Three cities. Fifty years. One interactive map. The new Population Density layers on geteach.com let students click anywhere on Earth and see exactly how many people live in a 20km cell — and how that number has changed since 1975.

The Population Density layers (1975, 2000, and 2025) are now live on geteach.com, powered by the Global Human Settlement Layer (GHSL) from the European Commission’s Joint Research Centre. Students can place two maps side by side — say, 1975 and 2025 — click any location, and instantly see the population count, density per km², and a growth chart spanning five decades. Below are three locations that tell three very different stories.

Detroit, Michigan — The Shrinking City

Where to click: Center of Detroit, approximately 42.30°N, 83.23°W

 

Detroit is one of the most dramatic cases of urban population loss in the developed world. The city’s population fell from a high of 1,850,000 in 1950 to around 680,000 by 2015, and the decline has continued since. Detroit is currently about 65% smaller than it was at its peak, and has shrunk roughly 33% since the year 2000.

When students click Detroit’s inner city cells and compare the 1975 and 2025 layers side by side, the growth chart shows a persistent negative slope — most cells in the urban core register a total decline of roughly 8–15% from 1975 to 2025, with the southern portions running closer to 15–20%. These numbers are modest at first glance, but there is an important reason for that: Detroit’s sharpest and most catastrophic losses came before 1975. The GHSL dataset begins at 1975, which means the map captures only the tail end of one of America’s most dramatic urban contractions. By 1975, Detroit had already shed hundreds of thousands of residents from its 1950 peak. The 8–20% the map shows is the continuation of a decline that was already well underway.

This is a valuable teaching moment in itself — data always has a starting point, and what happened before that starting point matters. The map is honest about what it shows, but context is essential. A negative growth rate of even 10% sustained over 50 years represents real neighborhoods abandoned, real tax bases eroded, and real infrastructure left without users.

The causes are deeply geographic. The rise and fall of the automotive industry, white flight to the suburbs, highway construction that gutted urban neighborhoods, and the deindustrialization of the Rust Belt all left their mark. What makes Detroit particularly instructive on this map is the contrast between the city and its suburbs. Ask students to click not just the urban core, but the cells to the north and west. They will find those cells grew over the same period — population didn’t disappear from the region, it moved outward. That spatial redistribution is the real story the map tells.

Discussion questions

  • The map shows 8–20% decline from 1975–2025, but Detroit’s total loss since 1950 is over 60%. What does that tell you about using 1975 as a baseline?
  • Why might the suburban cells around Detroit show growth while the city core shows decline?
  • What geographic factors — highways, industry, housing policy — shaped where people moved?
  • What does a persistent negative growth rate tell you about a place’s long-term economic trajectory?

Explore Detroit on geteach.com: Open Detroit Population Density →

New Delhi, India — Explosive Growth

Where to click: Central New Delhi, approximately 28.66°N, 77.34°E

 

New Delhi sits at the opposite end of the population spectrum from Detroit. New Delhi has expanded by approximately 400% since 1975, reaching a forecasted population of over 31 million. The metro area population of Delhi in 2025 was estimated at 34,666,000, continuing to grow at over 2.5% per year.

When students click central Delhi cells on the 1975 vs 2025 dual map, the growth chart rockets upward — the total growth percentage (1975 – 2025) for dense urban cells in this area can exceed 300% to 500%. The density figures for the most built-up cells are staggering, among the highest on the planet.

But the more geographically interesting story is what happens when students click outward from the center. The inner city cells, already dense in 1975, show strong but bounded growth. The real explosion shows up in the cells to the west, south, and east of the historic core — areas that were largely agricultural or sparsely settled in 1975 and are now dense urban fabric. This is urbanization made visible and measurable.

Delhi has a rapidly growing population that nearly doubled from an estimated 18.6 million in 2016 to an estimated 34.6 million by 2025. That rate of change — doubling in under a decade — is almost impossible to comprehend from statistics alone. The map makes it spatial and real.

Discussion questions

  • Which cells show the highest growth rates — the inner city or the outer edges? What does that pattern tell you?
  • What push and pull factors drive migration into a megacity like Delhi?
  • How does rapid urbanization create challenges for infrastructure, housing, and the environment?

Explore New Delhi on geteach.com: Open New Delhi Population Density →

Seoul, South Korea — A City of Two Stories

Where to click (inner city): Central Seoul, approximately 37.56°N, 126.85°E
Where to click (suburbs): Gyeonggi Province, approximately 37.21°N, 127.04°E (Seongnam/Bundang area)

 

Seoul offers the most nuanced of the three case studies because it is actually two population stories happening simultaneously in the same metropolitan area.

Inner Seoul — stable to declining. Seoul’s population peaked at over 10 million and has gradually decreased since 2014, standing at about 9.6 million residents as of 2024. Students clicking the dense inner-city cells will find growth rates that are relatively modest compared to Delhi, and in some cells even slightly negative in recent decades. The density numbers are extremely high — Seoul’s urban core is one of the most densely populated places in the world — but the trajectory has flattened. Reasons for the population drop include high costs of living, especially housing, urban sprawl to Gyeonggi region’s satellite cities, and an aging population with an extremely low birth rate.

The suburbs — rapid growth. The story changes dramatically when students move their clicks outward into Gyeonggi Province. Satellite cities like Seongnam, Suwon, Goyang, and Yongin show steep upward growth curves on the chart. The Seoul metropolitan area has continued strong population growth, with the 2020 census indicating steady annual increases driven by suburban expansion. The Seoul Metropolitan Area as a whole has a population of 26 million as of 2024, ranked as the fourth-largest metropolitan area in the world.

This inner-decline / outer-growth pattern is called suburbanization or counterurbanization, and Seoul is one of the world’s clearest examples of it. The dual map is perfectly suited to showing this — students can place inner Seoul on map 1 and a suburban Gyeonggi cell on map 2, compare the growth charts side by side, and immediately see the spatial redistribution of population that defines modern Seoul.

Discussion questions

  • Why would people leave one of the world’s most connected cities for the suburbs?
  • How does a very low birth rate affect a city’s long-term population even if migration is stable?
  • Compare Seoul’s suburbanization pattern to Detroit’s. What is similar? What is fundamentally different?

Explore Seoul on geteach.com: Open Seoul Population Density →

Classroom Activity: The Population Comparison Challenge

This activity works for AP Human Geography (Unit 2 — Population and Migration, Unit 6 — Cities and Urban Land Use) and Geography for Life Standards 9 and 12.

 

Setup: Open geteach.com and load Population Density-1975 on Map 1 and Population Density-2025 on Map 2. Sync the maps so both canvases show the same location simultaneously.

Step 1 — Pick your city. Assign each student or pair one of the three cities above, or let them choose any city in the world.

Step 2 — Click and record. Click the urban core and record: total population (1975 and 2025), density per km², and the gTotal growth percentage shown in the chart.

Step 3 — Move outward. Click two or three cells progressively further from the city center. Record the same data. How does the pattern change?

Step 4 — Compare and explain. Using the data collected, ask students to write a geographic explanation: What pattern do they see moving from center to edge? What human or physical geographic factors explain it?

Step 5 — Cross-city comparison. Share results across the class. Build a comparison table: Which city grew fastest? Which shrank? Which shows suburbanization? What does that tell us about different development paths?

Try the activity yourself: Open geteach.com →

About the Data

The population counts displayed come from the Global Human Settlement Layer (GHSL) P2023A dataset, produced by the European Commission’s Joint Research Centre. The raw data represents population counts at 100m × 100m pixel resolution. On geteach.com, these values are aggregated into 20km grid cells, giving students a total population estimate and a density figure (residents per km²) for the area around their click. Growth rates are calculated relative to 1975 as the baseline year.

The three epochs available — 1975, 2000, and 2025 — align directly with AP Human Geography Unit 2 (Population and Migration), which examines how and why population distribution changes over time, and Unit 6 (Cities and Urban Land Use), which asks students to explain the internal structure of cities, patterns of urban growth, and the forces driving suburbanization and urban decline. The layers also support Geography for Life Standard 9 (Human Populations) and Standard 12 (Human Settlement).

geteach.com Curated by Josh Williams @ geteach.com