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Nepal Census Atlas 2011 · Between War and Quake

Jonathan Witcoski · GIS Architect · witcoskitech.com

A scrollytelling district story map of Nepal’s 2011 National Population & Housing Census — the country between civil war and earthquake, told through literacy, electricity, migration, and density.

The census year is frozen history. The craft is not: turn imperfect administrative tables into trustworthy geography, then pace the map so a reader understands a place.

This repository started in 2015 as a placeholder. In 2026 it is a portfolio piece for spatial ETL + narrative cartography.

Live map

Serve the repo root with any static server (GitHub Pages works from root):

python3 -m http.server 8080
# → http://localhost:8080

Hard-refresh after pulls — the app loads ES modules under js/ and CSS partials under css/.

Story arc

Chapter Map focus
Prologue Ecological belts · China / India / Everest / Kathmandu
1 · War hills Mid-Western hills · electric lighting
2 · Three Nepals Literacy · Mountains / Hills / Tarai
3 · Tarai School attendance in dense plains districts
4 · Absent men Sex ratio · remittance geography
5 · The Valley Density + USGS ShakeMap MMI · pre-quake context
Explore Free metric picker + district inspector

Census indicators never pretend to prove causation for war or quake — they supply honest geographic context beside Wikipedia / USGS references.

Project layout

index.html          Story markup + inlined locator inset
app.js              ES module entry
js/                 Map logic (chapters, choropleth, labels, wiki, boot…)
css/                Styles split by concern; styles.css imports them
etl/                Atlas builder + locator inset script
data/raw/           Vendored CBS extracts + district polygons
data/processed/     Joined GeoJSON, metadata, shake overlays, locator

What it demonstrates

Skill Where it shows up
Census geography ETL etl/build_district_atlas.py
Toponym reconciliation CBS ↔ GADM aliases (Chitwan/Chitawan, Kavre/Kavrepalanchok, …)
Aggregate-before-rate VDC rows summed; literacy & service rates rebuilt at district scale
Spatial metrics WGS84 geodesic area (pyproj.Geod) → people / km²
Cartographic classification Quantile breaks in data/processed/atlas_metadata.json
Narrative web GIS MapLibre scrollytelling, belt focus, landmark overlay, district inspector
Multi-source context USGS ShakeMap MMI · Natural Earth locator · Wikipedia summaries

Pipeline

pip install -r requirements.txt
python3 etl/build_district_atlas.py
python3 etl/build_locator_inset.py   # optional: rebuild China/India/Nepal inset SVG

Inputs (vendored under data/raw/):

  • districts_complete.csv — Code for Nepal VDC/municipality extracts from CBS NPHC 2011
  • districts.geojson — 75 pre-federal district polygons (anjesh/NepalMaps / GADM, CC BY 3.0)

Outputs (data/processed/):

  • districts_2011.geojson — web-simplified joined features
  • districts_2011.csv — flat indicator table
  • atlas_metadata.json — national rollups + legend breaks
  • gorkha_2015_mmi_contours.geojson / gorkha_2015_epicenter.geojson — USGS ShakeMap
  • locator_china_india_nepal.geojson / locator_inset.svg — Natural Earth inset

See data/raw/SOURCES.md for provenance notes.

Mapped indicators

Population density · literacy · female literacy · electric lighting · flush toilets · improved drinking water · school attendance (5–25) · mobile-phone households · sex ratio

Sources & credit

Author

Jonathan Witcoski — geospatial engineer building enterprise GIS, spatial ETL, and lakehouse-friendly map products (ArcGIS, PostGIS, Python, GeoParquet/PMTiles, AWS).

About

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