CARTOGRAPHY COMPARISON: GOOGLE & APPLE

Introduction · 📍PART 1 · Part 2

PART 1: PARTS OF THE MAP
Cities, Roads, & Places

In What Happened to Google Maps?, we saw that the number of cities labeled on Google Maps has decreased over time:

But how does Apple Maps compare? Does it show more cities than Google? Or fewer?

Let’s investigate…

First, let’s take all of our map pairs and count the number of city labels on them:

On nearly every zoom with city labels, Apple labels more cities than Google.

To get a better sense of the differences, let’s plot our counts above into a set of graphs:

The Apple lines (black) are higher than the Google lines (red) at nearly every zoom.

But the graph is a bit of a mess. Let’s clean it up by averaging all of the red and black lines together:

Much clearer. And look what it shows: Apple, on average, labels more cities than Google at every zoom.

The graph tells us that the biggest difference between Google and Apple is at z8. Let’s take a look at that zoom across our three cities:

First, New York:

What a difference! Apple shows way more cities than Google. It’s not even close. (Here, Apple labels 44 cities, while Google labels just 10.)

I wonder why Google doesn’t label more cities here?

Let’s look at San Francisco next:

Another large difference! Apple labels 32 cities, while Google labels just 10. And it’s also surprising to see Oakland and Napa missing from Google’s map.

Let’s check London, too:

The pattern continues: Apple labels 48 cities, while Google labels just 13.

Though these are the most extreme examples, our graph showed that Apple, on average, labels more cities than Google at every zoom. So to answer our first question, Apple Maps generally labels more cities than Google Maps on the maps we looked at.

*   *   *
 

We also saw in What Happened to Google Maps? that the number of roads shown on Google Maps has actually increased over time:

How does that compare to Apple Maps? And which map—Google Maps or Apple Maps—shows more roads overall?

Let’s investigate that next…

Did you know that the first twelve zooms on each map only show a fraction of an area’s actual roads?

For instance, these are the roads that Google shows on its eighth zoom-level:

And these are the area’s actual roads, compared to the roads that Google shows:

In the image on the left, you can clearly see where all of the Bay Area’s cities are: there are so many roads in some areas (such as San Francisco), all we see are dark blobs. It looks cool, doesn’t it?

Now look at the image on the right. Google Maps is showing only a tiny fraction of the roads shown on the left.

But that’s by design.

If Google showed all of the area’s roads at this zoom, the map would be a cluttered mess, and it’d be difficult to trace any individual road. So Google instead simplifies the map and shows just a selection of the area’s most important roads. 

Apple actually does the same—notice that it also doesn’t show all of the Bay Area’s roads at this zoom:

So neither Google Maps nor Apple Maps shows all of the area’s roads at this zoom:

But did you also notice that Apple’s selection of roads is actually larger than Google’s?

Look here on the maps, near Vacaville and Davis—Apple is actually showing a greater number of roads than Google:

Interesting, isn’t it?

Which map—Google Maps or Apple Maps—shows more roads at more zooms?

Let’s tally it up:

For almost two-thirds of the zooms, Google and Apple show roughly the same number of roads. But for the remaining zooms, where one map shows more roads than the other, it’s almost always Apple that’s showing more roads.

So now that we’ve looked at roads, let’s look at road labels… which map shows more?

*   *   *

There are actually two kinds of road labels on Google Maps and Apple Maps: shields and text labels:

Which map shows more of each?
 

*   *   *
 

First, let’s look at shields.

We’ll start by counting the number of shields on each zoom:

Interesting. Now, Google’s totals are higher for every city.

Let’s plot the counts:

Our graphs show that Google almost always has more shields than Apple — especially at earlier zooms.

In the first graph, the New York one, there’s a huge difference at z8. Isn’t that the same zoom we looked at a little earlier? The one where Apple labeled far more cities than Google?

Let’s take another look:

Yep—it was that zoom alright. But look at it now: Google shows a bunch of shields (20), while Apple shows just 1!

Let’s see if the same thing is happening in San Francisco:

It looks as if it is. Here, Google has 7 shields, while Apple has 0!

Let’s check London too:

Here, Google has 9 shields, while Apple has just 1.
 

*   *   *
 

So maybe that’s the answer to our earlier question? (“Why doesn’t Google label more cities here?”) Google is prioritizing shields over cities—while Apple is prioritizing cities over shields.

I’m having déjà vu. Are you?
 

*   *   *
 

Let’s take all of our shield graphs and average them out:

Google, on average, shows many more shields at earlier zooms, while Apple shows more shields than Google after z12 (but not nearly as many as Google shows early on).

This is quite different than what we saw with the city labels…
 

*   *   *
 

Now that we’ve looked at shields, what about text labels for roads? Remember, those are the other kind of road labels on Google Maps and Apple Maps:

Which map shows more?

First, we’ll count the totals:

A pattern’s emerging: similar to the shields, Google’s totals are once again higher than Apple’s for every city.

Let’s plot our counts:

It looks as if things are a bit closer here than they were for the shields — that is, except in London, where there’s a very wide difference early on, at z12.

Let’s average the cities together:

Google Maps, on average, shows more text labels for roads at every zoom.

Looking at the graph above, there’s still a big difference at z12—the same zoom we saw that huge difference in London on the smaller graphs.

Let’s see what’s going on there in London:

Interesting. There are no shields on Google’s map—instead, the route numbers are labeled as text. It actually seems to make the map look nicer. (Perhaps this has something to do with local cartographic expectations? We’ll look at that in one of our later chapters.)

Labeling the roads with text instead of shields, Google ends up with 37 text labels at this zoom. Meanwhile, Apple has just a single text label entirely within view.

That’s quite a difference, but our graph showed that the largest difference, on average, was actually at z13.

Let’s check out that zoom—but since we just looked at London, let’s look at a different city. We’ll look at San Francisco instead:

Comparing the two maps, it certainly looks as if Google shows more text labels for roads. Let’s count them up:

Google has 28 text labels for roads, while Apple has just 7 (25% of Google’s count).

And Google labels more of San Francisco’s main streets: Market, Divisadero, Mission, Valencia, Guerrero, Dolores, Folsom, Franklin, Gough, Columbus, and Castro are all labeled on Google’s map—but missing on Apple’s.

These are very different maps!
 

*   *   *
 

So far, we’ve counted shields and text labels separately. And Google tended to show more of each.

Let’s quickly add up the totals for both shields and text labels to see the overall number of road labels on each map:

As expected, Google Maps has a higher combined total for all three cities.

Let’s plot our counts...

...and average them out:

Google Maps, on average, labels more roads than Apple Maps—in some cases, many more—on all but two zooms.

This is especially interesting, given that Apple shows more roads than Google.

Looking at the graph above, the biggest average difference in road labels between the two maps is at z9. Let’s take a quick look at that zoom across our three cities:

New York
Google: 20 Road Labels
Apple: 1 Road Label

*   *   *

San Francisco
Google: 16 Road Labels
Apple: 0 Road Labels

*   *   *

London
Google: 22 Road Labels
Apple: 6 Road Labels

*   *   *
 

We’re seeing some really interesting results so far:

Apple is labeling more cities. And Apple is also showing more roads. But Google has more road labels.

Our z8 maps from earlier capture the pattern better than any map we’ve seen so far:

The Google map has more road labels—19 more than Apple. And the Apple map has more city labels—34 more than Google.

Two very different views of the same area!
 

*   *   *
 

I keep thinking of our subway maps from What Happened to Google Maps?:

Similar to subway maps, our maps below are simple network maps. The roads are the lines, and the cities are the stations. And there’s basically nothing else labeled on these maps, other than roads and cities (lines and stations):

But it’s strange:

Google is good at labeling the lines—but not the stations.

And Apple’s good at labeling the stations—but not the lines.

We're only getting half of the picture on each map. And both maps seem imbalanced, don’t they?
 

If only we could take the best of both maps above—Google’s road labels and Apple’s city labels—and somehow combine them together…
 

*   *   *
 

Let’s try a little experiment with our two z8 maps:

We’ll take the Google Map, but we’ll remove its city labels—and we’ll take the Apple Map, and we’ll remove its shield:

(The maps actually don’t look too different with those labels removed.)

Now let’s combine the two maps together:

And let’s make it even larger:

There are a few overlapping labels—but overall, the information density on our combined map is interesting.

Let’s reposition the overlapping labels and enhance the map’s contrast to make it a little easier to read:

That doesn’t look half bad.

And now let’s compare our Frankenstein map to its parents:

The information density on the combined map is interesting. Perhaps a bit too busy, but certainly interesting.

And at least we're now seeing the whole picture.
 

*   *   *
 

So far, we’ve only been looking at Cities and Roads. Let’s move on to a different part of the map: Places.

Most paper maps never had enough space to label every “place”. Instead, they labeled a selection of an area’s most interesting and important places, calling them “Points of Interest” (or “POIs” for short).

But today, with multiple zoom-levels, there’s plenty of room for things that would’ve never fit before. Small businesses, apartment buildings, ATMs, and even homes — suddenly, no place is too small or too trivial to be included.

It’s hard to overstate just how big of a change this has been. Google only started adding labels and icons for businesses to its maps six years ago. But like a contagion, those little place icons have spread and multiplied to every corner of the map — and in doing so, they’ve quickly become a core, expected feature.

The “POI” is dead because today every place is of interest.
 

*   *   *
 

Given how important places have become, let’s find out which map—Google Maps or Apple Maps—labels more...

First, let’s count the number of places on each zoom:

According to our counts, Apple labels more places in New York and San Francisco, while Google labels more places in London.

Let’s plot our counts to get a better sense of the differences:

The counts look somewhat similar in New York and San Francisco—but check out that spike in London at z13. What’s going on there?

Let’s take a look:

Ah, there’s our culprit: it’s all the Tube stations that Google is labeling at this zoom.

Comparing the two maps, the Tube stations really add up. They give Google a total of 38 places—versus just 14 for Apple:

(34 of the 38 places on Google’s map are Tube and rail stations—no wonder why Google’s count is so high there.)

Let’s take our graphs and average them together to see if there’s a general pattern:

There really isn’t much of a difference here: on average, it’s less than five across all zooms.

So for now, we’ll conclude that Google Maps and Apple Maps label a similar number of places.

*   *   *

Now that we’ve seen that Google and Apple label a similar number of places, are they labeling the same places? Or different places?

Let’s investigate that next…

It’s a super interesting question: how often are the pairs of maps labeling the same places (e.g., the exact same businesses, the exact same landmarks, the exact same parks, etc.)?

For example, take these New York maps at z14:

There are just 5 places that are labeled on both maps: Times Square, Bryant Park, Grand Central Terminal, the Empire State Building, and the Flatiron Building.

But Google is actually labeling 24 places in total, while Apple is labeling 16:

That means that out of a combined total of 35 unique places on both maps, the two maps have only 5 places in common.

That’s really surprising.

But is it the same for all zooms?

Let’s take all of our map pairs and count the number of place labels that both maps have in common:

Now, let’s take those totals and divide them by the total number of unique places on both maps, and see what kind of percentages we get:

Those percentages are really low. 

Let’s average them across each city:

Wow. In New York, both maps have only 10% percent of their place labels in common! And in London, it’s just 12%!

So, “How often were the same places shown on both maps?”

Not often at all.

And once again, we see two very different maps.
 

*   *   *
 

So the maps don’t seem to label the exact same places. But do they generally show the same kinds of places?

Let’s look at that next…

In a dense city like New York, there are so many different kinds of places: hospitals, parks, homes, schools, grocery stores, fire stations, skyscrapers, government buildings, cathedrals, universities—the list goes on and on, and it’s seemingly endless.

Take the maps below: there are thousands of different places that could’ve been labeled on either of these maps:

But similar to what we saw with all of the Bay Area’s roads, it would be impossible to show everything that’s actually there and still have a legible map:

Instead, the maps show just a tiny selection of everything that’s actually there.

Remember Faisal’s picture of the Empire State Building at the beginning of this essay? That’s a picture of the same area shown in the maps above. There are a lot of places there!

*   *   *

So out of thousands of possible places in Midtown Manhattan, Google and Apple choose to label these specific ones:

But how do Google and Apple choose these places? (They had thousands to choose from—how did they end up with these?)

And are there specific kinds of places favored by each map?

Let’s dig into this more…
 

*   *   *
 

First, we’ll divide all of the places on Google Maps and Apple Maps into eight simple categories:

• Things to Do & See: Landmarks & attractions, entertainment (theaters, stadiums, and nightclubs), and recreation (parks and other spaces).

• Eat & Drink: Restaurants, bars, coffee shops, etc.—anywhere you can be served prepared food and beverages.

• Shopping & Services: Banks, hotels, shops, stores, markets, etc.

• Airports

• Transit Stations: Train and subway stations, bus and streetcar stops.

• Universities

• Hospitals

• Other: Anything that doesn’t fit into the other seven categories: corporate headquarters, apartment buildings, homes, etc.

Now that we have our eight categories, let’s count how many categories appear on each map.

We’ll do it like this for each pair:

So above, Google shows four categories, while Apple shows five.

Now, let’s count the number of categories on the rest of the zooms:

And next, let’s plot and average those counts:

Interesting. At nearly every zoom, Apple Maps is showing a greater number of categories.

Though given what we saw in New York (Apple showed five categories, while Google showed four), perhaps it isn’t too surprising?

Let’s take a closer look at each zoom, and see if we can find some other patterns…
 

*   *   *
 

While we were counting the number of categories on each zoom, I also recorded the number of places for each category shown:

This is cool because it’ll allow us to see which categories appear most at each zoom.

Like here in New York:

Interesting, isn’t it? The two maps are really different.

Early on, Apple shows airports, while Google shows transit stations. And then as you continue zooming in, both start showing a greater variety of places—though Apple shows a greater variety overall (just as we saw in our graphs).

And this certainly matches the map we just looked at—there are lots of transit stations on Google’s map and a greater variety of place categories on Apple’s:

Let’s see if we see the same pattern in San Francisco:

Here in San Francisco, we’re generally seeing fewer places per zoom than we did in New York, but the results are largely the same: Google is prioritizing transit after the first few zooms, while Apple is prioritizing landmarks.

Looking at the bar graphs above, z13 looks like one of the most different zooms between the two—let’s take a closer look:

Ah, this is that zoom where Apple showed very few text labels for roads. Remember that?

But perhaps now we see why: Apple is actually showing a greater number of places here than Google (15 for Apple, versus 6 for Google).

With so many more places labeled on the map, there’s probably less room for road labels—hence, the lower road label count we saw earlier.

But let’s test this theory.

First, we’ll merge the two z13 maps together:

Now, let’s look and see if any of Google’s road labels collide with Apple’s places.

Look at that! Apple’s place labels collide with seven of Google’s road labels. In other words, those place labels are occupying space on the map where roads could’ve been labeled. That’s why we saw the lower road label count on Apple earlier.

It’s interesting, isn’t it? Google is prioritizing roads, while Apple is prioritizing places. And that’s why were seeing such noticeable differences in the counts.

But even when it comes to places, the maps are prioritizing different things:

Above, Google is again prioritizing transit places, while Apple is prioritizing landmark places. And Apple is also showing a couple of hospitals and a famous bakery.

What’s more important on a map like this? Transit? Or landmarks and hospitals?

Each map voted with its pixels, and it’s interesting to see.

(And here we’re also seeing the argument for map personalization: Not everyone uses transit, so there might be places—such as landmarks—that are more important to some people. And when it’s life-and-death, hospitals are the most important places in the world. But how often does the average person visit a hospital? Personalized maps are better at surfacing the most appropriate places for each person; but for the default map, something still has to be chosen… and that’s what we saw above.)
 

*   *   *
 

Do the patterns we’ve seen for New York and San Francisco also hold for London?

Let’s see:

Whoa — look at all of those transit stations shown in London at z13! 

Let’s take a closer look at that zoom and see what’s going on:

Ah, it’s all of those Tube and rail stations we saw earlier.

The icons don’t have text attached to them, so Google is able to pack lots of them onto the map. (34 in total.)

It’s a clever way of increasing the map’s information density: the icons give just enough information that you know that they’re Tube stations—and without text, Google can fit even more of them on the map.

That’s why Google’s count is so high at this zoom.
 

*   *   *
 

Now that we’ve looked at each city individually, let’s average them together to see the overall pattern:

Google Maps prioritizes transit stations for several zooms, while Apple generally labels more landmarks. And as you zoom in, both maps show a increasing variety of categories.

Both maps also show a surprising number of restaurants (the yellow parts of the bar graphs). But notice that the restaurants don’t start appearing until later zooms.

And that’s another interesting point, isn’t it?

The places that each map feels are more important are shown earlier, while the places that each map feels are less important are shown later.

It’s clear that Google thinks transit is important, while Apple thinks that airports, hospitals, and landmarks are important.

Two very different views of the world!
 

*   *   *
 

Now that we have data on the kinds of places shown at each zoom, let’s look at how balanced an average zoom is on both maps:

We’ll use pie charts:

A zoom is generally “balanced” if no single category comprises more than 50% of its places.

And as you can see from the pie charts above, Google isn’t particularly balanced for the first nine zooms it labels places on. And in comparison to Google, Apple generally has a better balance of place labels per zoom, overall.

We’ve looked at the place categories that are shown on each zoom — but what about all zooms, taken together?

Which category does each map show the most, across all zooms? In other words, which category is each map’s favorite?

Let’s investigate this one last thing…

*   *   *

We’ll start by adding up all of the place labels in each city, across all zooms:

Ok. Now, let’s average all of the place labels across our three cities:

More than anything else, Google Maps is labeling transit stations, while Apple is labeling landmarks. And Apple, on average, also shows twice as many restaurants and stores than Google. Interesting, isn’t it? The maps are very different!

Everything said, the number of transit stations labeled is clearly the largest difference between the two—and Google labels far more than Apple. And that’s actually quite intriguing, given that Google also offers a dedicated transit map.

But that’s an interesting question, isn’t it? If there’s already a dedicated transit map, why not use the main map as an opportunity to show different, non-transit places?

Then again, transit stations are important visual cues for way-finding — even if you’re not actually “taking” transit. And when transit stations are labeled with text, they actually double as area labels (e.g., Leicester Square, Charing Cross, Piccadilly Circus), adding even more detail to the map:

So there’s definitely value in labeling transit stations on the main map.

But is that value still there if all of the stations aren’t shown?

For example, take another look at our San Francisco maps from earlier — the ones where Google prioritized transit and Apple prioritized landmarks and hospitals:

If you’re familiar with San Francisco, you might notice that even though Google is prioritizing transit, half of the BART stations are actually missing: 

And the same is true with the New York maps we looked at.

Remember these from earlier?

A handful of stations are missing here too:

The missing stations provoke an interesting design question: if you can’t label all of a system’s stations, should any be labeled? In other words, is it deceptive to only label some stations? (Some people using the map—tourists, especially—may not realize that some of the system’s stations aren’t labeled.)

We saw earlier in San Francisco that Google seemed to be prioritizing road labels over place labels:

Perhaps this is what’s actually causing the missing BART stations? Notice below that road labels cover two of the missing BART stations, while the third missing station is clipped by the label for Downtown San Francisco (i.e., the “Financial District” label):

There are so many things to label at this zoom (roads, places, districts, etc.), in such limited space—and only a handful of things can fit. Perhaps this is why Apple doesn’t even seem to try to label transit stations? (Perhaps it knows that, with everything else that has to be labeled, it can’t fit all of the stations?)

Similar to Google, Apple also offers a dedicated transit map. And you get the sense that because Apple offers one, it instead uses its default map as an opportunity show different, non-transit places.

Is that what’s really going on? We don’t know—but it’s certainly interesting to observe such different approaches!

And it goes to show just how difficult cartography really is: seemingly small decisions, such as prioritizing road labels over place labels, can impact the larger map in unexpected ways (such as preventing all of a city’s transit stations from appearing together at the same zoom).

*   *   * 

Now that we’ve looked at three important parts of the map (Cities, Roads, and Places), we’ll turn our attention to what’s on each map, as a whole...

Introduction · 📍 · Part 2