Zero Chance of Rain on Mars Today

It’s currently a rather brisk -31 °C at Syrtis Major on Mars. Despite the chill, there’s only a light northerly wind of around 5 km/h. However, if you’re driving on Mars today, you might want to be cautious - visibility is extremely low!

This weather report is brought to you by the Mars Explorer Weather Map, NASA’s new dashboard for visualizing atmospheric conditions on Mars.

Since the release of Hint.fm’s Wind Map in 2012, we’ve grown accustomed to seeing animated flow lines depicting real-time weather on Earth. Still, that doesn’t make it any less awe-inspiring to watch wind patterns sweeping across Mars. It’s Mars, for crying out loud!

Before you get too carried away, though, keep in mind that the PSG Mars map is not a real-time weather map. It’s actually a simulation of Martian conditions based on past climate data. Even so, it’s still absolutely incredible.

America’s Carnegie Libraries on One Map

Few philanthropic endeavors have left as enduring a mark on American culture as Andrew Carnegie’s library-building mission. During his lifetime, the Scottish-American steel magnate funded the construction of 2,509 public libraries worldwide, including 1,681 in the United States. Today, you can explore these historic institutions through the Carnegie Libraries Mapping Project interactive map.

Launched by the Carnegie Corporation of New York, the map visualizes nearly 1,700 U.S. libraries, drawing from a definitive 1963 study by Florence Anderson. Clicking on a library’s marker reveals key details, such as the amount Carnegie donated and the year of the donation. Many entries also feature a "Share Your Story" button, inviting users to contribute photos and personal memories of these community landmarks.

For architecture enthusiasts, the project offers a "Tile View" alongside the standard map. This layout displays libraries in a gallery format, making it easy to browse portraits of each building (where available) alongside their donation details.

The Carnegie Libraries Of Britain, maintained by the Welsh School of Architecture, Cardiff University has created a map of the 660 Carnegie libraries built in the United Kingdom. This map uses colored markers to indicate the status of each building (purpose built library, never built, conversion of existing building etc).

Each marker on the map reveals information about the selected library and a photo of the building, if it still exists. For demolished / destroyed buildings a map is shown, instead of a photo, visualizing where the building used to stand. 

Which states have the ugliest kids?

LalGeo Maps is an interactive map which allows users to create map visualizations using natural language queries. For example if you type 

"Show US states by population'"

into LalGeo Maps then it will produce a choropleth map of the United States coloring and numbering the states by population size. 

This map comes with a legend that says 

"Data provided by the U.S. Census Bureau. Accuracy based on official government statistics."

However other visualizations created by LalGeo Maps in my testing come with the warning 

"Data generated by a large language model (LLM). It may be outdated, incomplete, or inaccurate. Use with caution."

This is true even for other visualizations that could be created from Census Data, for example 

"Show me a map of U.S. states by median household income."

Even though census data could have been used by LalGeo Maps to create this visualization the actual map created warns me that the data could be 'outdated, incomplete, or inaccurate'.

Even when the data comes with the 'Data provided by the U.S. Census Bureau', I don't trust the results. For example the result of the query

"Visualize U.S. states by percentage of population over age 65"

is a map supposedly based on U.S. Census data. This map, however, shows California with the highest proportion of its population over 65. A simple check of the Census Bureau Tables reveals this is not remotely true - California has only 15.2% of its population over 65, compared to 21.2% in Florida.

This is obviously the major flaw in using AI to create visualizations. Every use case for a mapped choropleth visualization that I can think requires a verifiable data source, allowing users to assess and evaluate the data collection methodology. Put simply I don't trust the visualizations created by LalGeo Maps - which for me makes its output virtually worthless.

The only possible remaining use of LalGeo Maps is perhaps for joke visualizations, using prompts like 'Create a map of US states by nose size', or 'Show US States by ugliest children'. Even then I would be worried that some users might mistakenly read these maps as factual.

Searching Text in Street View

The Pudding has created an amazing data journalism project that allows you to search New York for any word or combination of words. Called All Text in NYC, it’s a remarkable tool that lets you dive into the city’s written landscape - mined entirely from Google Street View images. From shop signs in Queens to murals in the Bronx, it captures the way language is woven into the physical space of NYC.

Media artist Yufeng Zhao, who built the tool, fed more than 8 million Street View panoramas into a machine learning model that identifies and transcribes visible text. The result is a searchable archive of 138 million snippets of urban lettering - graffiti, storefronts, bumper stickers, menus, flyers, billboards, and more. It turns the city into a giant text document you can explore by keyword. 

You can discover more about the project and explore some of the remarkable textual patterns found in New York by The Pudding on NYC's Urban Textscape. This interactive article not only explains how All Text in NYC works but also explores some of the interesting linguistic clusters, recurring phrases, and neighborhood-specific quirks that emerge from the data - like the use of certain languages in different boroughs, or how slogans like “never forget” or “we deliver” dot the city’s commercial and cultural fabric.

What’s fascinating about this project is that it captures not just what’s written, but where and when it was captured. You can trace the spread of a meme, spot clusters of non-English signage that reveal cultural enclaves, or simply marvel at the quirks of hyperlocal advertising.

For example, I searched Urban Textscape for the words Google Maps and in a neat piece of meta discovery, I found a Street View image of the Google Maps Street View car itself. It’s a strange, self-reflective loop: using a tool built from Street View to find a photo of the very car that made All Text in NYC possible. Urban Textscape is full of these surprising moments that blend technology, city life, and storytelling.

This isn’t just a fun distraction - though it definitely is fun. It’s also a powerful reminder that cities speak. The signs we put up, the slogans we repeat, the language we choose - it all forms part of our urban landscape.

Whether you’re a linguist, a data nerd, a city lover, or just curious, it’s worth diving in and seeing what words you can find in New York’s ever-changing textual landscape.

The Ultimate Tube Challenge

Due to the demise of Glitch, I’ve recently moved several of my map projects over to GitHub. In the process of migrating my map memory game - Tube Recall - I decided it was the perfect time to give the game a complete redesign..

🎮 What is Tube Recall?

Tube Recall is a fast-paced, memory-testing game where your goal is simple: name as many London Underground stations as you can. There are 269 stations to name in total, spread across 11 different Tube lines.

🚧 What Has Changed

The biggest change in the redesign of Tube Recall is the switch from Leaflet to MapLibre. This move has allowed me to use customized OpenFreeMap tiles with most map labels turned off. The result is a clean, minimal street map - with no textual clues to help identify the Tube stations. MapLibre’s powerful expression support means I can now dynamically reveal station names on the map only when they’re correctly guessed. 

🎯 Give It a Try!

Whether you're a die-hard Londoner, a transit geek, or just love a good map-based challenge, Tube Recall is the perfect way to test your knowledge and have fun in the process. The game now works beautifully on mobile, so you can even play it while riding the Tube.

👉 Play Tube Recall now and see how many stations you can remember!

When is Pothole Season?

Uptown News has mapped pothole reports made to San Diego's “Get It Done” service system, revealing that January to April is pothole season. By analyzing when pothole repair requests are submitted throughout the year, the newspaper demonstrates a sharp increase in reports during the months of January, February, March, and April compared to the rest of the year.

Admittedly, the animated timeline in the Uptown San Diego Potholes map does most of the narrative work - at least in terms of showing when potholes spike - but it’s still fascinating to watch the map unveil these underlying temporal patterns in how potholes appear on San Diego’s roads.

Curiously, the accompanying article in Uptown News shows little interest in exploring why January through April marks pothole season in San Diego. So, I turned to ChatGPT, which explains:

“San Diego’s January–April pothole surge is primarily driven by rainfall and water infiltration, rather than harsh freeze–thaw cycles (which are minimal in this region).”

I don’t have enough local knowledge to determine whether the map reveals any meaningful geographic trends in pothole distribution across the city. Uptown News also appears just as uninterested in exploring spatial patterns as it is in explaining the seasonality behind San Diego’s potholes. A 2022 article in Uptown News did anecdotally note potholes on “city-maintained freeway entrances and exits.” It would be interesting to use the mapped data to test whether potholes are indeed more common near freeway on-and-off-ramps compared to other roads and road segments.

GeoGuessr for Photos

MapaPhoto

In my never-ending quest to find alternatives to GeoGuessr, I want to like MapaPhoto - however, this latest 'geoguessing' game has just one too many annoying quirks to satisfy my wanderlust.

MapaPhoto’s basic game concept is solid. If you’ve ever played GeoGuessr or any of its many imitators, you’ll be familiar with the idea: identify the location shown in a given image by clicking on a map. Points are then awarded based on how close your guess is to the correct location.

So far, so good.

But this brings me to my gripes with MapaPhoto.

This first one might be a personal bugbear, and maybe it won’t bother you - but it really bothers me that MapaPhoto requires you to press Ctrl to zoom in and out on the map. I’m racing against the clock here - don’t make me mess around with awkward key combinations!

Another frustration is that the game never seems to reveal the actual location in a photo. When you get close enough, your marker turns green to show you're in the right area - but the game never confirms exactly where the photo was taken. FFS, just tell me where I was supposed to click!

My final and perhaps biggest complaint: although MapaPhoto uses the Google Maps API, it doesn't include Street View. That seems like such an obvious feature for a visual game about real-world locations. Even if you don’t want players using Street View to search for the photo’s location (which might feel too much like GeoGuessr), you could at least reward correct guesses by showing the same view in Street View side-by-side with the original photo.

Despite these frustrations, MapaPhoto is still a fun game to play. If you're a fan of GeoGuessr, then MapaPhoto is definitely worth a try. The core idea is engaging, and with just a few improvements, it could become yet another strong contender in the geoguessing genre.

Time Travel Maps

If I were President of the World every major city would be required to create a 3D city map documenting the city for every year of its history. Unfortunately I am not yet the global overlord so my dreams of virtual time-travel go largely unfulfilled.

But in Zurich, I can get close.

Zurich Time Travel is an impressive 3D interactive map that reconstructs the city’s architectural evolution from 1850 to the present. Built using open city data and historical maps it lets you scroll through time, and observe how the city's medieval alleys have given way to grand boulevards and modern skyscrapers.

Using the map's timeline you can witness the growth of Zurich, from a compact, walled city hugging the Limmat River to the modern sprawling metropolis it is today.

You can explore even further back in time on the Zurich 4D interactive map. This map includes digital 3D models of the city in 3000 BC, in the year 200, in 1500 and in 1800 - providing a fascinating insight into how the city of Zurich has developed over time.

If you closely explore the ancient 3000 BC model of Zurich you might be able to spot a few Neolithic stilt houses nestled among the trees. The 3D model of the city in 1800 shows a city which is still largely confined within its medieval city walls. Skip forward to view the 3D model of the modern city and it is now hard to even discern the location of the historic city walls amongst the modern sprawl of Zurich. 

In the USA, the Welikia Project lets you travel back in time to explore New York’s natural landscape before the arrival of Dutch settlers. This interactive map reconstructs Manhattan Island as it existed pre-1600, revealing its original ecosystems - rolling hills, dense forests, sprawling wetlands, salt marshes, and a network of streams and ponds.

To create this digital time capsule, researchers combined early historical maps, soil surveys, and tree-ring analysis with firsthand accounts from colonial-era records. These sources helped piece together an accurate portrait of the island’s lost wilderness - long before skyscrapers and paved streets transformed the city forever.

How Hazardous is Your Town?

Now that all links to FEMA’s National Risk Index appear to have been purged by the Trump administration, you might want to bookmark CartoGuophy’s United States of Rising Hazards map instead.

Before it was removed by the Republicans, FEMA’s National Risk Index map provided detailed information about the risk from 18 different natural hazards across the United States. For example, if you were thinking of sending your kids to summer camp, you could click on the map to check the flood risk in that area. In fact, the map allowed you to see which counties were most at risk from each of the 18 natural hazards nationwide.

Although the Trump administration has taken down the National Risk Index from FEMA’s website, you can still explore these risks using the United States of Rising Hazards map. Click on your home on the map, and you'll see your FEMA-based risk scores for all 18 hazards, as calculated from the original National Risk Index (NRI) dataset.

The map also includes layer filters that let you view the relative risk levels of the 18 natural hazards across the U.S. Each hazard is assigned a unique color, and the intensity (or transparency) of that color indicates the level of risk: brighter, more opaque colors signal higher risk, while fainter, more transparent colors indicate lower risk.

The Global News Map

Over the years, there have been many attempts to map the news. With the advent of AI and its ability to automatically detect locations mentioned in news articles, we're now seeing a resurgence in News Maps.

The latest of these is Needle, which uses a large language model (LLM) to "best estimate general locations of stories posted in the past day, and pin them on the map." Using the map, you can zoom in on any location in the world to explore the latest news. According to Needle's 'About' page each story location is determined based on a hierarchy: if a specific place is mentioned, the story is pinned there; if only a city is named, the pin is placed randomly within city limits; and if only a country or region is referenced, it's placed somewhere within that broader area. However, as the creators note, AI isn't perfect - so a story’s location on the map doesn’t always mean it’s truly tied to that place.

One major drawback of Needle at the moment is its limited range of news sources. The creator notes that the map is currently "limited to mostly Canadian sources of news." This is especially apparent in places like London, where today's top stories include how King Charles misses Canada and how a Canadian female soccer player has signed with a London team.

However, there is a filter option to select news sources by the "United States" - so if you're American, you may be able to sidestep the map’s Canadian bias. Needle is also looking to expand its news source database and anyone can suggest new sources by emailing Needle.

Other filter options allow users to refine the stories shown on Needle by category, including Politics, Sports, Business & Economy, Technology, and Environment & Climate.