How a bivariate map works (explained simply)

One map, two answers at once

Most maps colour each spot by a single thing — population, say, or how built-up it is. A bivariate map is cleverer: it shades every tile by two things at the same time, so you can see how they line up across a whole city in one glance.

In Geo-Intel you turn this on with the Bivariate tab at the top of the map. You pick two metrics — one for the left-to-right direction (the X axis) and one for the up-and-down direction (the Y axis) — and every tile gets a colour that says where it sits on both at once.

Our example: buildings vs. people in New York

The screenshots use New York City with two everyday questions stacked together:

• XResidential building volume (the left-to-right axis) — how much housing is actually built on that patch of land, measured in cubic metres (m³).
• YTotal population (the up-and-down axis) — how many people are counted as living there.

Put together, the map answers a much richer question than either could alone: where are there lots of homes and lots of people, where are there big buildings but few residents, and where do people live without much built housing around them?

“But one is m³ and the other is a head-count!”

You may have noticed the two metrics use completely different units — cubic metres of building versus a plain count of people. Geo-Intel even pops up a gentle note about it. That is fine, and here is why.

A bivariate map never compares the two numbers against each other. It compares each tile against all the other tiles on the same axis. The X axis is ranked only against other X values, and the Y axis only against other Y values. So “a lot of building” and “a lot of people” are each judged on their own scale — the units never touch.

The pattern you see is always valid even with mismatched units. The only thing to do is read the raw numbers in a tile's pop-up with a little care — don't mentally subtract “200 people” from “243,000 m³,” because they measure different things.

Reading the colour: the 3×3 key

The little colour square in the bottom corner of the map is your decoder. It is a 3×3 grid — three steps for X (Low, Medium, High) crossed with three steps for Y (Low, Medium, High), giving nine possible colours.

Read it like a chart you learned in school: move right for more on the X metric (more residential building), and move up for more on the Y metric (more people). The corner where both are highest gets the deepest, darkest colour — that is the simple rule: darker means both are high at once.

So a pale tile is “low on both.” A strongly teal tile is “lots of building, but not many people.” A strongly magenta tile is “lots of people, but not much built housing.” And the dark corner is “packed with both.” Once you internalise the corners, you can read the whole city without thinking.

Hover any tile to see the exact numbers

Colours give you the big picture; the pop-up gives you the receipts. Hover (or tap) a tile and Geo-Intel tells you which of the nine combinations it belongs to, plus the real value behind each axis.

Notice the read-out names the band (“Low,” “High”) and the raw value beside it. The highlighted square in the key shows exactly which of the nine cells you are on. You can also hover a cell in the key to light up every matching tile on the map — a fast way to ask “show me everywhere that's high-building, low-people.”

Picking a colour scheme

The relationship is the same no matter which palette you choose — the colours are purely about readability and taste. Geo-Intel ships four hand-tuned schemes (Teal · Magenta, Blue · Pink, Green · Purple, Orange · Blue). Each one keeps the same logic: one colour family leans toward the X metric, another toward the Y, and they blend toward a dark corner where both are high.

Pick whichever you can read most comfortably — on a dark map, on a bright day, or for colour-vision needs. Switching palettes is instant and changes nothing about the data underneath.

Where do the Low / Medium / High lines go?

Here is the one genuinely important choice on the panel: Classification. To turn thousands of different values into just three bands, Geo-Intel has to draw two cut lines — one between Low and Medium, one between Medium and High. Where it draws those lines changes which tiles look high or low.

That is not a trick or a bias — it is a real decision every map-maker faces, and there is no single “correct” answer. So Geo-Intel gives you three well-known methods and lets you switch between them live. None of them re-fetches data; they just re-draw the cut lines.

A closer look at “Natural” (Jenks natural breaks)

“Natural” is worth a sentence more because it is the most thoughtful of the three. It uses an algorithm called Jenks natural breaks, named after the cartographer George Jenks. The idea is intuitive: real-world data usually clumps, and you want the bands to fall in the empty gaps between clumps rather than slicing straight through a tight cluster.

Imagine plotting every tile's value on a number line. You would see little crowds of dots with gaps between them. Jenks mathematically finds the cut points that keep each crowd as tightly together as possible while making the crowds as different from each other as possible. The result is bands that match how the data actually groups in the real world — which is why it so often “looks right.”

Quantile guarantees an even spread of colour, Equal interval respects raw magnitude, and Natural respects the data's own shape. Flip between them and watch the map — if the big picture barely changes, your pattern is robust. If it changes a lot, it means a few tiles sit right on a boundary, which is itself useful to know.

Which one should you pick?

A simple rule of thumb, no statistics required:

• Just exploring and want to see the strongest and weakest areas? Start with Quantile — it always fills the map with contrast.
• Care about the true size of the gap between places (e.g. one area has twice the housing of another)? Use Equal interval.
• Want the map to honour the natural clusters in the city? Use Natural (Jenks).

The honest best practice is to try all three. They are one click apart, and the way the map shifts (or doesn't) tells you how solid your story is.

The whole idea, in four lines

• A bivariate map colours every tile by two metrics at once — X goes left-to-right, Y goes bottom-to-top.
• Mismatched units are fine: each axis is ranked on its own, so m³ and head-counts never get compared directly.
• Darker corner = both high. Hover a tile or a key cell to see exact numbers and isolate a combination.
• Classification (Quantile, Equal, Natural/Jenks) decides where the Low/Medium/High lines fall — switch live to test how solid the pattern is.