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Yesterday — May 29th 2020Your RSS feeds

As wildfire season approaches, AI could pinpoint risky regions using satellite imagery

By Devin Coldewey

The U.S. has suffered from devastating wildfires over the last few years as global temperatures rise and weather patterns change, making the otherwise natural phenomenon especially unpredictable and severe. To help out, Stanford researchers have found a way to track and predict dry, at-risk areas using machine learning and satellite imagery.

Currently the way forests and scrublands are tested for susceptibility to wildfires is by manually collecting branches and foliage and testing their water content. It’s accurate and reliable, but obviously also quite labor intensive and difficult to scale.

Fortunately, other sources of data have recently become available. The European Space Agency’s Sentinel and Landsat satellites have amassed a trove of imagery of the Earth’s surface that, when carefully analyzed, could provide a secondary source for assessing wildfire risk — and one no one has to risk getting splinters for.

This isn’t the first attempt to make this kind of observation from orbital imagery, but previous efforts relied heavily on visual measurements that are “extremely site-specific,” meaning the analysis method differs greatly depending on the location. No splinters, but still hard to scale. The advance leveraged by the Stanford team is the Sentinel satellites’ “synthetic aperture radar,” which can pierce the forest canopy and image the surface below.

“One of our big breakthroughs was to look at a newer set of satellites that are using much longer wavelengths, which allows the observations to be sensitive to water much deeper into the forest canopy and be directly representative of the fuel moisture content,” said senior author of the paper, Stanford ecoydrologist Alexandra Konings, in a news release.

The team fed this new imagery, collected regularly since 2016, to a machine learning model along with the manual measurements made by the U.S. Forest Service. This lets the model “learn” what particular features of the imagery correlate with the ground-truth measurements.

They then tested the resulting AI agent (the term is employed loosely) by having it make predictions based on old data for which they already knew the answers. It was accurate, but most so in scrublands, one of the most common biomes of the American west and also one of the most susceptible to wildfires.

You can see the results of the project in this interactive map showing the model’s prediction of dryness at different periods all over the western part of the country. That’s not so much for firefighters as a validation of the approach — but the same model, given up to date data, can make predictions about the upcoming wildfire season that could help the authorities make more informed decisions about controlled burns, danger areas, and safety warnings.

The researchers’ work was published in the journal Remote Sensing of Environment.

‘Oumuamua Might Be a Giant Interstellar Hydrogen Iceberg

By Daniel Oberhaus
It isn’t an alien spaceship, but new research suggests the first known interstellar object to grace our solar system could be something even stranger.

Covid-19 Testing Is Expensive. It Doesn't Have to Be

By Gregory Barber
The diagnostics industry favors wealthy countries, but the rest of the world needs tests, too. Stanford bioengineer Manu Prakash thinks "frugal science can help.

Some Nursing Homes Escaped Covid-19—Here's What They Did Right

By Sara Harrison
As states start to reopen, senior care facilities must balance the needs of residents against the potential for more deadly Covid-19 outbreaks.
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SpaceX gets FAA permission to fly its Starship spacecraft prototype

By Darrell Etherington

SpaceX has received authorization from the Federal Aviation Administration (FAA) to fly suborbital missions with its Starship prototype spacecraft, paving the way for test flights at its Boca Chica, Texas site. SpaceX has been hard at work readying its latest Starship prototype for low-altitude, short duration controlled flight tests, and conducted another static engine fire test of the fourth iteration of its in-development spacecraft earlier today.

Officially, the FAA has granted SpaceX permission to conduct what it terms “reusable launch vehicle” missions, which essentially means that the Starship prototype is now cleared to take-off from, and land back at, the launch site SpaceX operates in Boca Chica. The Elon Musk-led space company has already conducted similar tests, but previously used its ‘Starhopper’ early prototype, which was smaller than the planned production Starship, and much more rudimentary in design. It was basically used to prove out the capabilities of the Raptor engine that SpaceX will use to propel Starship, and only for a short hop test using one of those engines.

Since that flight last year, SpaceX has developed multiple iterations of a full-scale prototype of Starship, but thus far they haven’t gotten back to the point where they’re actively flying any of those. In fact, multiple iterations of the Starship prototype have succumbed during pressure testing – though SN4, the version currently being prepared for a test flight, has passed not only pressure tests, but also static test fires of its lone Raptor engine.

The plan now is to fly this one for a short ‘hop’ flight similar to the one conducted by Starhopper, with a maximum altitude of around 500 feet. Should that prove successful, the next version will be loaded with more Raptor engines, and attempt a high altitude test launch. SpaceX is quickly building newer version of Starship in succession even as it proceeds with testing the completed prototypes, in order to hopefully shorten the total timespan of its development.

There’s something of a clock that SpaceX is working against: It was one of three companies that received a contract award from NASA to develop and build a human lander for the agency’s Artemis program to return to the Moon. NASA aims to make that return trip happen by 2024, and while the contract doesn’t necessarily require that each provided have a lander ready in that timeframe, it’s definitely a goal, if only for bragging rights among the three contract awardees.

Researchers use biometrics, including data from the Oura Ring, to predict COVID-19 symptoms in advance

By Darrell Etherington

A team of researchers from the West Virginia University (WVU) Rockefeller Neuroscience Institute (RNI), along with WVU’s Medicine department and staff from Oura Health have developed a platform they say can be used to anticipate the onset of COVID-19 symptoms in otherwise healthy people up to three days in advance. This can help with screening of pre-symptomatic individuals, the researchers suggest, enabling earlier testing and potentially reducing the exposure risk among frontline healthcare and essential workers.

The sudsy involved using biometric data gathered by the Oura Ring, a consumer wearable that looks like a normal metallic ring, but that includes sensors to monitor a number of physiological metrics, including body temperature, sleep patterns, activity, heart rate and more. RNI and WVU Medical researchers combined this data with physiological, cognitive and behaviroral biometric info from around 600 healthcare workers and first responders.

Participants in the study wore the Oura Ring, and provided additional data that was then used to develop AI-based models to anticipate the onset of symptoms before they physically manifested. While these are early results from a phase one study, and yet to be peer-reviewed, the researchers say that their results showed a 90 percent accuracy rate on predicting the occurrence of symptoms including fever, coughing, difficulty breathing, fatigue and more, all of which could indicate that someone has contracted COVID-19. While that doesn’t mean that individuals have the disease, a flag from the platform could mean they seek testing up to three days before symptoms appear, which in turn would mean three fewer days potentially exposing others around them to infection.

Next up, the study hopes to expand to cover as many as 10,000 participants across a number of different institutions in multiple states, with other academic partners on board to support the expansion. The study was fully funded by the RNI and their supporters, with Oura joining strictly in a facilitating capacity and to assist with hardware for deployment.

Many projects have been undertaken to see whether predictive models could help anticipate COVID-19 onset prior to the expression of symptoms, or in individuals who present as mostly or entirely asymptomatic based on general observation. This early result from RNI suggests that it is indeed possible, and that hardware already available to the general public could play an important role in making it possible.

Covid-19 Creates Long, Anxious Waits for Fertility Treatments

By Monique Brouillette
As fertility clinics gradually reopen, patients and doctors must weigh the risks of seeking pregnancy during a pandemic—or waiting too long to try.

To Beat Covid-19, You Have to Know How A Virus Moves

By Adam Rogers
As public spaces reopen, scientists are racing to understand the mysterious and turbulent way the disease spreads through air—from person to person, and place to place.

Weather Delays the SpaceX Crew Dragon Launch

By Daniel Oberhaus
The historic launch planned for Wednesday gets pushed back due to stormy conditions, but the launch window remains open. SpaceX and NASA will try again Saturday.

Whoooaaa Duuuuude: Why We Stretch Words in Tweets and Texts

By Matt Simon
Notice you've been elongating your words lately? You're actually loading them with a whooooole lot of meaning.

3 Ways Scientists Think We Could De-Germ a Covid-19 World

By Michele Cohen Marill
Researchers want to know if we can create an antiviral infrastructure that would protect humans from transmission. Here are a few ideas.

Trump’s New Space Force Missile Might Be Too ‘Super-Duper’

By Rhett Allain
To go that fast, it would need a ridiculous amount of fuel—and even then, it might never come back down.

Virgin Orbit’s Air-Launched Rocket Fails Its First Test

By Daniel Oberhaus
LauncherOne failed a few seconds into its first flight. But that’s OK—the only two US rocket startups that made it to orbit flubbed their first tries too.

This Citizen Science Gig Pays People to Match Space Photos

By Sarah Scoles
Astronomers at the Hubble Image Similarity Project are employing their out-of-work neighbors to help them train a neural net to recognize celestial objects.

How an Immunology Blog Became a Covid-19 Guide to Going Out

By Megan Molteni
With lockdowns ending, people have a lot of questions about how to calculate the risks of returning to everyday activities. Erin Bromage has answers.

Covid-19 Flares Up in America's Polluted ‘Sacrifice Zones’

By Sidney Fussell
Researchers find that areas with high levels of airborne dust or toxic chemicals also have more deaths from the coronavirus.

How to Watch SpaceX Launch Astronauts to the ISS

By Daniel Oberhaus
The occasion will mark the first time a private company blasts NASA astronauts into space. Here's everything you need to know.

Meet This Museum's All-Star Arachnids and Insects

By Matt Simon
Camel spiders and giant hornets and shimmering butterflies, oh my. An arachnologist gives a behind-the-scenes tour at the California Academy of Sciences.

What It’s Like to Be First to Fly a Brand New Spacecraft

By Daniel Oberhaus
Robert Crippen is the only living NASA astronaut to have flown on a new spacecraft for the first time. The Crew Dragon flyers will join his elite club this week.

Covid-19 Makes the Case for More Meatpacking Robots

By Megan Molteni
The coronavirus has hit meat processing plants hard. But not in Denmark, where automation makes for safer slaughterhouses.
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