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Maps ❤️ Data: A voyage across the world of geo-...

Rasagy Sharma
August 01, 2017

Maps ❤️ Data: A voyage across the world of geo-visualization

A short introduction with examples of visualizing data on maps, from circles on a map, Choropleths, Hex Bins, Cartogram, Heatmap, Isopleths, Flow maps & 3D extrusions.

Conducted as part of Geo-Visualization workshops by Rasagy Sharma. Last updated in Jun, 2021 for a session for Plaksha Fellows.

This talk was first presented at Fifth Elephant (2017): https://www.youtube.com/watch?v=oF537asHhBA

Examples shared are © of respective creators (attributed in the slides).

Rasagy Sharma

August 01, 2017
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Transcript

  1. Maps♥ Data A voyage across the world of geo-visualization Rasagy

    Sharma Information Designer & Data Artist
  2. What does the term map mean? Mapping data/information vs making

    a map: Verb vs noun As a noun: conceptual, geographic, schematic, contextual, fantasy…
  3. Mapping maps Detailed (Lot of Geographical data) Abstract (Less/No Geographical

    data) Accurate & real Imaginary or conceptual Geographic maps Schematic maps Mind mapping Charts Fiction or Fantasy maps
  4. 1. Introduction 2. Maps as viz 3. Dots 4. Choropleths

    5. Bins 6. Cartogram 7. Heatmap 8. Isopleths 9. Flow maps 10.3D
  5. 1. Introduction: Geo (map) + viz (data) 2. Maps as

    viz 3. Dots 4. Choropleths 5. Bins 6. Cartogram 7. Heatmap 8. Isopleths 9. Flow maps 10.3D
  6. Babylonian Map of the World (~600 BC), Anaximander’s Map (~600

    BC vs today) , Leonardo da Vinci, “Town plan of Imola” 1502
  7. Maps as a representation of world’s data • Area covered

    by water vs land • Terrain type • Country borders • Buildings, land use • Transport network • Points of interest • & more
  8. How map data is stored: Raster vs Vector Raster: •

    Image/pixel • Data in bands • Ex: Satellite imagery (RGB & more), Elevation, Temperature etc. • Formats: GeoTIFF, JPEG2000 Vector: • Geometry: Point, line, polygon • Can have more attributes • Ex: Road network, Contour lines, Points of Interest, Building outlines & heights etc. • Formats: Shapefile, GeoJSON, TopoJSON*, KML, CSV…
  9. Data that you can show on a map: nodes, ways,

    relations Created using Geojson.io using OpenStreetMap
  10. Maps turn the real world into 2D • Projection: Equations

    to turn the earth into a 2D surface • Latitude & Longitude • Geocoding: Place à (long,lat) Illustrations from Map School, Transition by Mike Bostock
  11. 1. Introduction: Think about the basemap & the data 2.

    Maps as viz 3. Dots 4. Choropleths 5. Bins 6. Cartogram 7. Heatmap 8. Isopleths 9. Flow maps 10.3D
  12. 1. Introduction 2. Maps as viz: Visualizing data within layers

    of a map 3. Dots 4. Choropleths 5. Bins 6. Cartogram 7. Heatmap 8. Isopleths 9. Flow maps 10.3D
  13. 1. Introduction 2. Maps as viz: Subtle, layered in the

    map 3. Dots 4. Choropleths 5. Bins 6. Cartogram 7. Heatmap 8. Isopleths 9. Flow maps 10.3D
  14. 1. Introduction 2. Maps as viz 3. Dots: Showing your

    data on top of a map 4. Choropleths 5. Bins 6. Cartogram 7. Heatmap 8. Isopleths 9. Flow maps 10.3D
  15. Jobs gained vs lost: dots + size + color +

    time Geography of job loss
  16. 1. Introduction 2. Maps as viz 3. Dots: Visual encoding

    + controlling density 4. Choropleths 5. Bins 6. Cartogram 7. Heatmap 8. Isopleths 9. Flow maps 10.3D
  17. 1. Introduction 2. Maps as viz 3. Dots 4. Choropleths:

    Visualizing using geographical areas 5. Bins 6. Cartogram 7. Heatmap 8. Isopleths 9. Flow maps 10.3D
  18. Paddy crop farming in India: Area & Production India Data

    Portal by Gramener Production (tonnes) across states & districts Crop area (hectares) across states & districts
  19. 1. Introduction 2. Maps as viz 3. Dots 4. Choropleths:

    Familiar, but is data based on area? 5. Bins 6. Cartogram 7. Heatmap 8. Isopleths 9. Flow maps 10.3D
  20. 1. Introduction 2. Maps as viz 3. Dots 4. Choropleths

    5. Bins: Splitting the map into small pieces 6. Cartogram 7. Heatmap 8. Isopleths 9. Flow maps 10.3D
  21. 1. Introduction 2. Maps as viz 3. Dots 4. Choropleths

    5. Bins: Best of clustering & choropleths 6. Cartogram 7. Heatmap 8. Isopleths 9. Flow maps 10.3D
  22. 1. Introduction 2. Maps as viz 3. Dots 4. Choropleths

    5. Bins 6. Cartogram: Skewing map with data 7. Heatmap 8. Isopleths 9. Flow maps 10.3D
  23. 1. Introduction 2. Maps as viz 3. Dots 4. Choropleths

    5. Bins 6. Cartogram: Harder to create, more honest 7. Heatmap 8. Isopleths 9. Flow maps 10.3D
  24. 1. Introduction 2. Maps as viz 3. Dots 4. Choropleths

    5. Bins 6. Cartogram 7. Heatmap: Smoother distribution on a map 8. Isopleths 9. Flow maps 10.3D
  25. 1. Introduction 2. Maps as viz 3. Dots 4. Choropleths

    5. Bins 6. Cartogram 7. Heatmap: High level overview, choose colors wisely 8. Isopleths 9. Flow maps 10.3D
  26. 1. Introduction 2. Maps as viz 3. Dots 4. Choropleths

    5. Bins 6. Cartogram 7. Heatmap 8. Isopleths: Using lines to mark data as boundaries 9. Flow maps 10.3D
  27. 1. Introduction 2. Maps as viz 3. Dots 4. Choropleths

    5. Bins 6. Cartogram 7. Heatmap 8. Isopleths: Dynamic, novel view of time-based data 9. Flow maps 10.3D
  28. 1. Introduction 2. Maps as viz 3. Dots 4. Choropleths

    5. Bins 6. Cartogram 7. Heatmap 8. Isopleths 9. Flow maps: Connecting a map 10.3D
  29. 1. Introduction 2. Maps as viz 3. Dots 4. Choropleths

    5. Bins 6. Cartogram 7. Heatmap 8. Isopleths 9. Flow maps: Connections lead to stories 10.3D
  30. 1. Introduction 2. Maps as viz 3. Dots 4. Choropleths

    5. Bins 6. Cartogram 7. Heatmap 8. Isopleths 9. Flow maps 10.3D: Using another dimension
  31. Density & count: Height for density, volume for count •

    https://www.m apbox.com/bit es/00273/
  32. 1. Introduction 2. Maps as viz 3. Dots 4. Choropleths

    5. Bins 6. Cartogram 7. Heatmap 8. Isopleths 9. Flow maps 10.3D: Do you really need to use another dimension?
  33. 1. Introduction 2. Maps as viz 3. Dots 4. Choropleths

    5. Bins 6. Cartogram 7. Heatmap 8. Isopleths 9. Flow maps 10.3D: Using another dimension
  34. The spectrum of tools Interactive tools: Tableau, Flourish, Mapbox Studio…

    Programming libraries: d3 (js), Mapbox GL (js), Deck GL (js), ggmap (R), basemap+matplotlib (Python) GIS tools: ArcGIS, QGIS…
  35. Where to get Indian data • Datameet shapefiles (github.com/datameet/maps) •

    Open data portals (data.gov.in, indiadataportal.com etc.) • OpenStreetMap (openstreetmap.org, extract using overpass-turbo.eu) • Ask on Datameet group (datameet.org & google group)
  36. “Nothing is certain in this life but death, taxes and

    requests for geographic data to be represented on a map.” — Danny DeBelius (NPR)