The temperature on a hot summer day in a single city can vary by as much as 11 degrees Celsius depending on where you are—whether you’re near green spaces that cool down the surrounding areas, or pavement and concrete, which absorb heat and radiate it. That’s the heat island effect, and mapping it is the focus of a project led by Portland State University researchers, funded in part by NOAA, and conducted by on-the-ground volunteers who have been taking temperature measurements across a number of U.S. cities. Those measurements have been cross-referenced with other data about the neighbourhoods, which will help cities figure out how to keep their citizens cool during heat waves—which, let’s face it, are going to be a lot more common going forward. National Geographic, New York Times.
Facebook’s AI tool has added some 480,000 kilometres of previously unmapped roads in Thailand to OpenStreetMap, BBC News reports, but some local mappers have been complaining about the quality of those edits, and the overwriting of existing edits by Facebook’s editors: see OSM Forum threads here and here. In particular, see OSM contributor Russ McD’s rant on the Thai Visa Forum:
What Facebook fail to state is the inaccurate manner in which their AI mapping worked. The OSM community in Thailand had for years, been working slowly on mapping the Country, with the aim of producing a free to use and accurate map for any user. Information was added backed by a strong local knowledge, which resulted in a usable GPS navigation system based on OSM data. Main road were main roads, and jungle tracks were tracks.
Then along came Facebook with its unlimited resources and steamrollered a project in Thailand with scant regard for contributors … sure they paid lip service to us, with offers of collaboration, and contact emails … but in reality, all our comments went unanswered, or simply ignored.
Sure, their imagery identified roads we had not plotted, but along with that came the irrigation ditches, the tracks though rice paddies, driveways to private houses, and in once case, an airport runway! All went on the map as “residential roads”, leaving any GPS system free to route the user on a physical challenge to make it to their destination.
Local users commented, but the geeky humans who were checking the AI, living thousands of miles away, having never visited Thailand, just ignored our comments. They would soon move onto bigger and better things, while sticking this “success” down on their resume.
Sounds like another case of local mapping vs. armchair mapping and automated edits, where local mappers are swamped and discouraged by edits from elsewhere. [Florian Ledermann]
Previously: OpenStreetMap at the Crossroads.
An incident of map vandalism roiled the Internet last week. Users of several online services, including CitiBike, Foursquare and SnapChat, discovered that New York City had been relabelled “Jewtropolis” on the services’ maps: see coverage at Gizmodo, Mashable and TechCrunch. The problem was quickly traced to Mapbox, which provides maps to these services. Mapbox, understandably upset about the act of vandalism, soon figured out what the hell happened.
The problem was traced to OpenStreetMap, one of Mapbox’s data sources. On August 10 an OSM user renamed a number of New York landmarks, as well as New York itself, after a number of alt-right and neo-Nazi memes. The edits were quickly reverted and the user blocked—on OpenStreetMap. They nevertheless entered the Mapbox review pipeline, where they were, in fact, caught and flagged on the 16th, but a human editor mistakenly okayed the renaming of New York to Jewtropolis. A simple human error, but with a delayed fuse: the edit turned up on Mapbox’s public map two weeks later. When all hell broke loose on the 30th, the map was fixed within a few hours.
Vandalism of online maps isn’t a new thing: in 2015 Google ran into trouble when a series of juvenile map edits exposed the shortcomings of the Map Maker program’s moderation system and led to a temporary suspension of Map Maker (it closed for good in 2017) and an apology from Google. Anything involving user contributions needs a moderation system, and OpenStreetMap and Mapbox both have them. But moderation systems can and do still fail from time to time. (That’s a take on this incident that isn’t on Bill Morris’s list.)
Brian Tomaszewski writes about his project to train Syrian refugees in the Zaatari refugee camp in Jordan to map the camp. “They have intimate knowledge of the camp’s layout, understand where important resources are located and benefit most from camp maps.” Over 18 months his team trained 10 refugees basic concepts, field collection techniques, and how to map with mobile phones. “Within a relatively short amount of time, they were able to create professional maps that now serve camp management staff and refugees themselves.” His team is now working on obtaining GIS certifications for some of them. [Leventhal]
See also “GIS for Refugees, by Refugees,” an article Tomaszewski wrote for the Summer 2017 issue of ArcNews.
When I started contributing edits to OpenStreetMap in earnest, I couldn’t help notice certain idiosyncrasies in its tagging: for example, there was a tag for brothels, which I didn’t need to use, but there wasn’t one for daycares, which in Quebec there are rather a lot of. That seemed odd. And it was indicative of a project whose contributors were overwhelmingly male. On CityLab, Sarah Holder examines OSM’s abysmally low female participation rate (only two to five percent of contributors are women), makes the case for better representation, and looks at where women are making a difference to the map. Because a map built overwhelmingly by men can have some massive blind spots.
When it comes to increasing access to health services, safety, and education—things women in many developing countries disproportionately lack—equitable cartographic representation matters. It’s the people who make the map who shape what shows up. On OSM, buildings aren’t just identified as buildings; they’re “tagged” with specifics according to mappers’ and editors’ preferences. “If two to five percent of our mappers are women, that means only a subset of that get[s] to decide what tags are important, and what tags get our attention,” said Levine.
Sports arenas? Lots of those. Strip clubs? Cities contain multitudes. Bars? More than one could possibly comprehend.
Meanwhile, childcare centers, health clinics, abortion clinics, and specialty clinics that deal with women’s health are vastly underrepresented. In 2011, the OSM community rejected an appeal to add the “childcare” tag at all. It was finally approved in 2013, and in the time since, it’s been used more than 12,000 times.
Interestingly, when you look at crisis mappers, the female participation rate jumps: to 27 percent, based on a survey of the Humanitarian OpenStreetMap Team community.
There are many circumstances where the amount of data vastly exceeds the ability to process and analyze it—and computers can only do so much. Enter crowdsourcing. Steve Coast points to Digital Globe’s Tomnod project, which basically crowdsources satellite image analysis. In the case of the current project to map the presence of Weddell seals on the Antarctic Peninsula and the ice floes of the Weddell Sea, users are given an image tile and asked to indicate whether there are seals in the image. It’s harder than it looks, but it’s the kind of routine task that most people can do—many hands, light work and all that—and it helps researchers focus their attention where it needs focusing. (A similar campaign for the Ross Sea took place in 2016.)
Another ongoing campaign asks users to identify flooded and damaged infrastructure and trash heaps in post-Hurricane Maria Puerto Rico.
When disaster strikes, crowdmapping kicks into high gear. Last Friday, six universities hosted mapathons where volunteers, using satellite imagery, contributed to the map of Puerto Rico and other hurricane-damaged areas on OpenStreetMap. More from one of the universities involved. Here’s the relevant project page on the OSM Wiki.
Today Esri is proud to announce that we are making our own global collection of satellite imagery available to the OSM community directly through our existing World Imagery Service. This regularly updated resource provides one meter or better satellite and aerial photography in many parts of the world, 15m TerraColor imagery at small and mid-scales (~1:591M down to ~1:72k), 2.5m SPOT Imagery (~1:288k to ~1:72k), 1 meter or better NAIP in the US and many other curated sources, so we know it will make a welcome addition to OSM’s growing catalog of reference layers.
OSM editors have been able to trace maps from satellite imagery for years; other sources of such imagery have included Bing and Yahoo (back when Yahoo Maps was a thing). Different sources have different strengths, so this can only help the project. (Esri’s imagery makes no difference where I am, but that’s not a surprise.)
Google Map Maker, Google’s tool to allow users to edit its maps, has been shut down, Ars Technica reports. “A support page went up over the weekend declaring that Map Maker is closed but that ‘many of its features are being integrated into Google Maps.’” You may recall that Map Maker was temporarily suspended in 2015 after a series of embarrassing edits came to light; its editing tools have been increasingly limited to a smaller circle of editors.
In response to measures like North Carolina’s House Bill 2, which restricts access to public washrooms by transgender people, crowdsourced online maps of safe washrooms—places with unisex or gender-neutral washrooms, or that let transgender people use the washroom that matches their gender identity—have been created: Refuge Restrooms has both a list and a map view; Safe Bathrooms uses Google My Maps. These maps seem like the modern-day equivalent of The Negro Motorist Green Book for trans people. [WMS]
Quartz takes a look at the Missing Maps project, which I suppose can best be described as a way to jumpstart mapping the unmapped developing regions of the world with OpenStreetMap. What’s interesting about Missing Maps is how it systematically deals out tasks to people best able to do them: remote volunteers trace imagery, community volunteers do the tagging and labelling. There’s even an app, MapSwipe, that gives its users “the ability to swipe through satellite images and indicate if they contain features like houses, roads or paths. These are then forwarded onto Missing Maps for precise marking of these features.” [WMS]
In Smithsonian, Erin Blakemore explores the on-the-ground, amateur efforts to get disadvantaged communities—slums, shanty towns, whatever they may be called—on the map, like the Map Kibera and Mapillary projects, and the implications of such projects.
Sterling Quinn, who is earning his Ph.D. in geography at Penn State, notes that there are downsides to user-generated maps. Just because an underserved community makes its way onto the map doesn’t mean it becomes less vulnerable, says Sterling. “Putting yourself on the map may make you more vulnerable to people who want to exploit the area,” he tells Smithsonian.com.
Point Google Maps or OpenStreetMap at a city like Dar es Salaam, Tanzania and you’ll get a reasonably good map. What you won’t get is Street View or street-level imagery—or, necessarily, the data that comes from a street-level understanding of the territory. NPR’s Nadia Whitehead looks at a joint project of the World Bank and Mapillary, a company that crowdsources street-level photos, to produce those images. “Volunteers are mounting camera rigs to their tuk tuks—three-wheeled motor-powered vehicles—to snap pictures as they cruise Dar es Salaam’s dirt roads. Others download the Mapillary app on their smartphones and capture images as they walk or hitch rides on motorbikes. In all, more than 260 people have volunteered.” [via]