A new study calls the technique "location spoofing."
Research indicates that "deepfake geography," or realistic but fake images of real places, could become a growing problem.
For example, a fire in Central Park seems to appear as a smoke plume and a line of flames in a satellite image. In another, colorful lights on Diwali night in India, seen from space, seem to show widespread fireworks activity.
Both images exemplify what the new study calls "location spoofing." The photos—created by different people, for different purposes—are fake but look like genuine images of real places.
So, using satellite photos of three cities and drawing upon methods used to manipulate video and audio files, a team of researchers set out to identify new ways of detecting fake satellite photos, warn of the dangers of falsified geospatial data, and call for a system of geographic fact-checking.
"This isn't just Photoshopping things. It's making data look uncannily realistic," says Bo Zhao, assistant professor of geography at the University of Washington and lead author of the study in the journal Cartography and Geographic Information Science. "The techniques are already there. We're just trying to expose the possibility of using the same techniques, and of the need to develop a coping strategy for it."
Putting lies on the map
As Zhao and his coauthors point out, fake locations and other inaccuracies have been part of mapmaking since ancient times. That's due in part to the very nature of translating real-life locations to map form, as no map can capture a place exactly as it is. But some inaccuracies in maps are spoofs that the mapmakers created. The term "paper towns" describes discreetly placed fake cities, mountains, rivers, or other features on a map to prevent copyright infringement.
For example, on the more lighthearted end of the spectrum, an official Michigan Department of Transportation highway map in the 1970s included the fictional cities of "Beatosu and "Goblu," a play on "Beat OSU" and "Go Blue," because the then-head of the department wanted to give a shout-out to his alma mater while protecting the copyright of the map.
But with the prevalence of geographic information systems, Google Earth, and other satellite imaging systems, location spoofing involves far greater sophistication, researchers say, and carries with it more risks. In 2019, the director of the National Geospatial Intelligence Agency, the organization charged with supplying maps and analyzing satellite images for the US Department of Defense, implied that AI-manipulated satellite images can be a severe national security threat.
Tacoma, Seattle, Beijing
To study how satellite images can be faked, Zhao and his team turned to an AI framework that has been used in manipulating other types of digital files. When applied to the field of mapping, the algorithm essentially learns the characteristics of satellite images from an urban area, then generates a deepfake image by feeding the characteristics of the learned satellite image characteristics onto a different base map—similar to how popular image filters can map the features of a human face onto a cat.
Next, the researchers combined maps and satellite images from three cities—Tacoma, Seattle, and Beijing—to compare features and create new images of one city, drawn from the characteristics of the other two. They designated Tacoma their "base map" city and then explored how geographic features and urban structures of Seattle (similar in topography and land use) and Beijing (different in both) could be incorporated to produce deepfake images of Tacoma.
In the example below, a Tacoma neighborhood is shown in mapping software (top left) and in a satellite image (top right). The subsequent deepfake satellite images of the same neighborhood reflect the visual patterns of Seattle and Beijing. Low-rise buildings and greenery mark the "Seattle-ized" version of Tacoma on the bottom left, while Beijing's taller buildings, which AI matched to the building structures in the Tacoma image, cast shadows—hence the dark appearance of the structures in the image on the bottom right. Yet in both, the road networks and building locations are similar.
These are maps and satellite images, real and fake, of one Tacoma neighborhood. The top left shows an image from mapping software, and the top right is an actual satellite image of the neighborhood. The bottom two panels are simulated satellite images of the neighborhood.Zhao et al., 2021, Cartography and Geographic Information Science
The untrained eye may have difficulty detecting the differences between real and fake, the researchers point out. A casual viewer might attribute the colors and shadows simply to poor image quality. To try to identify a "fake," researchers homed in on more technical aspects of image processing, such as color histograms and frequency and spatial domains.
Could 'location spoofing' prove useful?
Some simulated satellite imagery can serve a purpose, Zhao says, especially when representing geographic areas over periods of time to, say, understand urban sprawl or climate change. There may be a location for which there are no images for a certain period of time in the past, or in forecasting the future, so creating new images based on existing ones—and clearly identifying them as simulations—could fill in the gaps and help provide perspective.
The study's goal was not to show that it's possible to falsify geospatial data, Zhao says. Rather, the authors hope to learn how to detect fake images so that geographers can begin to develop the data literacy tools, similar to today's fact-checking services, for public benefit.
"As technology continues to evolve, this study aims to encourage more holistic understanding of geographic data and information, so that we can demystify the question of absolute reliability of satellite images or other geospatial data," Zhao says. "We also want to develop more future-oriented thinking in order to take countermeasures such as fact-checking when necessary," he says.
Coauthors of the study are from the University of Washington, Oregon State University, and Binghamton University.
Can spacekime help us make headway on some of the most pernicious inconsistencies in physics?
- Our linear model of time may be holding back scientific progress.
- Spacekime theory can help us better understand the development of diseases, financial and environmental events, and even the human brain.
- This theory helps us better utilize big data, develop AI, and can even solve inconsistencies in physics.
We take for granted the western concept of linear time. In ancient Greece, time was cyclical and if the Big Bounce theory is true, they were right. In Buddhism, there is only the eternal now. Both the past and the future are illusions. Meanwhile, the Amondawa people of the Amazon, a group that first made contact with the outside world in 1986, have no abstract concept of time. While we think we know time pretty well, some scientists believe our linear model hobbles scientific progress. We're missing whole dimensions of time, in this view, and our limited perception could be the last obstacle to a sweeping theory of everything.
Theoretical physicist Itzhak Bars of the University of Southern California, Los Angeles, is the most famous scientist with such a hypothesis, known as two-time physics. Here, time is 2D, visualized as a curved plane interwoven into the fabric of the "normal" dimensions—up-down, left-right, and backward-forward. While the hypothesis is over a decade old, Bars isn't the only scientist with such an idea. But what's different with spacekime theory is that it uses a data analytics approach, rather than a physics one. And while it posits that there are at least two dimensions of time, it allows for up to five.
In the spacekime model, space is 5D. Besides the ones we normally encounter, the extra dimensions are so infinitesimally small, we never notice them. This relates to the Kaluza–Klein theory developed in the early 20th century, which stated that there might be an extra, microscopic dimension of space. In this view, space would be curved like the surface of Earth. And like Earth, those who travel the entire distance would, eventually, loop back to their place of origin.
Kaluza-Klein theory unified electromagnetism and gravity, but wasn't accepted at the time, although it did help in the search for quantum gravity. The concept of additional dimensions was revived in the 1990s with Paul Wesson's Space-Time-Matter Consortium. Today, proponents of superstring theory say there may be as many as 10 different dimensions, including nine of space and one of time.
The Spacekime model
Spacekime theory was developed by two data scientists. Dr. Ivo Dinov is the University of Michigan's SOCR Director, as well as a professor of Health Behavior and Biological Sciences, and Computational Medicine and Bioinformatics. SOCR stands for: Statistics Online Computational Resource designs. Dr. Dinov is an expert in "mathematical modeling, statistical analysis, computational processing, scientific visualization of large datasets (Big Data) and predictive health analytics." His research has focused on mathematical modeling, statistical inference, and biomedical computing.
His colleague, Dr. Milen Velchev Velev, is an associate professor at the Prof. Dr. A. Zlatarov University in Bulgaria. He studies relativistic mechanics in multiple time dimensions, and his interests include "applied mathematics, special and general relativity, quantum mechanics, cosmology, philosophy of science, the nature of space and time, chaos theory, mathematical economics, and micro-and-macroeconomics."
Drs. Dinov and Velev began developing spacekime theory around four or five years ago, while working with big data in the healthcare field. "We started looking at data that intrinsically has a temporal dimension to it," Dr. Dinov told me during a video chat. "It's called longitudinal or time varying data, longitudinal time variance—it has many, many names. This is data that varies with time. In biomedicine, this is the de facto, standard data. All big health data is characterized by space, time, phenotypes, genotypes, clinical assessments, and so forth."
A better way to manage big data
"We started asking big questions," Dinov said. "Why are our models not really fitting too well? Why do we need so many observations? And then, we started playing around with time. We started digging and experimenting with various things. And then we realized two important facts.
"Number one, if we use what's called color-coded representations of the complex plane, we can define spacekime, or higher dimensional spacetime, in such a way that it agrees with the common observations that we make in (the longitudinal time series in) ordinary spacetime. That agreement was very important to us, because it basically says, yes, the higher dimensional theory does not contradict our common observations.
"The second realization was that, since this extra dimension of time is imperceptible, we needed to approximate, model, or estimate, one of the unobservable time characteristics, which we call the kime phase. After about a year, we discovered that there is a mathematically elegant tool called the Laplace Transform that allows us to analytically represent time series data as kime-surfaces. Turns out, the spacekime mathematical manifold is a natural, higher dimensional extension of classical Minkowski, four-dimensional spacetime."
Our understanding of the world is becoming more complex. As a result, we have big data to contend with. How do we find new ways to analyze, interpret and visual such data? Dinov believes spacekime theory can help in some pretty impressive ways. "The result of this multidimensional manifold generalization is that you can make scientific inferences using smaller data samples. This requires that you have a good model or prior knowledge about the phase distribution," he said. "For instance, we can use spacekime process representation to better understand the development or pathogenesis to model the distributions of certain diseases.
"Suppose we are evaluating fMRIs of Alzheimer's disease subjects. Assume we know the kime phase distribution for another cohort of patients suffering from amyotrophic lateral sclerosis, Lou Gehrig's disease. The ALS kime-phase distribution could be used for evaluating the Alzheimer's patients," and many other neurodegenerative populations. Dinov also thinks spacekime analytics could help improve political polling, increase our understanding of complex financial and environmental events, and even the innerworkings of the human brain, all without having to take the huge samples required today to make accurate models or predictions. Spacekime theory even offers opportunities to design novel AI analytical techniques. But it goes beyond that.
The problem of time
Spacekime theory can help us make headway on some of the most pernicious inconsistencies in physics, such as Heisenberg's uncertainty principle and the seemingly irreconcilable rift between quantum physics and general relativity, what's known as "the problem of time."
Dinov wrote that the "approach relies on extending the notions of time, events, particles, and wave functions to complex-time (kime), complex-events (kevents), data, and inference-functions." Basically, working with two points of time allows you to make inferences on a radius of points associated with a certain event. With Heisenberg's uncertainty principle, according to this model, since time is a plane, a certain particle would be in one position or phase, time-wise, in terms of velocity, and another phase, in terms of position.
This idea of hidden dimensions of time is a little like Plato's allegory of the cave or how an X-ray signifies what's underneath, but doesn't convey a 3D image. From a data science perspective, it all comes down to utility. Dinov believes that if we can calculate the true phase dispersion of complex phenomena, we can better understand and control them.
Drs. Dinov and Velev's book on spacekime theory comes out this August. It's called "Data Science: Time Complexity, Inferential Uncertainty, and Spacekime Analytics".
Light-emitting tattoos could indicate dehydration in athletes or health conditions in hospital patients.
- Researchers at UCL and IIT have created a temporary tattoo that contains the same OLED technology that is used in TVs and smartphones.
- This technology has already been successfully applied to various materials including glass, food items, plastic, and paper packaging.
- This advance in technology isn't just about aesthetics. "In healthcare, they could emit light when there is a change in a patient's condition - or, if the tattoo was turned the other way into the skin, they could potentially be combined with light-sensitive therapies to target cancer cells, for instance," explains senior author Franco Cacialli of UCL.
Scientists at University College London (UCL) and the IIT (Istituto Italiano di Tecnologia) have created a temporary tattoo that contains the same light-emitting technology used in TVs and smartphone screens.
The technology uses organic light-emitting diodes (OLEDs) and is applied in the same way as simple water-transfer tattoos. The OLEDs are fabricated onto a temporary tattoo paper and then transferred to a new surface by being pressed onto it and dabbed with water.
According to the research, these OLED devices being developed are 2.3 micrometers thick in total (less than one 400th of a millimeter) and about one-third of the length of a single red blood cell. The device consists of an electroluminescent polymer (a polymer that emits light when an electric field is applied) that is placed in between electrodes. An insulating layer is then placed in between the electrodes and the commercial tattoo paper.
This process has already been successfully applied to various materials.
Once the research team had perfected the technology, they applied the tattoo-able OLEDs (which emit green light) onto various surfaces including a pane of glass, a plastic bottle, an orange, and paper packaging. The first OLEDs were used in a flatscreen television more than 20 years ago, and now, through this proof-of-concept study, "smart tattoos" may be a thing of the (very near) future.
Why “smart tattoos” could be beneficial
OLEDs are used to create digital displays in devices (such as television screens computer monitors, smartphones, etc).
Credit: Hanna on Adobe Stock
While this is perhaps the most obvious way you could use light-emitting tattoo technology, the world of tattoo art and design could see a huge surge in new exciting trends based on light-emitting tattoo technology.
It's not just about looks—this approach provides a quick and easy method of transferring OLEDs onto practically any surface.
OLEDs are used to create digital displays in devices (such as television screens computer monitors, smartphones, etc). While some may get OLED and LED confused, they are quite different, with OLED displays emitting visible light and therefore being able to be used without a backlight. The breakthrough process of being able to transfer OLEDs onto virtually any surface can be useful in many different applications and settings.
Light-emitting tattoos could be used to indicate (and potentially even treat) various health conditions in the future.
The eventual implementation or use of OLED tattoos could be combined with other tattoo electronics to, for instance, emit light when an athlete is dehydrated, or when a person is being exposed to too much sun and is prone to sunburn.
"In healthcare, they could emit light when there is a change in a patient's condition - or, if the tattoo was turned the other way into the skin, they could potentially be combined with light-sensitive therapies to target cancer cells, for instance." - Professor Franco Cacialli (UCL)
OLED tattoo devices
Credit: Barsotti - Italian Institute of Technology
Similarly, this technology could be used on the packaging of various items to give us more information about them.
For example, OLEDs could be tattooed onto the packaging of a fruit to signal when the product is passed its expiration date or will soon become inedible.
In reality, creating light-emitting tattoo technology doesn't have to be expensive.
Professor Franco Cacialli explains to Eurekalert: "The tattooable OLEDs that we have demonstrated for the first time can be made at scale and very cheaply. They can be combined with other forms of tattoo electronics for a very wide range of possible uses. These could be for fashion - for instance, providing glowing tattoos and light-emitting fingernails. In sports, they could be combined with a sweat sensor to signal dehydration."
"Our proof-of-concept study is the first step. Future challenges will include encapsulating the OLEDs as much as possible to stop them from degrading quickly through contact with air, as well as integrating the device with a battery or supercapacitor."
Do they really need the human touch?
- In Pinduoduo's Smart Agriculture Competition, four technology teams competed with traditional farmers over four months to grow strawberries.
- Data analysis, intelligent sensors and greenhouse automation helped the scientists win.
- Fourth Industrial Revolution technologies such as AI are forecast to deliver huge productivity gains – but need the right governance, according to the Global Technology Governance Report 2021.
Strawberries can be easy to grow – especially, it seems, if you're an algorithm.
When farmers in China competed to grow the fruit with technology including machine learning and artificial intelligence, the machines won, by some margin.
Data scientists produced 196% more strawberries by weight on average compared with traditional farmers.
The technologists also outperformed farmers in terms of return on investment by an average of 75.5%
The inaugural Smart Agriculture Competition was co-organized by Pinduoduo, China's largest agri-focused technology platform, and the China Agricultural University, with the Food and Agriculture Organization of the United Nations as a technical adviser.
Teams of data scientists competed over four months to grow strawberries remotely using Internet of Things technology coupled with artificial intelligence (AI) and machine learning-driven algorithms.
In the competition, the technology teams had the advantage of being able to control temperature and humidity through greenhouse automation, the organizers said. Using technology such as intelligent sensors, they were also more precise at controlling the use of water and nutrients. The traditional farmers had to achieve the same tasks by hand and experience.
One of the teams, Zhi Duo Mei, set up a company to provide its technology to farming cooperatives after it generated a lot of interest during the competition.
The contest helped the traditional farmers and the data scientists better understand each other's work and how they could collaborate to everyone's advantage, the leader of the Zhi Duo Mei team, Cheng Biao, said.
Numerous studies show the potential for Fourth Industrial Revolution technologies like AI to boost economic growth and productivity.
By 2035, labour productivity in developed countries could rise by 40% due to the influence of AI, according to analysis from Accenture and Frontier Economics.
Sweden, the US and Japan are expected to see the highest productivity increases.
In its Future of Jobs Report 2020, the World Economic Forum estimates that by 2025, 85 million jobs may be displaced by a shift in the division of labour between humans and machines, while 97 million new roles may emerge that are more adapted to the new division of labour between humans, machines and algorithms.
Emerging technologies including AI and drones will also play a vital role in helping the world recover from COVID-19, according to a separate Forum report compiled with professional services firm Deloitte.
The Global Technology Governance Report 2021 considers some of the most important applications for these technologies – and the governance challenges that should be addressed for these technologies to reach their full potential.
From making their own swabs to staying in constant communication across the board, Northwell Health dove headfirst into uncharted waters to take on the virus and save lives.
- Preparing for a pandemic like COVID-19 was virtually impossible. Northwell Health president and CEO Michael Dowling explains how, as the largest healthcare provider in New York, his team had to continuously organize, innovate, and readjust to dangerous and unpredictable conditions in a way that guaranteed safety for the staff and the best treatment for over 128,000 coronavirus patients.
- From making their own supplies when they ran out, to coordinating with government at every level and making sense of new statistics and protocols, Northwell focused on strengthening internal and external communication to keep the ship from sinking.
- "There was no such thing as putting up the white flag," Dowling says of meeting the pandemic head on and reassuring his front line staff that they would be safe and have all the resources they needed to beat the virus. "It's amazing how innovative you can be in a crisis."