In the summer of 2019, a research project spearheaded by Monument Lab asked St. Louis residents and visitors to draw personal maps of the city’s monuments and important sites. “Some maps celebrate famous sites like the St. Louis Zoo and the statue of St. Louis himself atop Art Hill in Forest Park. Others point to things that have been removed from the landscape, like the mounds built by native Mississippians,” St. Louis Public Radio reports. “Another shows a street map of downtown St. Louis with notations for ‘incidents of racism, from microaggression to racial violence.’” A total of 750 people contributed maps, which you can see at this Flickr gallery as well as on the project website, which has accompanying data and analysis. [Osher]

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.

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.

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 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.

Previously: Volunteers Mapping Post-Hurricane Puerto Rico.

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.)

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.

[Dave Smith]

Previously: The Geospatial Revolution Project, Episode Four; Crowdsourcing Street Photos of Dar es Salaam.

[via]

Researchers are mapping the shift in Swiss German dialect usage via an iOS app. The app asks users to take a 16-question survey based on maps from a language atlas that mapped Swiss German usage circa 1950. The app predicts the user’s actual home dialect location based on those maps; differences between that prediction and the user’s actual home dialect location reveal how Swiss German has changed over time. They ended up getting responses from 60,000 speakers. PLOS ONE article. [via]

If mapcodes and other geographical shortcodes aren’t Googly enough for you, take a look at Open Location Codes, a Google-developed, open-sourced project. Generated algorithmically rather than with data tables. Announced for developers last April, they can now be used in Google Maps searches.

To be fair to Google, crowdsourcing map data does have its pitfalls: OpenStreetMap has to deal with this sort of thing all the time. You have to have something in place to deal with bad-faith edits. None of the edits I’ve made to Google Maps went through without someone reviewing them, so I’m surprised that this could happen. That said, when you need your map updated fast (such as during natural disasters like yesterday’s earthquake in Nepal), it’s hard to beat crowdsourcing.

As always, it’s important to keep in mind that all online maps have their shortcomings.

On-the-ground surveying with a GPS is a great way to contribute to OpenStreetMap, but it’s not hard to see how it might be construed as suspicious activity. The problem isn’t actually the GPS, which is inconspicuous enough unless you’re staring at it every five seconds, it’s the note-taking that goes along with it. Even here in Shawville, when we were surveying a couple of residential streets, one of Jennifer’s co-workers spotted us and later asked us what the hell we had been doing. We were writing down house numbers to add to the map — but stopping every few metres to write down the house number at each corner does look a bit odd. So does taking a photo of every street sign (to confirm road names independently of third-party mapping data). It helps to be as discreet and non-creepy as possible.

Fortunately, it’s a small town and we’re known, so we haven’t run into any serious trouble yet. If asked, I usually explain that I’m mapping the town for a website called OpenStreetMap, which is like Wikipedia for maps: everybody runs around with a GPS to create a map of the world. (At that point their eyes usually glaze over.)