Patrick Niklaus is joining Mapbox. He has worked on great projects before like the alaCarte map renderer. Patrick has been amazing to work with in academia and I’m excited to announce that he is joining the Mapbox directions team part time. Patrick is currently pursuing a degree in computer science.
Maptime is coming to DC with its inaugural meetup today, June 17 at 6:30 in the Mapbox garage. This hands on meetup teaches skills on how to make online maps, no matter your experience level. This first meetup will walk through how to make an edit in OpenStreetMap using the iD editor.
Maptime is an excellent way to bring new people into the mapping community. We’re excited to be involved in the new DC chapter, as well as groups in San Francisco, Portland, and Toronto.
While this week’s MaptimeDC is fully booked, you can sign up for the waitlist here, join the meetup group and follow @MaptimeDC on Twitter for news about future events.
Lauren Budorick is joining the Mapbox team in San Francisco!
Lauren is a graduate of Hackbright Academy, where she built an elevation-based running route generator. She’ll be putting her development and design skills to work on some exciting new products.
Hikable.com just launched, giving hikers step by step trail descriptions and tools for planing trips on detailed terrain map with elevation data. Anyone can now create their own hiking guides on a map that shows every mountain, river, stream, and summit using Mapbox Outdoors - the map also is updating trails, walkways, and street in real time from OpenStreetMap.
Mapbox Outdoors is available for Enterprise plan holders now and will be available this summer for all Mapbox plans. Let us know if you want early access.
Embedded videos in maps let you explore content in new and exciting ways. This video was shot from space in January over Maryland. As you zoom, rotate and pan, you can clearly see two power generation stations: Brandon Shores Generating Station to the west and the Herbert A. Wagner Generating Station to the east. Smoke billows from a smokestack at the coal-fired Brandon Shores station, indicating operational status at the plant and a moderate wind from the west.
The Mapbox GL framework allows for new types of map visualizations such as the video embedded into the map above. The video is loaded in a hidden HTML5 video element with multiple source formats. From there the video is handled the same way any video element would be, with full control over pausing, looping and scrubbing.
varurls=["/videos/baltimore-smoke.mp4","/videos/baltimore-smoke.webm"];varvideo=document.createElement('video');video.crossOrigin='Anonymous';for(vari=0;i<urls.length;i++){varsource=document.createElement('source');source.src=urls[i];video.appendChild(source);}An RGBA texture is created to store the current frame.
vartexture=gl.createTexture();gl.bindTexture(gl.TEXTURE_2D,texture);gl.texParameteri(gl.TEXTURE_2D,gl.TEXTURE_WRAP_S,gl.CLAMP_TO_EDGE);gl.texParameteri(gl.TEXTURE_2D,gl.TEXTURE_WRAP_T,gl.CLAMP_TO_EDGE);gl.texParameteri(gl.TEXTURE_2D,gl.TEXTURE_MIN_FILTER,gl.LINEAR);gl.texParameteri(gl.TEXTURE_2D,gl.TEXTURE_MAG_FILTER,gl.LINEAR);gl.texImage2D(gl.TEXTURE_2D,0,gl.RGBA,gl.RGBA,gl.UNSIGNED_BYTE,video);On each frame, the texture is updated to hold the video's current frame.
gl.bindTexture(gl.TEXTURE_2D,texture);gl.texSubImage2D(gl.TEXTURE_2D,0,0,0,gl.RGBA,gl.UNSIGNED_BYTE,video);The texture is then drawn to the screen with two triangles (a quad) formed by projecting the bounding box coordinates.
We've been hard at work on expanding Mapbox GL across platforms to allow for these and other exciting new mapping opportunities. We're continuing to push out and refine tools that facilitate total control and flexibility when it comes to building and sharing maps. Stay tuned for updates to the open source Mapbox GL framework including video support.
This is what 1.5 million walks, runs, and bike rides look like. The colors of the tracks denote route length, glowing white hot in the places where athletes most often travel. Longer routes over 20 miles render yellow, while shorter workouts range from cool blues to hot pink.
Eric Fischer worked with the RunKeeper team to composite an entire planet's worth of publicly-shared routes on an adjusted Mapbox Outdoors terrain layer.
Each route on the map was added and made public by RunKeeper users, providing a glimpse at what athletes are doing all over the world.
Mapbox Outdoors is available for Enterprise plans now and will rollout late summer for all of our Mapbox plans – get in touch if you want early access.
In the past months our data team has updated 71,000 roads and added 69,000 new ones to OpenStreetMap. Our work is spanning the entire United States, touching over 80 cities and metropolitan areas so far. This is part of our effort to continuously improve the quality of OpenStreetMap. Here is a map of all the areas we have updated so far.
Do you have questions or feedback about our data improvement work on OpenStreetMap? Tweet at us or post a ticket on Github. Interested in improving roads on the US map yourself? Here’s how to get started.
Endurance athletes can now see where they’ll be hurting the most as they haul up mountains, run through canyons, or power through the water with the new app, Compete Hub. Maps are huge for triathletes on Compete Hub, so this week they just added the high density zooms, hill shades, and contours of Mapbox Outdoors.
Challenge Walchsee-Kaiserwinkl, home to one of Europe’s most beautiful triathlon race courses
Compete Hub is also leveraging the modularity of the Mapbox.js API, which lets them add in additional functionality, like a plugin to view the map full-screen and scrub through elevation profiles with contextual markers.
If you’re an athlete, sign up with Compete Hub and start planning your races alongside some beautiful maps.
Join us for happy hour at Mapbox SF on June 26th at 6pm and learn everything about Mapbox maps on Android. Just last month we launched the Mapbox Android SDK. This Thursday you’ll have the chance to find out more about open source maps and geo services, and how to make your own beautiful data driven maps — all over a drink. RSVP here!
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”.
For Google I/O attendees, it’s a 5 block walk from Moscone West, straight down Howard Street. Once you reach the entrance use the intercom to call Suite 404 and we’ll buzz you in.
For several years, taxis in New York City have had GPS receivers to record the location of the start and end of every trip, but the data has never been made available to the general public. Chris Whong and Andrés Monroy used New York’s Freedom of Information Law to request a copy of the taxi records from 2013 and publish them on the web. I plotted the starts of trips in blue and the ends in orange on this map:
New York taxi pickups and dropoffs
It is a fascinating data set, one of the densest I’ve ever seen. There were about 187 million taxi trips made during the year, almost all of them within the confines of Manhattan Island.
There are dropoffs all over the city and at Newark Airport in New Jersey, but if you want to catch a taxi, it helps to be in the right place and even on the right side of the street. The pattern is especially clear in Brooklyn, where taxis drop off passengers on the sides of the streets leading away from the Brooklyn and Manhattan Bridges and then pick up new passengers on the other side of the street. A similar pattern is visible on Broadway on the Upper West Side. Individual street corners stand out in brightness as particularly popular places for people to be picked up or dropped off.
Dropoffs and pickups on opposite sides of the street
The patterns at JFK and LaGuardia airports show interesting artifacts of the data collection process. Almost all of the trips there must have really begun or ended right at the terminals, but many of them are attributed to the roads leading to and from the airports, where the last good GPS fix must have occurred.
Terminal access roads at LaGuardia Airport
A different kind of GPS noise turns up in the fuzzy streets of Midtown Manhattan, where the taxis don’t completely lose the GPS signal but have to contend with signals bouncing off of tall buildings. At the lower left are some very bright spots from the many taxi trips to and from Penn Station.
GPS noise in Midtown Manhattan
OpenAddresses is amazing data for geocoding and map making. We wanted to make a map of all 30 million addresses to get an idea of how much coverage there already is and which areas are missing. What we found was a variety of artistic patterns of dots that describe neighborhoods and cities.
Interested in using address data or know of an open address dataset? Head over to OpenAddresses to learn more about the project.
West Palm Beach
San Francisco
Auckland, New Zealand
Washington DC
Interactive map (fullscreen)
Lookout, the leader in mobile security, has switched to Mapbox. Trusted for security by over 50 million users worldwide and leveraging the world’s most comprehensive mobile data set, Lookout protects individuals and organizations from advanced mobile threats, often before they put data, devices and networks at risk.
We worked with the Lookout team to not only provide a secure infrastructure that they could trust, but also designed a custom map that fit their brand and interface.
At the core, it’s a utilitarian and legible map that follows cartographic standards for coloring and label hierarchy. Subtle tones and an emphasis on place labels make it perfect for adding context. The map’s color palette, clean aesthetic, and typographic hierarchy rooted in Avenir Next make it a recognizable part of the Lookout brand.
Download the app to secure your phone today.
Watch your groceries travel right to your doorstep with Instacart’s live map view. The San Francisco-based grocery delivery service is now operating in 10 cities nationwide and has begun using the Mapbox Directions API to display the best routes for their deliveries.
Using the plug-and-play versatility of the Mapbox.js API, Instacart broadcasts the car’s location on your order page.
The Directions API is currently available for paid accounts on Mapbox.com. If you want to use it for your product, reach out to us at sales@mapbox.com and find out more on our developer’s page.
You can now drag & drop spreadsheet files on the Mapbox editor and we’ll automatically turn placenames into points on a map! Ever since we launched the improved editor on Mapbox.com, we’ve noticed that a lot of great geographic data talks in addresses and states, not latitude and longitude. Now we speak that language, thanks to the Mapbox geocoder and a new user-friendly interface.
So, if you have a spreadsheet that looks something like this, Mapbox will guide you through the process of converting it into geodata. This works alongside our existing support for DSV formats like CSV and TSV. It’s easy to get these kinds of files out of your Google Spreadsheets and Microsoft Excel documents.
| Title | Address | City | Province |
|---|---|---|---|
| Ontario Science Centre | 770 Don Mills Road | Toronto | Ontario |
| Toronto City Hall & Nathan Phillips Square | 100 Queen Street West | Toronto | Ontario |
| TIFF Bell Lightbox | 350 King Street West | Toronto | Ontario |
Our geocoding service is happy to place points on exact street addresses in the United States & Canada. We’re working on compiling more open data to support more granularity worldwide, but in the meantime, accuracy outside of North America is limited to cities and countries.
Here is a little preview of some of the new fonts from our friends at FontFont that we are going to include in the next version of Mapbox Studio:
Developer Will Snook joins the Mapbox mobile team! Will has been leading development on MBXMapKit for the past few months after spending some time with it and our iOS SDK on client projects in the past year. We’ve since contracted him to work on Mapbox GL and other mobile projects as we reshape our rendering technology.
Starting way back in middle school algebra with a QBasic plotting program to untangle the troubling mysteries of y = f(x), Will has been enthusiastically writing code to understand patterns, answer interesting questions, and solve practical problems. His most recent project was a special purpose topographic map designed to help answer the question, “What’s the name of that mountain over there?”. You’ll be hearing more about that topo map soon.
Mapbox will be in New York on Thursday for AWS Summit at the Javits Center. If you’re attending the conference or just in the area, let’s grab a coffee. Ping me @willwhitedc.
Also, don’t miss my talk at 4:30 PM, which is part of the disaster recovery session from AWS Architect Ryan Holland. I’ll be sharing how Mapbox prepares for natural disasters like Hurricane Sandy using multiple AWS regions.
If you can’t make the session, check out this recording from the San Francisco Summit in March:
Here’s a typical example of what the horizon might look like across an intersection or parking lot as you walk around Boulder, Colorado:
The picture above shows Bear Peak, the Flatirons, and Green Mountain, which are all part of the Front Range. Depending on where you are in town, it’s also possible to see through valleys back to the Indian Peaks, which are considerably higher and further west. There are also some interesting and distinctive hills in the plains north of Boulder. I got tired of not knowing the names of mountains and hills that I see all the time when walking around town, so I made a map.
After shopping around for existing printed maps, I decided that none of my available options showed the data I wanted at an appropriate scale. What I really needed was a specialized topo map which had four main layers:
Sparse elevation contours with enough detail to pick up hills in the plains, but not so much as to turn into mushy hill-shading up in the Indian Peaks.
State and Interstate highways to provide a sparse summary of the city of Boulder’s road network.
A significantly filtered subset of the POI data from the United States Board on Geographic Names' Geographic Names Information System (GNIS) for the state of Colorado.
A graticule with longitude lines spaced no more than about an inch or two apart so that they can be used with the alignment marks on the dial of a compass like this:
Here’s a closeup:
Here’s what the first version looked like:
And here’s the full-sized 270dpi 8.5"x11" image.
To make this map I used TileMill with public domain data from the USGS and Natural Earth.
My TileMill layers look like this:
#markers: This CSV layer adds a POI marker for the office of some friends in Boulder.#boulderGNIS01: This is the filtered-down list of GNIS POI’s for Colorado. My Python script to do the filtering and the resulting .csv output are at wsnook/hiking-toys/gnis.#graticule: This is a 0.05° GeoJSON graticule with named latitude and longitude lines. My Python script to create it, and the resulting JSON, are at wsnook/hiking-toys/graticule.#majorRoads: This is Mapbox’s hosted copy of Natural Earth North American roads: /natural-earth-1.4.0/cultural/10m-roads-north-america.zip.#contour2.contour and #contour1.contour: USGS 1°x1° contour shapefiles that I downloaded from The National Map Viewer: Elev_321499_Greeley_W_1X1 and Elev_321379_Denver_W_1X1. Those files include a mix of 40ft and 10ft contours, but what I really needed was 80ft contours, so I used a gigantic brute-force CartoCSS selector to enumerate each and every contour elevation that I wanted to include in the map (i.e. [CONTOURELE=4680],...,[CONTOURELE=15000] {...}). My approach was kind of quick and dirty, but it was effective and less trouble than the equivalent GDAL work to create my own contour shapefiles from the USGS 1°x1° NED image files.#countries: The Mapbox default Natural Earth countries layer. The borders aren’t necessary, but I left it alone since #fff was a good background color.You can also download my stylesheet for the 8.5"x11" US Letter-sized version of the map.
By way of some experimentation, I decided that I wanted to start off by exporting a 2250x1683 image at zoom 13
for a -105.7032,39.9082,-105.0983,40.2544 bounding box to produce approximately 270dpi output when scaled
to fit an 8.5"x11" sheet of US Letter paper. I arrived at the somewhat unusual resolution of 270dpi by trial
and error as I attempted to find a combination of font sizes, line widths, zoom level, bounding box, and
export resolution which looked good on paper. Because TileMill doesn’t automatically scale sizes and line
widths as export resolution is adjusted, finding the right combination of sizes and widths was a challenging
process.
For font sizes, I just experimented until it looked good when I printed a draft. Similarly for the 0.05° graticule divisions, I just guessed until it came out right. In this case, “right” means the line spacing in the printed output is narrow enough (one to two inches) to allow using a compass as a protractor to project angles relative to any point of interest on the map. It’s worth noting that increasing the map’s printed size can require finer graticule divisions to maintain a good spacing to match the fixed real-world size of the compass dial.
Once I got the small map working and showed it around a bit, it seemed like the thing to do was make a bigger one. A 20"x30" poster seemed about right, so my next step was to create a 18"x28" map image for printing on a large format printer with a 1" margin. Scaling the map up turned out to be another challenge. I ended up needing to use a bounding box with a different aspect ratio (1:1.5 instead of 1:1.29), a different zoom level (14 instead of 13), a different DPI (600 instead of 300), and differently scaled font sizes, marker sizes, and line widths.
To improve my ability to iterate changes to the style, I wrote aPython
script
to generate CartoCSS. That let me create the final version of the style for 20"x30" and a 600dpi image of the big map. Because of how TileMill handles the auto-scaling math for latitude/longitude bounding boxes and export sizes in pixels, I ended up exporting -105.746,39.8975,-105.024,40.2525 at a size of 16807x10800, then cropping
that image to a final size of 16800x10800 using OS X’s Preview app.
Currently we’re looking at proofs to get a big map printed for some friends in Boulder.
This week, the data team finished adding buildings in San Francisco to OpenStreetMap. Since January, we have added or updated over 152,022 building polygons based on San Francisco building footprint data and Bing imagery.
| User | Total | Added | Updated |
|---|---|---|---|
| ediyes | 62,882 | 59,501 | 3,381 |
| Luis36995 | 61,876 | 36,137 | 25,739 |
| Rub21 | 27,264 | 23,043 | 4,221 |
| Team | 152,022 | 118,681 | 33,341 |
This is an ongoing effort, join us tracing, or post feedback on Github— we’d love to hear from you.
Tatiana is a designer and illustrator who alongside making crazy animated GIFs brings an amazing ability to communicate product.
She is a graduate student from Howest College in Kortrijk, Belgium. Before starting this degree, she completed a Masters in Visual Arts, focusing on Graphic and Multimedia Design at Sint-Lucas School of Arts in Ghent, Belgium. Tatiana is continuing on with Mapbox after spending a semester with us through The Washington Center.
Here’s some of what she’s done so far:
