tecznotes

If you need to make a bag of polygons from a selection of OpenStreetMap data, you would think that simply running shapely.ops.polygonize on the selection of linestrings is enough. In fact, polygonize needs for the line endings to coincide, and may not work as you would expect with OSM data. I scratched my head over this a bit after successfully using polygonize to handle TIGER data, until it occurred to me that TIGER is built to have lots and lot of little lines.

The trick is to split each linestring input to polygonize() into all its constituent segments, and then let the function do the reassembly work for you. Creating the polygons of Amsterdam above from metropolitan extract roads took just a few seconds. Here’s the polygonize.py script that does it, expecting GeoJSON input and producing GeoJSON output.

Hachures are an old way of representing relief on a map. They usually look a bit like this, and they’re usually hand-drawn:

I’ve been playing some some simple algorithmic ways to generate hachure patterns with input elevation data.

They’re rather New Aesthetic, with the regular-spaced grid based this pattern that encodes slope and aspect together:

You can align the marks with the slope, or across it (as with contour lines). The latter results in some pretty blocky-looking hills; my feelings about these are mixed:

I especially enjoy the smooth appearance of hills in San Francisco using the orientation along the slope. Things get even more interesting when minimal labels are added on top:

Also, good things happen at relative-low zoom levels, where the relative size of hills and marks gives everything a spiny, written-on appearance:

Have a look through a collection of renders for more examples.

Next weekend, I’m heading to Chicago to spend a week volunteering for the Obama 2012 campaign’s tech team. I’m very excited; it should be a fairly high pressure environment and I hope to have a number of opportunities to bring a bit of API design and basemap cartography love from San Francisco.

This election feels intuitively like the one that matters, the one where we prove that the past four years weren’t just a reactionary fluke. We had a round of flowers and sunshine last time around, but the President wasn’t running on much of a record. In 2012, he’s been in office for a full term, and a lot of people who were hoping to see a 180° turnaround from the Bush years were disappointed to discover that ours is a rough political landscape to navigate. Given the circumstances, I think Obama’s done a great job. Given the risk that supporters from 2008 might not be so excited this time around, I’m putting in extra energy to help assure that we can push this not-at-all-guaranteed election over the hump.

If you’re local to San Francisco and want to help, Catherine and Angus at the SF technology field office in SOMA are looking for your help.

We launched a thing last week. It was fairly well-received by people on the internet. A few people at Stamen who don’t normally write on the company blog wrote on the company blog: Zach talked about the blur/noise process behind the watercolor tiles, Geraldine explained all the work that went into the textures, and Jeff showed off some of his work logging tile usage on the site. I recapped a lot of my background work on Terrain, and then Cups And Cakes Bakery went and made it into cupcakes.

Paul Smith, who taught me how to install Mapnik a long time ago, did an interview with me about maps while slacking off from his day job. In it, I wrote a bunch of things that I think are interesting about online maps, which is a good thing because today I didn’t feel well and bailed on my Where 2.0 talk. Sorry about that—you didn’t miss anything, I was really unhappy with the talk I had prepared, which probably contributed to my morning.

Here are pictures:

With some help from Ryan and Tom, I’ve been wrapping my pea-sized brain around WebGL. I’m doing my usual start-from-the-bottom thing so it’s been a great exercise in understanding a programming paradigm built around static lists and buffers. I’ve worked like this before, but not extensively and not with a render output this smoking fast.

It’s all simple stuff so far, but I’m chasing two ideas: using WebGL for simple 2D output with an added speed bump, and driving it from SVG or the HTML DOM. None of the examples below will work unless you’re using a current WebGL-compliant browser, which for me was Chrome 17.

The elephant is me figuring out the basics of viewport transformations that match pixel positions, image textures, and simple animation passed via vertex buffers:

The monkey is a test to see how many things I can throw around on a screen without sacrificing framerate, as well as some sanity checks on coding style. Turns out, the answer is “lots”. Interesting things happen with this one when you switch to and from its tab; I’m using a basic timeout-based mechanism for the little face particles, and it clearly falls into a regular rhythm.

The unicode patterns (borrowed from Sarah Nahm) are governed by an invisible D3 force layout, and are a test of synchronization between multiple “programs” and driving a visual effect from a geometric layout. Also additive blending for punchiness. Try dragging the boxes:

These are some of the resources I’ve been using to get up to speed:

• Learning WebGL
• OpenGL Shading Language wiki
• CAAT implementation notes
• Mozilla Developer Network (with best practices)
• Raw WebGL from Opera

I’m still not totally comfortable with the programming approach of maintaining collections of static lists in preference to objects and other data structures, and I’ve been avoiding three.js until I can get comfortable with how WebGL works for simple, two-dimensional graphics. No lighting effects or spinny statues quite yet.

I’ve been playing with ways to represent U.S. OSM involvement at the county level. This is in part spurred by some of Thea Aldrich’s work since the last State Of The Map U.S. as well as by Martijn Van Exel’s Temperature of local OpenStreetMap Communities. The county-equivalent is a basic unit of administrative power, a common baseline for Census demographic statistics, often home to GIS professionals, and guaranteed to cover any given piece of land in the United States. It’s a great way to divide a dataset like OpenStreetMap, so I’ve started to experiment with useful print representations of counties for looking at map coverage.

(PDF download, 21MB)

The visual design is rather primitive so far, with just three maps on a single tabloid printout as a quick test. At top is a basic representation of OSM coverage, a sort of “what do we know” for streets. Next is a map of TIGER/Line status, highlighting streets which remain untouched since their initial import in 2007 and probably overdue for review. Finally, a map showing recently-edited streets, which looks a little more interesting the Austin, Texas render. Each is rendered using Mapnik and Cairo’s PDF output from a recent OSM Planet extract.

There are intentional echoes of Newspaper Club’s Data.gov.uk Newspaper here.

My afternoon test prints suggest a few things:

• Printers have a very hard time with fine linework, so I’m switching to halftones for the smaller maps.
• I need to get many more layers of information in there, including buildings, parks, points of interest, etc.
• Maps will look better when printed large.
• I should do a newspaper run like Grassroots Mapping did recently, the output looks great:

Code can be found in Github under CountyOSM. You are not expected to understand it.

A mail from OSM Board member Richard Fairhurst, to the OSM-Talk mailing list about Apple’s recent use of our data, with links added for posterity:

• 3500 tiles per second. Seriously. In Grant’s words on Twitter: “Massive jump in #OpenStreetMap traffic due 2 Apple news: t.co/nB4ffgYy Fighting fires 2 keep systems up”

• switch2osm.org fell over. Yep, so many people wanting to find out about switching to OpenStreetMap that WordPress crapped itself (ok, not the hardest target but hey ;) ).

• More contributors. We’ve had people come into IRC saying “I want to fix this park name, how do I do it?”. Regular IRCers have been reporting a noticeably greater number of new editors in their areas. Or as someone just asked on IRC: “hmm did the apple fanbois drink the OSM koolaid and crash our servers with zealous mapping?”

• I think we’ve had a higher peak of publicity today than we’ve ever had —higher than the Foursquare switch even, or the Google vandalism incident. We’ve been Slashdotted; we’re #6 on Hacker News. We’ve been on The Verge, Forbes, Wired, Ars, Gizmodo, and all the Mac sites—that’s taking OSM to people who’ve not heard of us before. We might not be the front page of the New York Times yet, but we’re getting there!

• And one of the best things has been that people like how we’ve handled it. From Forbes: “OpenStreetMap itself has been much more polite about the whole thing. ‘It’s really positive for us,’ OSM founder Steve Coast told Talking Points Memo, ‘It’s great to see more people in the industry using OSM. We do have concerns that there wasn’t attribution.’.”

  From a comment at Hacker News: “While I think it’s quite messed up that a company as rich as Apple can’t abide putting credits for people who have put some really good work in (I’ve even made small updates to OSM in my time) I do think that this is a very classy move by the OSM people, no ranting blog post or ‘Apple stole our stuff’, welcoming people presents a much better image of the project.”

  Or The Verge: “Granted, OSM took this as an opportunity to get in the public eye by piggybacking on the iPad’s media fanfare; I applaud them for their maturity in their statement though. Many companies would’ve latched onto this and unleashed the lawyers threatening this and that, but they chose to be civil, point out the missing attributions, and say they are ‘we look forward to working with Apple to get that on there.’ A little civility goes a long way (in my book). I’m quite sick of the mudslinging in this space.”

Thanks to everyone who’s put the hours in today, to all the coders and sysadmins who sweat blood to not only keep OSM running but make it easier and faster... and to every single mapper making a map so amazing that everyone wants to use it.

cheers
Richard

I am kinda losing my mind over this hour-plus ambient audio/video construction by Goto80 and Raquel Meyers:

Press play, go fullscreen and lie down. 2SLEEP1 is a 66-minute playlist of audiovisual performances in text mode, designed to make you fall asleep. Made by Raquel Meyers and Goto80.

The first and fourth tracks are especially genius.

Webkit size profiles of a few sites I visit, ordered from smallest to largest.

Metafilter: 0.2MB

Metafilter’s front page is probably my most-visited and most-interesting thing. It’s a wall of solid text and not a lot of images. Still, the volume of actual content is smaller than the volume of javascript, which itself is about 80% jQuery (minified). It’s not immediately clear to me what jQuery is doing for Metafilter.

Google Homepage: 0.5MB

I don’t actually visit Google.com much and I typically have Javascript suppressed for the domain when I do, but the default experience looks like this: half a megabyte, 60% of which is a single .js file clocking in at 300KB.

OpenStreetMap: 0.64MB

The bulk of OSM’s Javascript use is taken up by OpenLayers, an epic bandwidth hog coming in at 437KB minified. You can build custom, minified versions of OpenLayers with just the features you want; I’ve never successfully gotten one below 250KB. Based on my experience with Modest Maps, I think it should be possible to get the core functionality of OpenLayers across in 100KB, tops. The next 100KB of Javascript on this site is a minified archive of Sizzle and jQuery. The remaining 16% of the bandwidth for this page is the visible map and all other content.

New York Times: 0.76MB

The Times is a toss-up depending on when you’re looking at it; I just reloaded and saw the overall size jump to 1.4MB, then reloaded again and saw it drop to 0.5MB. It’s the front page of a major paper, so the ratio of actual content (text and images) to code and stylesheets looks to be in the 2 or 3 to one range, which is decent.

Github, My User Page: 0.99MB

I spend an inordinate amount of time on Github these days. It’s balanced heavily toward code and stylesheets, with about a three-to-one ratio of framework to content. Github’s Kyle Neath has an excellent presentation on responsive web design where he shows how despite the heavy load of Javascript and CSS used in Github’s interface, the all-important “time to usable” metric is still pretty fast for them. He contrasts this to Twitter, which… ugh, more on them below.

My Home Page: 1.1MB

Here’s me; essentially 100% Actual Content, mostly images. I switched to big, stretchy images a little while back, and I’ve gotten more free with the sizes of things I post.

The Awl: 1.36MB

Page sizes take a sharp upward tick here. Most of The Awl is Javascript, though it appears to be largely custom with the usual slug of jQuery sitting in the middle. A majority comes from widgetserver.com and ytimg.com, so I’m going to guess it’s lightboxes and ad server junk.

The Verge: 7.4MB

Lots and lots of pictures. So many that after a minute or two, I wondered whether something had gone wrong with my network connectivity. Below all the images, there is 300KB of minified jQuery, thanks to the inclusion of jQuery UI. Also, 244KB of fonts which in Safari prevents any text from loading until this item is done.

A Single Tweet: 2.0MB

Twitter allows you send 140 characters in a tweet, which (when you add entities, hashtags, and all that) ends up in the 4KB range as represented in the JSON API. 140 is what you see, so I’m going to go out on a limb and suggest that a single tweet page on Twitter has about a 15,000-to-one ratio of garbage to content.

I get links to tweets by mail, etc. on a regular basis, and the aggressive anti-performance and apparent contempt for the web by Twitter’s designers is probably the thing that gets me most irrationally riled-up on a daily basis. How does this pass design review? Who looks at a page this massive, this typically broken and says “go with it”?

It’s mind-boggling to me that with the high overlap between web developers/designers and iPhone users on AT&T’s network, there isn’t more and smarter attention paid to the sizes of the things we’re slinging around the network. The worst sins of the Flash years are coming back with a vengeance, in the form of CSS Frameworks and the magic dollar sign. There has seriously got to be a better way to do this.

Last week, I finished up my four-part class at GAFFTA on visualizing and mapping data. For day three, I chose Mapbox’s TileMill to teach basic cartographic techniques such as choropleths and managing data from OpenStreetMap. I’d never really used TileMill in anger, and teaching the class was an excellent opportunity to apply experience with Mapnik and Cascadenik to a tool built for normal humans to use. I can report that TileMill is a champ. It’s not often that advanced nerd tools are adapted for civilian use, and the group at Development Seed have done an amazing job of packaging the Mapnik experience into a credible desktop application for easy cartography.

Meanwhile, Tile Drawer is now over two years old, and the stars are aligning for a revisit. I’ve substantially updated and modified Tile Drawer for the end times, and I’ve been retooling the creation process to address two questions that TileMill raises: how do you get data from OpenStreetMap in to begin with, and then what do you do with your tiles when you’re done? MapBox answers the second question with their various hosting plans, but what if you want to serve maps for areas larger than a single MBTiles files can handle or you simply want to be ready for the kinds of futures envisioned by Maciej Cegłowski or Aaron Cope?

I’ve been slowly and quietly answering the first question by building up shapefile exports for my Metropolitan Extracts service, and I’m happy to announce that it now includes Imposm and Osm2pgsql shapefiles for every extracted area. Oliver Tonnhofer’s Imposm is particularly well-suited to use in Tilemill, with its thematic division of OSM data into thematic layers.

If you want to use OSM data in Tilemill, and you’re interested in one of the 130+ extended metropolitan areas I’ve been supporting in the Metro Extracts, then you should be good to go with the zip files available there.

Now, about that second question.

I’ve generated collections of data in specially-named shapefiles for four sample metro areas:

• San Francisco (just osm2pgsql, just imposm)
• London (just osm2pgsql, just imposm)
• Berlin (just osm2pgsql, just imposm)
• Tokyo (just osm2pgsql, just imposm)

If you use these files with their names unchanged in TileMill and supply a zip file of your exported Mapnik 2.0 XML stylesheet to Tile Drawer, it will be able to figure out what PostGIS tables you might mean and render a map accordingly. If you want a map layer for all of Texas, it would probably take too long to render the entire set of tiles using TileMill and too long to upload it all to MapBox. Instead, you can start with a sample city above, create a custom cartographic treatment in TileMill, and then provide Tile Drawer with a bounding box for the entire state and a copy of your stylesheet. I’ll be documenting this process on the site soon for more information.

Looping back around, Tile Drawer is useful for TileMill even if you plan to use Mapbox for hosting. One of the last things that Tile Drawer does after importing a data extract is to generate the same collection of Osm2pgsql and Imposm shapefiles available in the sample selections above, so you can prepare data for your own use by setting up an instance of Tile Drawer, waiting for it to finish importing data from OpenStreetMap, and then downloading one of the osm-shapefiles zip files found in /usr/local/tiledrawer/progress.

I’ll be teaching a four-day class at the Gray Area Foundation For The Arts next month, Visualizing and Mapping Data. It’ll be a four-parter, Tuesday and Thursday evenings at GAFFTA’s San Francisco space. I’ll be covering mapping from both a browser and server perspective, focusing the presentation of data.

Go sign up!

Here’s an early draft of my class notes; these will change but not substantially:

This four-day workshop will follow the lifecycle of data, from its raw collection to preparation and presentation for the web. We’ll explore where geographic data originates, how it’s transformed to work online, how to see it flow and move, and finally how to publish a view into that data to the web with simple browser-based tools. We’ll work with data from Twitter and OpenStreetMap, push it through filters and viewers, and publish it to the open web.

This class will cover both browser-side Javascript code and server-side Python code.

Week One: Foregrounds

Meeting 1: Getting dots on maps

We’ll be working with street-level data for the duration of the class, so we’ll start here with some introductory concepts like interactive slippy maps and image tiles. We’ll take Google Maps apart into its component pieces to see how they work, add a selection of point-based data to a map, and finish up with a working example using freely-available Javascript mapping tools.

Meeting 2: Where data comes from

Data can come from all kinds of sources, and frequently it needs to be processed, cleaned, and prepared for use on the web. Become self-sufficient in making location data useful to others. We’ll look at local data sources like 311 calls, addresses, and demographic information and run them through a variety of tools to make them ready for online publishing.

Week Two: Backgrounds

Meeting 3: Choosing your own background

Commonly-available road maps designed for displaying driving directions or finding business addresses don’t always work in combination with arbitrary or complex data. We’ll look at alternate sources of street-level cartography and talk about the ways each might be appropriate to different data sets. We’ll finish up with a dive into the OpenStreetMap data set and the process of designing your own custom cartography.

Meeting 4: Spatial data

Dots on maps are just one of many ways to display data. Heat maps, for example, can be used to show characteristics of large areas of data such as zip codes or census tracts using color. We’ll look at ways to prepare heat map layers and integrate them with our other maps, and finish up with advanced topics like aerial photographs and raster data.

I’ve been kicking some files from the new Nokia 3D WebGL maps back and forth with Ryan Alexander, and my attempts to pick out the geometry are starting to get some results.

Nokia’s texture files:

My points in those same files—a visual match!

Dumping a bunch of X, Y, Z’s into Mac OS X Grapher.app:

Ryan pushing the whole thing into Blender:

This model is actually two meshes, corresponding to two separate textures:

The first one looks a bit like a post-Tornado city. Now to figure out the mipmaps in the height lookup tables.

Nokia’s new 3D WebGL maps are done very nicely. Here’s my house:

Here’s the zoom=16 texture JPEG for the are around my house:

And here are parts of the raw geometry for the same area. I'm thinking to do as Brandon Jones did and figure out the file format here, since I can already see obvious signs of four-byte floating point values:

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...

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...

00023250  08118916 08119d00 86115400 05118611  ..........T.....
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00023290  8f160711 8a160711 54008b16 8a165400  ........T.....T.
000232a0  05119c00 9b008916 88169c00 89169c00  ................
000232b0  05118916 05110711 8f168916 07110611  ................
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These tracks:

1. were added to iTunes in 2011,
2. and listened to a lot.

I do these each year, lately. Also: everything as an .m3u playlist.

1. Kanye West: Runaway feat. Pusha T

It’s actually a bit embarrassing how much I listened to this album overall. Runaway, All Of The Lights, and Lost In The World are all amazing tracks, and it all hangs together amazingly.

2. Los Fabulosos Cadillacs: Matador

My roommate in college loved this.

3. Skinny Puppy: Worlock

Rabies (produced by Al Jourgensen) is one of those early-guitar industrial albums balanced right on the edge of dance music.

4. Elbow: Grounds For Divorce

I think this was in Burn After Reading.

5. Paul Simon: The Boy In The Bubble

This year was the 25th anniversary of Graceland. I grabbed a copy, and still remembered all of the lyrics to every song.

6. Skeeter Davis: The End Of The World

7. Adele: Rolling In The Deep

Ubiquitous, amazing voice.

8. Jay-Z: Dirt Off Your Shoulder

Why did I never pay attention to this album when it came out? Dirt Off Your Shoulder is the track from the “milk” studio video with Timbaland.

9. Blamstrain: Ei Voi Olla Tanssimatta

Thanks, Ryan!

10. Technotronic: Pump Up The Jam