The Guardian just published an amazing interactive regarding immigration on the south Texas border. It’s all powered by the new open-source Mapbox GL JS framework for the web.

Hats off to their team Melissa del Bosque, The Texas Observer, Kenton Powell, and the Guardian US interactive team.

Get started now with Mapbox GL, available for iOS, OS X, Linux and the web.

The new imagery coming down from WorldView-3, the satellite that DigitalGlobe launched only two weeks ago, is amazing! And this early imagery is now live on Mapbox Satellite for all Mapbox.com maps. The combination of color and crispness from WorldView-3 is unparalleled by any other commercial imagery that we’ve worked with. We’re starting with a small update to Mapbox Satellite, just a 3 km² area around Madrid’s airport, but the details are stunning. Below you can see minute runway details, down to expansion joints in the pavement. You can read the numbers on the planes’ parking lots, count shipping containers, and see trucks queued for departure. The satellite has laid out the whole story of the airport’s traffic at this moment in time. Shot from 619km altitude in space, you can’t tell the difference between this imagery and the 30cm flyover imagery that it’s seamlessly mosaiced with in our map.

© Mapbox, Digital Globe

Captured on August 21, eight days after launch at 12:56:21 local time, Madrid Spain. Using WorldView-3’s 27 super-spectral bands. Powered by Mapbox GL.

We can’t wait for more imagery in the coming months as we look to continue to build out the most beautiful satellite map in the world. The combination of image quality, image volume, and timeliness will make entirely new kinds of maps possible. The satellite is still in testing phase, but DigitalGlobe is already taking early orders, so if you’re looking for updated imagery, or even custom tasking, drop us a line satellite@mapbox.com.

By extracting and analyzing historical OpenStreetMap data, we can see the story of contributions to the dataset over time. The number of edits, number of contributors, geographic concentration of contributions, and pace of change are all accessible for analysis and visualization.

Moscow

3,613 contributors - 1,000,898 features - May 2008 to August 2014

Berlin

6,011 contributors - 1,447,791 features - June 2007 to August 2014

Baghdad

154 contributors - 38,090 features - December 2006 to July 2014

London

6,700 contributors - 1,887,638 features - March 2006 to August 2014

Juba

188 contributors - 82,368 features - November 2009 to August 2014

An Australian imagery update adds 30 billion fresh pixels to Mapbox Satellite. The new data goes in to zoom level 19, meaning you can count cars and bushes. As always, it’s licensed for OpenStreetMap tracing and is available on our Commercial Satellite plan.

Today we’re live with fresh pixels of Australia, some of which were captured on Tuesday this week. This update is part of our ongoing global refresh of half a million km². We select the best images, then render them with the Satellite Live processing pipeline. Today’s imagery comes to many parts of Australia, from the remotest outback to the biggest metro areas:

Crisper imagery

With ultra high-res data from Digital Globe’s WorldView-2 satellite, we render down to zoom level 19. That means you can see everything from backyard gardens to street markings, footpaths in parks, and the details of industrial sites.

Recency matters

All of the 18,000 km²+ (4.5 million acres+) of new imagery is from the last year. Fresher is always better, but especially when it comes to feature extraction for the OpenStreetMap community and for Commercial Satellite.

Hit me up (@brunosan on Twitter) with any questions. If you’re interested in an update like today’s for another area, please visit our imagery request tracker and we’ll prioritize it.

Smartphone-to-car startup Automatic just went live with an analytics dashboard. Automatic is making driving safer and smarter for everyone and their dashboard shows everything about your car’s gas mileage, parking locations, and onboard computer issues. This dashboard breaks down every driving segment with details ranging from hard braking and acceleration stats to improve mileage to route summaries on the map. The custom map branding fits Automatic’s product perfectly, with a clean look to the map and APIs for direct integration into the dashboard app.

Welcome Shiv! A long-time colleague from the international development space, Shiv started mapping using TileMill 0.4 (old school 2011-style) and now joins us to help grow our data team, expand our data collection operations, and push into new markets.

We’re in Portland this week for the FOSS4G conference and will be hitting up JS.geo and WhereCamp PDX before and after — come say hi! Throughout the week we’ll be talking and giving workshops on Mapbox Studio, the future of Leaflet, why GL matters, and a lot more. Watch @Mapbox on Twitter for updates on our sessions, and hit up @mourner@jfire@lbudorick@incanus77@geografa@springmeyer@sgillies to talk more about Mapbox and open map technologies.

And don’t forget to swing by the FOSS4G closedown and WhereCampPDX kickoff party on Friday.

Matt Irwin joins the Mapbox team after eight years working as a diplomat with the Department of State. While at State, Matt mediated boundary disputes, negotiated ceasefire agreements, and forged relationships with rebel groups in the Middle East. Most recently he led the Syria team within State’s Bureau of Near Eastern Affairs and served as liaison to the intelligence community for activities in Syria. Matt will be pushing on the business side and working to spread Mapbox in government.

I’m presenting on our imagery processing pipeline and how we deal with the enormous amount of imagery that we see every day, from satellites to drones, at the Bay Area GeoMeetup, this Thursday the 11th at 6:30 at the Mapbox office. Our pipeline is a set of customizable and modular image processing components that handle everything from data calibration to declouding, mosaicking, and color adjustment. At a scale of tens of trillions of pixels, it all has to work smoothly and efficiently. The pipeline is what lets us hook up to any imaginable imagery source—ultra high-res commercial data, microsat frames, weather satellite streams, aerial and drone surveys, you name it—and get consistent, beautiful maps.

A very simple pipeline for Landsat 8: low-resolution color data (left, including the Golden Gate Bridge) is combined with high-resolution panchromatic data (center, including Alcatraz) to prepare a true color image (right, including SOMA and Mapbox SF, where we’ll see you on Thursday).

I’ll talk about the challenges we’ve found while building and refining this system, and how we worked through them. I’ll also mention some details of basemap philosophy, for example how we prioritize image recency versus image quality. And I’ll point out some resources like free imagery and open-source tools that anyone can use to get started working with satellite data. All illustrated with lots of pretty pictures, of course.

That’s “Big and Little Satellites” at Mapbox SF on the 11th! We’ll hear talks by people from satellite companies and other parts of the imagery ecosystem—including me. RSVP now and come by!

Mapbox Studio, our open source map design platform, launches today across all platforms; Mac OS X, Windows and Linux. Studio allows anyone to design radically custom maps, easily work with huge global datasets, publish updates in seconds, and design with resolution independence from retina devices to high resolution printing.

It's the first map design application built from the ground up using vector tiles, providing a new level of design control and interaction, all while being more performant - lighter and faster on any mobile app and web site. Now you can style maps faster, your data simply scales, and everything renders sharper than ever before.

Editing Mapbox Outdoors, one of the example styles included with Mapbox Studio.

Instant access to big data

Studio gives you immediate access to Mapbox data. Use the OpenStreetMap-based Mapbox Streets to style roads, highways, parks, buildings, local venues and more. Create and customize elevation contours and hillshades to visualize natural geography with Mapbox Terrain. Take full control over the color balance, saturation and contrast of satellite and aerial imagery using Mapbox Satellite.

These datasets and your own custom vector tiles are available without massive downloads or huge imports by streaming vector tiles directly into Studio using your Mapbox access token. We manage all the data on our platform, providing live updates every minute to all our global data sets, and serve maps fast wherever you are in the world.

Some of the custom styles included with Mapbox Studio that you can use as a starting point.

Radical design tools

Studio lets you combine different datasets into the same map and style them seamlessly as if they were one. You can use the same CartoCSS styling language created for TileMill by the Mapbox team with capabilities unlocked by vector tiles. Merge raster and vector layers and blend between the two using advanced compositing effects. Iterate quickly on different styles to create the best possible map designs.

Retina

Deploying a Mapbox Studio style takes seconds and comes ready to serve billions of tiles globally at multiple resolutions. Vector tiles allow the Mapbox API to serve @2x 512x512 tiles automatically for retina devices without any additional effort. The same resolution independence powers the hidpi image export in Mapbox Studio for making print-ready maps at up to 600dpi.

High end cartography

Start publishing up to 5 custom styles with Mapbox Studio on the Mapbox Standard plan for $49/month. Download Mapbox Studio now and use it free for 30 days.

Join us at 6:30pm tomorrow for a GeoMeetup at Mapbox SF to talk Big and Little Satellites, organized by Ragi Burhum and Bronwyn Agrios. Charlie Loyd from our team will be talking about our imagery processing pipeline— all over beers and pizzas from our friends at Digital Globe. Looking forward to catching up!

Directions to Mapbox SF

Our office in San Francisco is at 149 9th Street. We’re on 9th between Howard & Mission in a big brick building with an old-school sign that says “The Storex Building”. Once you reach the entrance use the intercom to call Suite 404 and we’ll buzz you in.

The OpenStreetMap community has mapped more than 43,700 miles of road in Syria. This data is of vital importance to humanitarian workers on the ground. Over just the last three and a half years, the OSM community has traced more than 13,000 buildings and added over 5,500 thousand miles of road in key urban areas in Syria. The results are helping humanitarian workers and average Syrians deliver food, distribute water, and rescue civilians from collapsed buildings. Better maps created by fresh imagery and the OpenStreetMap community can make their work safer and more effective.

For more, watch OSM contributions since March 2011:

Key Urban Areas

Damascus

Aleppo

Homs

Raqqa

Deir al-Zour

Meet us in Mexico City for Condatos, this year’s major Latin American Open Data conference bringing people from all over the continent together around building a better future with open data. We will be talking about open source mapping tools for totally custom data, drone mapping and making OpenStreetMap the best map in the world.

Look for Tom, Eric, Paul, and myself at one of the following events:

Drone mapping — Sep 30

We’ll be mapping part of a neighborhood in Mexico City, showing how drones can be used to rapidly generate imagery, publish it through Mapbox and use it for tracing in OpenStreetMap or other mapping platforms.

AbreLatam — Sep 30

We’ll be attending the regional open data unconference AbreLatAm to connect with the Latin American open data community.

ConDatos — Oct 1

This is the opening day of the conference, between these amazing talks hunt us down in the hallways for a chat.

ConDatos social — Oct 1

Let’s party and connect over drinks - details to be announced.

ConMapas — First Latin American OpenStreetMap day

If you make us pick, this is the part we’re most excited about. Conmapas is the first regional meeting of the Latin American OpenStreetMap community, bringing together community leaders, non profits and businesses to discuss the future of OpenStreetMap in LatinAmerica. Whether you’re already familiar with OpenStreetMap and talk about growing the project even bigger in Latin America or you’d like to learn more about the project - this is the place to be. Condatos is coming right at the time of amazing growth in the Latin American community and leading right up to the annual State of the Map taking place later this year in Buenos Aires.

Duncan is joining the Mapbox design team, coming to us from daytime hours at The Washington Post and nighttime experiments with CSS and JavaScript:

Duncan will be jumping in to scale our developer support, explore new data visualization tools, and design features in our growing product suite.

With vector tiles, Mapbox Studio maps are print ready. The resolution independence of vector tiles now makes it possible to create a map with flexible resolution appropriate for high quality printing. Now your data doesn’t just scale, it renders across all media in sharp detail.

Exporting print ready images of Mapbox Outdoors and dynamically styling

Download print ready images in Mapbox Studio through the export pane, integrated into the style pane for quick styling of print areas. You choose between three different paradigms for selecting the export area based on use case: dimensions in pixels, dimensions in inches, and geographic area. Export png and jpeg images at 150, 300, and 600 ppi.

Paris at 150, 300, and 600 dpi

To create high resolution static images of your maps, we use abaculus to collect the vector tiles within the area you’ve selected to export, increase the dimensions of an individual tile from 256 x 256 pixels to 1024 x 1024 pixels or higher, and stitch them together seamlessly.

How Abaculus scales

Tips for better prints:

• Use svg icons and shields, such as Maki, in map styles instead of raster elements to maintain the fidelity of your styles across resolutions.
• Like raster icons, raster fill patterns and textures do not scale well.
• Use CartoCSS to filter or move labels that may be cropped in your desired export area.

We’re excited to welcome Peter to the Mapbox design team, where he will be focusing on map creation tools with an eye for user experience. Peter comes to us from a background in application design and data visualization. Check out his awesome Muni bus visualization!

Say hello to Danny Aiquipa. Danny is a power OpenStreetMap contributor. She is excited to join the Mapbox data team working on improving the map, systematically fixing errors, and adding data. For some examples of what our data team is up to, take a look at our recent efforts to add all buildings to San Francisco and update road networks across the United States.

We are heading to the Code for America summit next week! The Summit is where cities come to share, inspire, and collaborate around tackling some of the toughest civic challenges with the power of open source. We here at Mapbox Code for America, open source, and makingfantasticmaps that improve our communities.

Look for Camille and myself– we’ll be there ready to talk maps and open source government tools. As a former Code for America fellow, I’m particularly looking forward to see the great things this year’s fellows have accomplished!

With Mapbox Studio, it’s straightforward to apply styles to every building, park, or road label in the world. But sometimes you want more control. Regular expression filters are one way to get control. They’re just like regular filters, but instead of matching exact strings, they match patterns. With regular expressions, you can do things like select every city that starts with the letter “M” or every road label that has between 10 and 20 characters.

Local control with global datasets

To showcase the usefulness of regular expressions, I’m going to make a map of the 14th Street corridor in Washington, DC using Mapbox Streets data.

I’ll start by adding a single point to the map:

#poi_label[address='1811 14th Street NW'] {
  shield-file: url('marker.svg');
  shield-unlock-image: true;
  shield-size: 12;
  shield-fill: #e16363;
  shield-name: '[name_en]';
  shield-face-name: ‘Open Sans Bold’;
  shield-text-dy: 8;
}

I’m filtering out every point of interest in the #poi_label layer that doesn’t have an address that exactly matches the Black Cat’s address. Now that I have the Black Cat on my map, I could take the same approach to add the rest of the POIs along 14th Street to the map.

Instead of writing dozens of nearly duplicate selectors, I can use a regular expression to automatically match everything along 14th Street:

#poi_label[address=~'.*14th Street N.*'] {
  shield-file: url('marker.svg');
  shield-unlock-image: true;
  shield-size: 12;
  shield-fill: #e16363;
  shield-name: '[name_en]';
  shield-face-name: 'Open Sans Bold';
  shield-text-dy: 8;
}

Lets break down how this works: the =~ operator tells my style that the following filter is a regular expression, and not a basic string match. That means I can use regular expression tokens. The . at the beginning of the filter is a token meaning “any character”. The * that follows means, “match 0 or more of the preceding token”. 14th Street N is basic string. The . and * at the end mean the same thing as those at the beginning: match any character, any number of times.

Taken together, the whole filter translates to, “look for every feature that starts with any combination of characters, followed by exactly ‘14th Street N’, followed by any combination of characters”. The filter will match 1811 14th Street NW as well as 1714 Rear 14th Street Northwest Washington 20009, so it covers a range of address formats but is specific enough to avoid picking up unwanted points.

I’m now going to make the focus on 14th street clearer by aligning map labels relative to the street:

#poi_label[address=~'.*14th Street N.*']{
  shield-file: url('marker.svg');
  shield-unlock-image: true;
  shield-size: 12;
  shield-fill: #e16363;
  shield-name: '[name_en]';
  shield-face-name: 'Open Sans Bold';
  [address=~'(...)[13579].*'] {
    shield-text-dx:  8;
  }
  [address=~'(...)[24680].*'] {
    shield-text-dx: -8;
  }
 }

I’m taking advantage of the fact that addresses on the East side of the street have odd numbers and addresses on the West side of the street have even numbers. The regular expression (…)[13579].* means, “match any three characters, followed by 1,3,5,7, or 9, followed by any number of characters”. So 1835 14th Street NW as well as 2231 14th Street North West both match.

After a few more tweaks, here’s the final map:

Check out the project source code for details, and open it in Mapbox Studio to experiment more with regular expressions.

More Examples

Regular expressions are useful for conventional mapping techniques like controlling the size of shields on highway labels based on the contents of the labels. The Mapbox Studio default style Looseleaf uses this technique:

#road_label::us_shield[class='motorway'] {
  // 1 & 2 digit US state highways
  [ref =~ '^(AL|AK|AS|AZ|AR|CA|CO|CT|DE|DC|FM|FL|GA|GU|HI|ID|IL|IN|IA|KS|KY|LA|ME|MH|MD|MA|MI|MN|MS|MO|MT|NE|NV|NH|NJ|NM|NY|NC|ND|MT|OH|OK|OR|PW|PA|PR|RI|SC|SD|TN|TX|UT|VT|VI|VA|WA|WV|WI|WY|SR)\ ?\d[\dA-Z]?(;.*|$)'] {
    shield-file: url(img/shield/us_state_2.png);
    shield-name: @us-shield-name;
  }
  // 3 digit US state highways
  [ref =~ '^(AL|AK|AS|AZ|AR|CA|CO|CT|DE|DC|FM|FL|GA|GU|HI|ID|IL|IN|IA|KS|KY|LA|ME|MH|MD|MA|MI|MN|MS|MO|MT|NE|NV|NH|NJ|NM|NY|NC|ND|MT|OH|OK|OR|PW|PA|PR|RI|SC|SD|TN|TX|UT|VT|VI|VA|WA|WV|WI|WY|SR)\ ?\d\d[\dA-Z](;.*|$)'] {
    shield-file: url(img/shield/us_state_3.png);
    shield-name: @us-shield-name;
  }
  // 1 & 2 digit US highways
  [ref =~ '^US\ ?\d[\dA-Z]?(;.*|$)'] {
    shield-file: url(img/shield/us_highway_2.png);
    shield-name: @us-shield-name;
  }
  // 3 digit US highways
  [ref =~ '^US\ ?\d\d[\dA-Z](;.*|$)'] {
    shield-file: url(img/shield/us_highway_2.png);
    shield-name: @us-shield-name;
  }
  // 1 & 2 digit US Interstates
  [ref =~ '^I\ ?\d[\dA-Z]?(;.*|$)'] {
    shield-file: url(img/shield/us_interstate_2.png);
    shield-name: @us-shield-name;
    shield-fill: #fefef1;
  }
  // 3 digit US Interstates
  [ref =~ '^I\ ?\d\d[\dA-Z](;.*|$)'] {
    shield-file: url(img/shield/us_interstate_3.png);
    shield-name: @us-shield-name;
    shield-fill: #fefef1;
  }
}

Regular expressions are also a powerful tool for more expressive visualizations. The map Assemblage uses regular expressions for random effects on buildings:

#building[osm_id =~ '.*[89]'][zoom>16] {
  [osm_id =~ '.*8'] { polygon-fill: @pink;}
  [osm_id =~ '.*9'] { polygon-fill: @lightblue;}
  polygon-geometry-transform: rotate(20,0,0);
  polygon-comp-op: multiply;
}

#building::a[osm_id =~ '.*[0123456]'][zoom>15] {
  [osm_id =~ '.*4'] { polygon-fill: @yellow;}
  [osm_id =~ '.*5'] { polygon-fill: @lightblue;}
  [osm_id =~ '.*6'] { polygon-fill: @gray;}
  polygon-fill: @green;
  polygon-geometry-transform: rotate(-3,0,0);
  polygon-comp-op: multiply;
  [osm_id =~ '.*[0-3]'] {
    polygon-pattern-geometry-transform: rotate(-3,0,0);
    polygon-pattern-file: url("il6.png");
    [zoom=19],[zoom=15]   { polygon-pattern-file: url("il3.png"); }
    [zoom=20],[zoom=16]  { polygon-pattern-file: url("il4.png"); }
    [zoom=21],[zoom=17]  { polygon-pattern-file: url("il5.png"); }
    [zoom=22] { polygon-pattern-file: url("il6.png"); }
    [zoom=18] { polygon-pattern-file: url("il7.png"); }
  }
}

Here’s a beautiful map style by AJ Ashton that wouldn’t be possible without regular expressions:

Map {
  background-color: #012;
}

@seed: #f24;
['mapnik::geometry_type'>1] {
  [osm_id =~ '.*0$'] { line-color: spin(@seed,36*0); }
  [osm_id =~ '.*1$'] { line-color: spin(@seed,36*1); }
  [osm_id =~ '.*2$'] { line-color: spin(@seed,36*2); }
  [osm_id =~ '.*3$'] { line-color: spin(@seed,36*3); }
  [osm_id =~ '.*4$'] { line-color: spin(@seed,36*4); }
  [osm_id =~ '.*5$'] { line-color: spin(@seed,36*5); }
  [osm_id =~ '.*6$'] { line-color: spin(@seed,36*6); }
  [osm_id =~ '.*7$'] { line-color: spin(@seed,36*7); }
  [osm_id =~ '.*8$'] { line-color: spin(@seed,36*8); }
  [osm_id =~ '.*9$'] { line-color: spin(@seed,36*9); }
}

Learn more

For an excellent starting point for writing your own regular expressions for Mapbox Studio styles, visit www.regexr.com.

We’ll be at one of our favorite bars, Strongroom, in London next Friday, September 26th. Swing by to talk maps, satellite imagery, and OpenStreetMap over drinks. You’ll find Alex and Eric at the bar from 6pm on.

RSVP today– can’t wait to catch up!