Missing Migrants on a Map

Missing Migrants on a Map

This visualization maps the global distribution of missing migrants from 2014 to 2021, using a natural Earth projection rendered with `d3.geoNaturalEarth1` and `d3.geoPath`. Each circle represents a recorded incident, with its radius scaled proportionally to the total number of dead or missing via a square-root scale. The map overlays land polygons and country borders from the world-atlas TopoJSON dataset onto graticule lines. React manages the component hierarchy, while D3 loads the CSV data and handles geographic projections, all rendered as SVG elements with semi-transparent teal circles.

JJun Suzuki

Missing Migrants Map

This map visualizes missing migrant incidents worldwide using a natural Earth projection. Circles sized proportionally to the total dead and missing per incident are placed at their recorded coordinates. The visualization uses React with d3.geoPath and d3.geoNaturalEarth1 for the map, d3.scaleSqrt for circle sizing, and renders as SVG. World atlas data comes from TopoJSON, while incident data is loaded via d3.csv from a public CSV.

Sstevensmithj

Missing Migrants on a Map

This visualization displays a world map of missing migrant incidents, with circle markers sized according to the total number of dead and missing individuals at each location. The map uses a natural Earth projection with graticules and country borders rendered as SVG paths, while circles are overlaid with square-root scaling for radius. Built with React and D3 v5, the example loads world atlas topology via the `topojson` library and pulls data from a CSV file. The `geoNaturalEarth1` projection and `geoPath` handle geographic mapping, while circles are positioned using the projection coordinates.

LLaura Johnson

Missing Migrants on a Map

This map visualizes missing migrant incidents worldwide, with each circle positioned at the incident’s coordinates and sized by the total number of dead and missing. It uses a natural Earth projection via `d3.geoNaturalEarth1` and `d3.geoPath`, rendering landmasses, graticules, and interiors from the World Atlas TopoJSON. Circles scale with `scaleSqrt` based on the CSV data, while React manages state and rendering.

CCodeDuckie99

Missing Migrants on a Map

This visualization shows the locations of missing migrants on a world map, using a natural Earth projection to render landmasses and graticules. Each migrant incident is drawn as a semi-transparent circle, with its radius scaled proportionally to the total number of dead and missing via a square-root scale. The map is built with d3.geoPath for geographic features and d3.geoGraticule for the coordinate grid, while data is loaded from a CSV file using d3.csv. The entire SVG is assembled in React, with world atlas topology processed through the topojson library’s feature and mesh functions.

JJohn Huang

Missing Migrants on a World Map

This visualization plots reported missing migrant incidents on a world map using a natural Earth projection. Each dark circle represents a location with a radius scaled by the square root of the total dead and missing count. The map renders SVG land masses, graticules, and country borders from TopoJSON world-atlas data, while the underlying CSV provides incident coordinates. The React app uses D3 utilities like `geoNaturalEarth1`, `geoPath`, and `scaleSqrt` to combine geographic and proportional symbol encoding.

Hhunsingeruk@gmail.com

Missing Migrants on a Map

This visualization maps missing migrant incidents worldwide, with circles sized by the total number of dead and missing individuals at each location. The map uses a natural Earth projection with graticules, country boundaries, and a light color scheme. The React app loads CSV data and world-atlas TopoJSON, then renders SVG marks via `d3.geoPath` and a square-root scale for circle radii. The underlying data is drawn from the Missing Migrant Project dataset.

Tthomasjungcoe

Missing Migrants of a map

This visualization maps missing migrant incidents worldwide, with circles sized by the total number of dead and missing per event. The geographic context comes from a world atlas with land, interiors, and graticules rendered using D3’s geoNaturalEarth1 projection and geoPath. A square root scale maps the data’s magnitude to circle radius, and the dataset is loaded via d3.csv from a GitHub gist. The visualization uses React to manage state and render the SVG marks.

Ssophievanderhorst