Satellogic, a geospatial analytics company headquartered in Buenos Aires, plans to remap the planet at one meter of resolution every week and dramatically reduce the cost of high-frequency geospatial analytics. This has the possibility of initiating new pathbreaking developments in Earth Observation and enabling new developments in analytics as well.
Earth Observation sector is undergoing a great disruption with the profusion of data, enhanced capability in data analytics and the emergence of technologies like AI and Machine Learning that have the potential to redefine the industry.
Gaining insights from multiple data streams and then collating the data is the most preferred way for companies that lead to greater efficiency and precision while substantially cutting down on costs.
AI to be a game-changer
Artificial Intelligence would completely transform the landscape of multiple sectors and set new contours for them. And Earth Observation and analytics certainly are among the sectors where adoption of AI is faster than the average rate.
Highlighting both the game-changing potential of AI and its increasing utility, Emiliano Kargieman, Founder and CEO, Satellogic, says “When you consider that in the near future we’ll be capturing millions of square kilometers every day, it puts into perspective the need for enabling technologies like artificial intelligence and deep learning, which elucidate the value within the imagery. That’s why Artificial intelligence is already an important tool in geospatial analytics, as it allows us to actually synthesize and find meaningful trends in the massive amounts of data that satellites are collecting today.”
He also believes that AI’s role as an enabling technology in the Earth Observation market would grow exponentially and make our insights here increasingly rich and valuable, and, more importantly, create new EO markets that weren’t feasible before.
Many companies are gearing themselves up as per the latest innovations and are preparing to take a plunge in the analytics sector for taking Earth Observation to the next level and ensure that its applications increase.
Cost-effectiveness is another major concern for the analytics industry and a stumbling block in the path towards the democratization of data. While a large number of small satellites have made space exploration more accessible than ever and increased accessibility of data is spurring new developments in data analytics and geospatial intelligence. But when it comes to analyzing the EO data using the latest methodology cost is still a significant deterrent in the adoption of new technology.
“The single biggest challenge in the EO industry is delivering solutions at a cost aligned with the unit economics of potential customers. Cost has, quite simply, been the largest barrier to adoption for businesses of all sizes – from the midmarket to the Fortune 1000”, believes Kargieman.
He says that Satellogic has been attempting to overcome the cost barrier by building its own constellation, own unique dataset, and own solutions.
Opening up access to geospatial insights will accelerate humanity’s ability to solve some of the world’s most pressing problems, shares Kargieman.
He is also of the belief that a vertically integrated approach produces efficiencies up and down the value chain. By passing those efficiencies, we can help level the playing field.
Discussing Satellogic’s initiatives to ensure democratization of data, Kargieman says, “We effectively reinvented the satellite from the ground up to produce a smaller, lighter, less expensive and more scalable system. We have designed a satellite that generates high resolution (1-meter) imagery and, at the same time, are orders of magnitude less expensive than the competition”.
This leading quality-to-cost ratio is what allows us economically to launch a constellation of tens and eventually hundreds of satellites and will lead the democratization of EO data, he further adds.
Hyperspectral Imagery will play a big role in the future of data analytics but currently, the possibilities are limited and the domain is in early stages. So, most companies do not rely only on hyperspectral imagery.
“Satellogic doesn’t exclusively rely on hyperspectral imagery, and we also capture multispectral imaging at 1-meter resolution”, says Kargieman.
“Hyperspectral imaging is still very much in the experimental phase, as companies determine how best to utilize the data it collects and find its place in the market”.
I think we’re moving towards a period of refinement, where the applications for hyperspectral will become better defined and the customer base will grow, Kargieman adds.