Hurricane Laura information and resources, including maps of the observed and forecasted storm track, potential rainfall, storm surge and flooding, and other warning maps, can be found via NOAA’s Laura event page, the National Hurricane Center’s Hurricane Laura page, and the Esri Disaster Response Program’s Hurricane Hub. [GIS Lounge]
Remember the nuttery surrounding President Trump, his erroneous warning that Hurricane Dorian would hit Alabama, and his Sharpie-adjusted hurricane map? That was two whole months ago. It all put NOAA and the National Weather Service in an awkward spot. Mother Jones put in a Freedom of Information Act request for their internal emails and found out just how uncomfortable things were inside NOAA during that period.
I hadn’t planned on posting anything about Trump’s Sharpie-adjusted hurricane forecast map: there was nothing useful for me to add to the discussion, and presumably you’d all heard about it already and didn’t need me to tell you. But it turns out something map-related can, and has, been said about the issue.
Charles Blow was once in charge of the New York Times graphics department, and an art director at National Geographic. His response to Trump’s marked-up map was “visceral”:
Because of this unyielding commitment to accuracy, I believe cartography enjoys an enviable position of credibility and confidence among the people who see it. If you see it mapped, you believe.
That is precisely what you want the case to be, particularly in natural disasters. This cartography should be devoid of any attempt to deceive. Its only agenda should be to inform and enlighten.
That’s what made Trump’s marked-on map such a blasphemy: It attacked, on a fundamental level, truth, science and public trust. It wasn’t just a defacement of a public document, it was a defilement of a sacred trust.
Blow’s reaction is predicated in the notion that maps can’t lie, or at least don’t, or at least shouldn’t. Enter Mark Monmonier, the author of How to Lie with Maps (reviewed here), who was interviewed by CityLab about this kerfuffle. Even Monmonier, who has no illusions about maps’ claims to accuracy and objectivity, and who literally wrote the book on how hazard mapping can be misleading, seems to be sputtering:
Usually, attempts to falsify tend to happen before maps are published, and don’t try to contradict established scientific facts. You can put a spin on something by influencing the appearance of a map before it’s published. You can put a spin on things by determining what is and is not going to be mapped. Something that might put your administration in an unfavorable view, for example: Those maps won’t be part of the plan. […]
But the Trump map is unusual. I cannot find anything truly comparable. We had a map that was already out there that he actually mutilated, and in a very obvious way. This guy shows absolutely no subtlety at all. And then people try to make excuses for him. I have never seen anything like this.
Trump’s little stunt has revealed something very interesting about how we see maps.
The cone of uncertainty is a core feature of hurricane maps: it shows the potential routes a hurricane is likely to take (the path grows over time, as we’re less certain where the storm goes next). But it’s misinterpreted in ways that put people at risk. That’s the argument made by Alberto Cairo in an online infographic (and in print) in the New York Times last week: research reveals that people living along the edge of the cone are much less likely to prepare for the storm, even though the edge of the cone is one possible path for the centre of the storm—and the cone only covers 60 to 70 percent of the storm’s potential paths in any event.
Alberto Cairo goes into more detail about the problem, and the responsibility of both journalists and readers when faced with such visualizations, on his blog. His book, How Charts Lie: Getting Smarter About Visual Information, comes out from W. W. Norton next month.
Previously: Rethinking the Cone of Uncertainty.
A feature of hurricane maps is the so-called cone of uncertainty, which shows the range of likely paths the hurricane is forecasted to follow. The problem is that the cone of uncertainty is easily misinterpreted by the reader. The MIT Technology Review’s Karen Hao looks at five ways the cone can be misinterpreted, along with some alternative methods of visualizing a hurricane’s projected path. [Gretchen Peterson]
It’s after the fact, at least in terms of initial landfall (if not aftermath), but maps I’ve seen of Hurricane Michael include the USGS’s Hurricane Michael page, which includes an event support map and a map of coastal change impacts; and imagery from the Suomi NPP satellite that shows the path of Hurricane Michael through the power outages left in the storm’s wake.
During a natural disaster like Hurricane Florence, crisis maps can be an invaluable source of information about road and bridge closures and other infrastructure outages. Trouble is, that information doesn’t always trickle down to mobile phones, which is where most people get their maps. (Especially when authorities have trouble keeping up with road closures on their own maps.) CityLab’s Clare Tran explores this question, looking at, for example, how Waze incorporates road closure data from Esri and its volunteers.
Meanwhile, Typhoon Mangkhut has hit the Philippines and is moving toward China. The New York Times has a map tracking the storm’s path; NASA has posted a number of visible-light and infrared images of the storm as well.
The Washington Post has maps tracking Hurricane Florence’s forecasted path and its potential impact. Researcher Eira Tansey compiled data from several NOAA sources—hurricane track forecasting, potential storm surge flooding and long-duration hazards—to create this map.
Direct Relief’s Hurricane Florence Social Vulnerability Dashboard shows the extent to which the population in Florence’s path will be disproportionately affected by the storm. As CityLab’s Nicole Javorksy explains, while coastal areas will be hit hardest, residents there are more affluent; socioeconomic status, age, disability status, car ownership can all determine one’s ability to endure or recover from a storm.
The New York Times maps the environmental hazards in Florence’s path: “ponds of coal ash, Superfund sites, chemical plants—and thousands of industrial hog farms with lagoons filled with pig waste.” All have the potential to cause widespread contamination if flooded.
NASA’s Goddard Space Flight Center produced this visualization, based on computer modelling and data from Earth observing satellites, tracking how hurricanes transport sea salt, dust, and smoke across the globe.
During the 2017 hurricane season, the storms are visible because of the sea salt that is captured by the storms. Strong winds at the surface lift the sea salt into the atmosphere and the particles are incorporated into the storm. Hurricane Irma is the first big storm that spawns off the coast of Africa. As the storm spins up, the Saharan dust is absorbed in cloud droplets and washed out of the storm as rain. This process happens with most of the storms, except for Hurricane Ophelia. Forming more northward than most storms, Ophelia traveled to the east picking up dust from the Sahara and smoke from large fires in Portugal. Retaining its tropical storm state farther northward than any system in the Atlantic, Ophelia carried the smoke and dust into Ireland and the UK.
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.
At NASA’s Earth Observatory, before and after images of Puerto Rico’s nighttime lights illustrate the extent of power outages and infrastructure damage on the island. NASA has also produced a map of likely damaged areas of eastern Puerto Rico, based on before and after radar satellite interferometry and similar to the map they produced for the Mexican earthquake. At ground level, the CrowdRescue Puerto Rico Infrastructure Map displays crowdsourced reports of damage—downed power lines, bridge collapses, floods, mudslides and other incidents.
Here’s a CBS News gallery of before-and-after images showing the impact of flooding in the wake of Hurricane Harvey. The page is undated but was published on 1 September. [Dave Smith]
And, via CityLab, here are a set of maps from the Urban Institute that show the impact of Hurricane Harvey on Houston’s neighbourhoods, based on income levels, home ownership rates, accumulated-equity rates, all of which looking at the economic impact of the storm. “Harvey’s aftermath puts an enormous hurdle in front of all homeowners and renters but will be a particular setback for low-income, minority families recovering from the 2008 housing bust.”
Previously: Mapping Hurricane Harvey’s Impact.