We're delighted to be participating again in the American flagship OpenStreetMap conference, State of the Map US, as both sponsors and speakers.
Here's the lineup for Saturday:
And for Sunday:
Stamen-sponsored online mapping education group Maptime will also be there, with a lightning talk on Saturday at 5PM, and a Birds of a Feather session on Sunday at 4PM. For the full shebang of what's happening, take a look at the full conference schedule.
See you in DC!
Today marks the official launch of parks.stamen.com, a project designed to highlight social media from parks and open spaces across California, created in partnership with Electric Roadrunner Lab.
Stories pour out of our parks every day. This project is a first step towards visualizing Twitter, Flickr, Instagram, and Foursquare content using the actual boundaries of our parks, so that we can start to understand how people feel about their favorite open spaces. Taken together these stories make plain that parks are integral to the lives of all Californians. They are evidence for the argument that access to open space must be protected'and expanded'for all and that parks need our support. This is also a tool that park rangers, managers, and advocates can use to understand how people are using parks and to connect with their customers and supporters.
The project's original concept came from writer and educator Jon Christensen, editor of BOOM! A Journal of California and his Electric Roadrunner Lab. Jon sees this work as a gift to the parks and park visitors, an experiment about learning who is using the parks and how. It's the start of a conversation about how we use open spaces in this screen-mediated age. Parks, it turns out, aren't just places where you get away from your everyday life and connect with nature (if they ever were)'they're also places of deep social meaning and engagement with others, and this project is a way of taking a new look at how we do that in the age of mobile everywhere. Our hope is that this project helps park rangers and staff to see your stories, and to clearly show how people are using and enjoying parks across California.
Project initiator Jon Christensen leading a workshop with Stamen and parks stakeholders about social media use in California Parks.
After building some initial prototypes, Stamen and Electric Roadrunner gathered colleagues from the Golden Gate National Parks Conservancy, National Wildlife Federation, East Bay Regional Park District, Bay Area Open Space Council, Stephen D. Bechtel, Jr. Foundation, California State Parks Foundation, Latino Outdoors, and Point Reyes National Seashore to review and discuss how a project like parks.stamen.com could help them in their work. It was a really useful day, and we're listening closely for ideas and feedback from parks folks about the project.
If you'd like to contribute to the conversation, here's how to join in:
- Go to parks.stamen.com
- Search for your favorite California park and find the park's hashtag, like #YOSE for Yosemite National Park, or #ALCA for Alcatraz Island.
- Include that hashtag when you share content on Twitter, Instagram, Flickr or Foursquare
Look for the wander
link too. It'll take you to a random open space and hopefully bring you to new parks that you didn't even know existed!
Not in California? Don't have any pics? Wish you had a project like this in your state? We'd still love to hear from you on Twitter, joining the conversation on #caliparks and following @parks_stamen. You can also send us a good old-fashioned email to let us know your thoughts.
Many thanks to Larry Orman and his team at GreenInfo Network for producing the California Protected Areas Database (CPAD), which is undoubtedly the backbone of the project. Thanks are also due to the San Diego Air and Space Museum for letting us use this lovely photo of Yosemite for the homepage backdrop, and to Jamison Wieser from the Noun Project for our handsome arrow icon.
Now go explore!
In late February 2014 MtGox, one of the oldest Bitcoin exchanges, filed for bankruptcy protection. On March 9th a group posted a leak of MtGox data, which included the trading history of users from April 2011 to November 2013. We've been collaborating with Kai Chang & Mary Becica on some visualizations of this data; they're live as of today at http://bitcoin.stamen.com/.
These graphs explore the trade behaviors of the 500 highest volume MtGox users from the leaked data set. These are the Bitcoin barons, wealthy speculators, dueling algorithms, greater fools, and many more who took bitcoin to the moon.
Barons are characterized by their early start in the market followed by big sells at higher prices. Initial trades with many sells suggest the user mined bitcoin before entering the Gox market.
Automated traders can build up a large volume by making thousands of small trades. Vertical stripes of sells across a wide price range may also indicate algorithmic activity.
Glitch in the System
User 15 purchases large volumes of bitcoin at seemingly random prices. Why do so many traders sell at low prices to User 15? Why does User 15 buy at astronomically high prices? Are these faulty trades or an algorithm gone mad?
The mark of the Greater Fool is a lonely green patch where the price is highest. Some of these may be investment groups encouraged by the Bitcoin Senate Hearings in November.
For more visuals (we've mapped the top 500), please see http://bitcoin.stamen.com/. You can take a look at some previous visualizations of markets Stamen has done here and here.
by Seth and Beth
Back in December, we launched a new map for the Golden Gate National Parks Conservancy. The goal was to help people get to the parks and once there, around them, and to create a framework for Parks Conservancy staff, volunteers, and partners to add additional data and content as needed. At first, custom cartography wasn’t even on the list, but in hindsight, it really made the project.
Here’s how it went down:
The project kicked off with a few key goals; at the top of the list was increasing the use of transit to get to the parks. We quickly realized that this constraint meant using something that both was familiar and incorporated great transit data. Stylistically, we wanted to allude to the classic maps from the National Park Service (NPS)–ample terrain, lots of green, and bold black iconography.
By National Park Service [Public domain], via Wikimedia Commons
Google Maps has some of the best transit data, and its usual look and feel isn’t far from that of NPS (not to mention being immediately recognizable due to its overwhelming popularity). Plus, Google provides tools to customize their maps to fit custom color schemes. With all roads leading to Google Maps, that’s the initial direction we set in on.
The Parks Conservancy’s original map interface, which we were hired to redesign.
This assumption was turned on its head, however, when we began to incorporate the Parks Conservancy’s trail data. It turns out that trails are highly entwined with roads, at least in the Styled Map Wizard. Replacing Google’s trail data with data from the Parks Conservancy meant hiding some of Google’s road data, which in no way would help anyone to make their way to the parks. We also realized that by using a Google base map it would be more difficult to specifically highlight areas managed by the Parks Conservancy and that the points of interest (POI) baked into their base layer (some of which we wanted, but not all) distracted from the parks.
This is when we realized that we needed to go custom. There was no other way we could incorporate the variety of datasets from the Parks Conservancy–trails, trailheads, overlooks, parking areas, bathrooms–without doing that clunky, terrible thing where you just pile a bunch of data over a general purpose map and hope the user can just create clarity on their own. *shudder*
Going custom meant working primarily with OpenStreetMap (OSM), our go-to source for free and open source spatial data. There’s a ton of data there, but we were still missing terrain, which was going to be critical in representing the lovely shaded mountainous regions throughout the Golden Gate National Recreation Area (GGNRA). We’d been given copies of some high-res elevation data produced by the ARRA Golden Gate LIDAR Project (a collaboration between the US Geological Survey and San Francisco State University) but realized that processing and using this data would put us way over time and budget. So we went with USGS’s lower resolution National Elevation Dataset (NED) (we also use it for Terrain on maps.stamen.com), which provided the soft, rolling texture we were going for.
A comparison of our map, on the left, and Google’s, on the right.
The end result looks very familiar–similar road coloration and widths–and using the Google Maps API for functionality, it works like a Google map. You might not be able to tell the difference immediately, but we hope you’ll appreciate that all the bathrooms are both clearly represented on the map as well as being routable when you need to find one in a hurry.
As simple as the map looks, we used a wide variety of data sources under the hood:
- OSM, for the transportation network, most place names, and secondary green areas like playing fields and golf courses. We made some edits around the Presidio and Marin Headlands to correct some one-way streets and inaccessible sections of road.
- The California Protected Areas Database (CPAD), for all open space areas (federal, state, county, and municipal parks). We drew these before adding NPS boundaries to provide texture and context without distracting from the map’s primary focus: the Golden Gate National Recreation Area.
- GGNRA areas were sourced from NPS.
- Coastlines and water features were drawn using using data from the National Hydrography Dataset (NHD).
- Transit and Trails provided all of the data for the trailheads and trips (such as Meander in Marin, visible as an overlay), which are curated by users of T&T, including Michael Norelli and other members of the Parks Conservancy staff.
- The GGNPC and GGNRA GIS departments provided trail alignments and names as well as notable features present in the GGNRA (bathrooms, overlooks, cafes, etc.).
- All additional data came from the Parks Conservancy, via their GIS lead (and wonderful collaborator) Michael Norelli. He also sent us the park names, campgrounds, overlooks, restrooms, POIs, trails, and building footprints throughout the GGNRA.
We used TileMill, PostGIS, GDAL, and other tools to combine these datasets into a coherent whole. In order to facilitate updating and repurposing, we created four layers and baked them together using bits of Map Stack. Here they are from bottom to top:
1. The background layer, containing park and protected area boundaries, beaches, and other solid polygons.
2. The processed terrain layer, combining hillshades and slope maps. At 60% opacity, it creates subtle shadows of terrain, indicating the natural landscape without obscuring the features most important to the Parks Conservancy.
3. The feature layer, containing water, the transport network, building footprints, and boundary lines. Land is transparent, allowing the background layer to show through.
4. Labels are rendered separately, giving us the ability to sandwich dynamic data (which we didn’t end up doing) and provide interactivity (using UTFGrids).
Here's how it all stacks up:
In the few months since launch, we’ve had lots of compliments (thank you!) as well as some questions. Many of them were about cartography, and have been answered above (we hope). Here are some more:
Did you have to create your own database?
Yes we did. No, it has not exploded yet, and we have Fastly, Heroku, and Amazon Web Services to thank for that.
With so many data layers, were you able to do any rapid prototyping?
Yes. Once we loaded the data into PostGIS, we used a combination of QGIS and TileMill to explore and style the data. Once we had a rough look and feel, we split the layers out (as above) and used Map Stack to introduce and tweak the terrain layer.
Why not use satellite imagery?
Great question, and we thought about this one a lot. In the end, although the extreme detail would allow for people to see the natural space in great detail, we would have lost the clarity we were going for.
What parts of the project are going to be open source?
Although we’d like for all of it to be, we’d rather purposefully release smaller chunks of documented, organized code than everything all at once in all its chaotic glory. With that in mind, the first things you should look for are:
That's all we can think to tell you about the cartography for now. Have more questions? We'd love to hear from you.
By Eric and Beth, cross posted from Markets for Good
This post is a check on both our ambitions and our processes. The uses of data visualization are different according to whether the goal is to communicate a specific thought for a single moment, e.g. as a poster, or the goal is to provide a durable tool for social change. It should be mighty safe to say that we want the latter, i.e. to take full advantage of the ability to create dynamic, interactive, real-time stories that make data plain and useful. Eric Rodenbeck, CEO & Creative Director, and Beth Schechter, Education and Outreach, Stamen Design offer a fundamental insight to inform data strategy: think about the future – how you will maintain your visualization outputs and capabilities (both human and technical) on a shifting landscape.
The data visualization community is a large, diverse, and growing one. As different as we all are, there is a vein that runs through all of us: earnest pursuit of the truth, love of information, and desire to share it in a beautiful, clear, understandable way. It is from this desire that the data visualizers produce some of their most impactful work, like Periscopic’s U.S. Gun Deaths in 2013, or Hyperakt and Ekene Ijeoma collaboration The Refugee Project. For us, one of these works is Crimespotting.
Crimespotting began as an independent guerrilla project, organizationally attached only to Stamen. We realized that it was important for residents of Oakland – a Bay Area city with a crime-addled history – to have more information about the crime in their neighborhood than just seeing police cars whiz by, sirens ablaze. Former Stamen partner Mike Migurski started scraping the Oakland Police Department’s API and sorting police reports by time, block, and report type. After Chauncey Bailey, a prominent local journalist, was assassinated in broad daylight in downtown Oakland, we decided to make this data public on an interactive map.
Not long after launch, two things happened. First, the City of Oakland turned off our access to their servers, which effectively shut down the project until we were able to connect with the city’s crime data department, who eventually turned into one of the project’s biggest supporters.
Second, the City of San Francisco asked us to create an officially sanctioned version of the project for San Francisco, which we did do. The San Francisco instance was launched in 2009, with Mayor Gavin Newsom at our side.
All of this happened over half a decade ago. In the years that followed, the project apexed with tremendous impact and support – including coverage in the New York Times and this video with Hans Rosling. But over the years, the project started wavering. Oakland’s API has sputtered to the point of being nonfunctional, rendering Oakland Crimespotting totally spotless. (see below) Although the San Francisco version has fared slightly better thanks to Stamen partner Shawn Allen and Jeff Johnson at the SF Department of Technology, it’s also broken several times. Only in the past couple of weeks have Shawn and Jeff found time to work on fixing it amid a medical leave. If not for these volunteered efforts, the San Francisco version would be as comatose as Oakland’s.
Watching the static nature of this project play out is painful, as is answering countless emails asking about why they are broken and when they will be fixed. We want to say that it will happen soon, but we know that reality dictates otherwise. We also know that it’s no longer acceptable to tell the public, “Sorry, it’s just that the code is creaky and the database is full.” We’ve come a long way since 2007, and the public expects better. They expect it to just work, and rightfully so.
I tell you this story because at this point it’s as archetypical as [a damsel in distress]. Too often we build works like these, only to see them falter and fail as browsers upgrade and technology evolves.
If you build a bookshelf, you take the time to design it once, to build it once, to finish and install it once. Dynamic data visualizations and other Web-based works are not quite the same. They’re more like plants, sprouted from the seed of an idea. Data visualization in particular also has a beautiful blossoming to it, one that happens naturally in response to the data, illustrated as pixels and color.
If you plant a flower in a garden and then never give it water or light, it will in fact die. Unless, of course, it happens to placed in just the perfect spot, in which case it will need to be pruned. Either way, some kind of tending is always required.
We don’t always think of digital works in the same way, perhaps because their metaphor of creation more closely resembles that of a built object, like a bookcase or building. But even buildings need maintenance, and after so many years, the shelves on the bookcase may falter and need new ones. We need to be more conscious about this aspect of dynamic data visualization, at the outset.
I urge of all our clients, in particular those who are making works for the public (which is most of them), to consider plans for maintenance. Luckily a lot has changed since 2007, and now more of our clients have some kind of web or technology team to take this work on. It’s part of their operating strategy. Clients in the nonprofit and municipal centers typically do not have those kinds of resources, and if they do, they are usually limited. What’s troubling is that these are the clients typically commissioning some of the most socially relevant work, yet their funding models typically only call for the build, and nothing beyond that. Nonprofits have the advantage of being able to fundraise (which is a TON of work), whereas governmental departments must rely on strict, slow process and very limited budgets.
If you are one of these bodies and you want to make socially relevant work, then we urge you too to think about how these works will live beyond the build and to come up with a plan (or at least funding model) for how it can be maintained. If not, all that work and money and time is going into something which is sadly, inevitably doomed. It’s not enough to visualize data, or to make it public: as data visualization moves from a flashy experimental genre to one that the public relies on, we need to come up with solutions that let them grow and change over time—to take the time to water and prune, just like we do our gardens.
We're pleased to announce a new project for the Golden Gate National Parks Conservancy. We've redesigned and built a new map, and trail visualizations to help people get to the parks in the Bay Area.
Since 1981 – in partnership with the National Park Service and Presidio Trust – this local non-profit has provided over $250 million in support to the Golden Gate National Parks, rallied more than 250,000 volunteers, pioneering innovative park stewardship and education programs, like this art installation on Alcatraz featuring Ai Wei Wei.
Earlier this spring, the Parks Conservancy reached out to us to help with a new initiative: creating a beautiful map to help more locals (and tourists) get outside and into the Golden Gate National Recreation Area, the nation’s largest urban national park, and to make it easier for Conservancy staff to create new maps and events on the website.
Part of our remit was also to build on existing efforts within the Conservancy wherever we could. For example, the Conservancy already works with Transit and Trails, which connects people with the trails in the Bay Area and beyond. We use their trail database to power a new curated trails page. Their data folds into the new map, along with an events calendar, locations and links for partner programs within the parks, and more.
We redesigned the "Big Map" from the ground up, using data from across the web. Sources include the Parks Conservancy, Presidio Trust, San Francisco State University, California Protected Areas Database, Transit & Trails, OpenStreetMap, the United States Geological Survey, and the National Parks Service. Phew!
Here's what it looks like:
We had fun one day making sure all the overlooks pointed in the direction of their respective views:
We've also deployed our handy "make the URL as dynamic as possible" to enable all sorts of new deep-linking, like, straight to this trailhead at Dias Ridge:
There are also "Little Maps" sprinkled across the site. In addition to making them gorgeous, we worked with Parks Conservancy staff to streamline their ability to make new ones for new events or other content.
There's a new Trails page too, designed to help you see what a hike is like before you're up the mountain. We've launched with a starting list of some 20 trails, and we've built a streamlined data pipe from the Transit and Trails system straight into parksconservancy.org. (The end game here is loads and loads of trails and trips created by friends of the Parks.) We like how you can move your mouse over either the elevation profile (above) or the trail on the map to see where you are.
Say you wanted to go and do this hike, you can feed it into the new Trip Planner we've built too. Wherever you see a "Get Directions" link, hitting it will feed you straight into the trip planner. By the power of teh Googles, we can grab directions for you in a jiffy.
Throughout the project, we’ve been genuinely delighted with the amount of interest and effort of various groups around the Bay to protect and enhance our open spaces. Workshops and conversations with folks from the Parks Conservancy, the National Parks Service, and the Bay Area Open Space Council (many of which include volunteers as well as senior and junior staff) have given us tremendous insight into the work of this network of talented, passionate people. These people work tirelessly to protect and preserve natural open spaces in California, and it’s a pleasure to be able to provide work that will help them in this mission.
Our hope is that the work doesn’t stop here, and we don’t think that it will. For one, we’re crossing our t’s and dotting our i’s on a few new open source tools that we created during the project, which we'll post about once we've gotten the their READMEs in good shape.
Future potential definitely calls for much more input, stories, and content from Conservancy staff and volunteers. Our favorite part of this job (aside from designing the lovely new cartography) was learning about how so many different people feel about and use open spaces near them. Some of our other projects this year have circled the Great Outdoors theme too, and it's fun to think about how the work and thinking could dovetail later on. (More about that later!)
When I first discovered Pinterest about two years ago, my heart exploded and my mind was blown in the best possible way. One simple interface allows me to visually browse all of the beautiful stuff I find on the internet and beyond, and to organize it how I please. It feels friendly & welcoming—a place where I know I’ll find good things to look at and that I carefully put things I want to use later.
So you can probably imagine the heart-explodiness that’s rolling through my corner of the studio this evening, with the release of Place Pins, featuring a beautiful new map designed by none other than us! Place Pins let you map the things you love, near and far, making the pins more actionable and bringing out the explorer in all of us. You can view and create these Pins on your desktop or on mobile, when you’re actually out and about exploring. You can also collaborate with friends and family, using it to plan your next vacation or a tour of your favorite architecture.
Making a map fit for this kind of activity was a fun one. Pinterest loves color and texture and a feeling authenticity, all of which you might find in a paper map. Our house style, to the degree that we have one, tends to veer towards the bright and sparkly, and this design challenge was the perfect opportunity to break from our mold and try something new. Which we did, using rice paper texture, subtle color washes, and a mixture of unicode and hand-drawn fonts. We’ve also added some extra touches, like using OSM ids to introduce just a bit of entropy into the angle of all of the place labels to introduce some variety and get away from the hyper-precise default modern way that these things tend to settle towards. If you look carefully you'll notice that the spacing of the letters on street labels varies a bit from road to road. This is an intentional gesture towards making maps more human. The result is a map that (we hope) has a bit of soul and variety to it, not just another one-off, and is just asking for pins to be put all over it.
I’m also pleased to announce that for the first time we’ve shifted the backend infrastructure burden of one of our projects to that developed by our colleagues at Mapbox (you can read their take on all this here). The whole process of getting this thing online and polished was incredibly smooth and hassle-free, totally different from the wailing & gnashing of teeth that historically has accompanied the release of our worldwide maps. Honor is due to those guys for solving a hard problem and for making it possible for this kind of project to flow smoothly. I’ll follow up in a separate post about some of the finer details we included in the project and some ways that I think things could get even better.
All in all, we’re delighted to have been asked by Pinterest to participate in this project, and we hope the results are to your liking. Let us know what you think, and we hope you’ll share your maps with us and others. And happy Place Pinning!
Here's the city view of Amsterdam. At this particular zoom level, the small details of roads and buildings amplify the textures that are being used for land and water.
The Bay Area. At this zoom level, we start to see the emergence of parks, as well as major roads. These elements, along with the textured waterways, reveal many layers of detail that work together quite beautifully.
The street level view of Boston is shown below. Here we see a nice combination of road labels, buildings, parks and waterways.
At the country level, a large portion of Europe is captured in this image. The forests become visible, giving the landscape another layer of texture.
Karlsruhe, Germany. At this street view, we see several detailed components, such as parks and foot paths, rail lines and building density.
Hong Kong captures one of our main design goals with the Pinterest project. The "hand-crafted" look and feel is quite evident with the contrast of textures, especially where the water meets the land.
Manhattan and the surrounding boroughs. Like the image of Amsterdam, this zoom level captures several detailed elements - roads, highways, waterways, buildings and parks.
"In September 2013, students in Webutuck High School art classes participated in a mapping workshop where they made maps of their lives--things they did, things they liked, things they didn't like, and things they'd like to see. They drew the maps on Field Papers, which were scanned, edited, and turned into geotiffs and markers. This is what they look like all together."
"Thanks to The Wassaic Project, Mr. Fitz at Webutuck High School, and Stamen for making Field Papers, seriously.
Maps and kids drawings FTW!
The Humanitarian OpenStreetMap Team (HOT) has been doing incredible work in coordinating the mapping the parts of the Philippines affected by Typhoon Haiyan / Yolanda. I encourage you donate to support their important work here. Our Field Papers project is seeing active use in this effort, with 256 atlases made in the Philippines as of this writing. You can contribute to the project starting here.
At Stamen we use OpenStreetMap data in most of the maps we make, including our Watercolor, Toner, and Terrain map tiles. OpenStreetMap is a rich and growing dataset that has been created and maintained by hundreds of thousands of volunteers around the world, and at Stamen we wouldn't be able to do what we do without it.
But it can be hard to visualize the immense amount of work that goes into building and refining a complex dataset like OpenStreetMap. As part of my dissertation research at the University of British Columbia—research that feeds into the work I am doing here at Stamen—I have been looking at the historical OpenStreetMap data to see how the project has grown and evolved over time.
To this end, I created some visualizations of historical OSM data called OpenStreetMap: Every Line Ever, Every Point Ever
The first map, "Every Line Ever", starts from a simple premise: draw every version of every linear feature present in the OpenStreetMap historical data, even if those features have been subsequently deleted. Each line is drawn at 1% opacity, such that areas where multiple linear features are present or where multiple versions of a single feature exist, the lines drawn on the screen will accumulate to produce a darker and darker mark. The result produces a map that is strikingly familiar and readable: freeways appear more prominent than city streets, which are in turn darker and more visible than alleyways. However this hierarchy is not derived from any attributes associated with those features; rather, the hierarchy emerges naturally through the cumulative traces of OSM contributors modifying and refining the map. Inevitably, the features that are important to more people are edited more often, thereby becoming darker traces on this map. On further inspection, it is possible to see how the ghostly initial sketches of some features gradually coalesce into thicker, sharper lines as the collective effort of OSM volunteers settles around a consensus.
Here is the same approach, applied to London, England, where the OpenStreetMap project began:
The second map, "Every Point Ever", follows a similar approach, but using the point features from the OSM history database. In this case, every version of every point is drawn on the map at 1% opacity, but in this map the points are also scaled according to their version number. Thus, a point that has been edited a dozen or even a hundred times will be drawn again and again on the map, represented as an increasingly larger circle. Points that are continually modified in the OSM database will appear to "bleed" onto the page in this map. Where the first map evokes the spidery traces of pencil drawing, this map appears more like a collection of inkblots. Both maps use these metaphors of hand-drawn illustration to reveal the historical traces of effort that normally go unseen when looking at a finished map.
Be sure to try out the interactive version at http://graphspace.com/every-line-every-point which allows you to zoom in and see more detail.
I'm also delighted to say that this project won first place at UC Berkeley's map exhibit called "See-Through Maps: Maps that lay bare their point of view", which was part of the Mapping and its Discontents symposium hosted by the Global Urban Humanities Initiative. Please take some time to peruse the other maps in the exhibit; you'll find a wide range of innovative and beautiful maps, and I was proud to present Every Line Ever, Every Point Ever alongside them.
Most maps of sea level rise are underwhelming, visually. By focusing on the land that's shrinking as sea levels change, they give the impression that there's lots of land left over, even after the oceans change the shape of the coastline.
Climate Central's new Surging Seas project (available in New York and New Jersey to start) turns this issue around by placing the visual emphasis not on the land that's left over, but on the land that's lost as the ocean rises. Ten feet sounded like an unrealistically high number when we started the project, but Sandy's storm surge of 13 feet changed our minds pretty quickly.
New in this version is the introduction of two new datatypes, also emphasized according to the level of sea rise: population density and social vulnerability. So in this view of Manhattan and eastern New Jersey, you can see that the Lower East Side, as well as Jersey City, both have a high number of people who'll be affected by the change:
In sharp contrast to one another, though, the Lower East Side contains a high number of socially vulnerable people, whereas in Jersey City people are generally less unprotected (the yellow bits near the harbor):
Here's what the Rockaways look like as sea level rises in high- and low-population densities near the beach: