural Earth admin-1 boundaries (public domain, simplified ~4 km for display). Region values are admin-1 aggregates (most recent available year) keyed by ISO-3166-2. This page is fully self-contained (no internet or external requests). It is a companion to the study for exploration and demonstration — associations shown here are not causal claims, and cover low- and middle-income countries only. · Built at HeiGIT · GIScience, Heidelberg University.