The iPhone Moment for Data from Space: Dealing with The Hype around Earth Observation
By: Aravind Ravichandran
Tags: Space, iPhone, Innovation, Earth Observation, Geospatial

Innovations and Expectations

Advancements in satellite miniaturisation and reduction in launch costs have meant that different types of payloads could now be developed and flight-tested faster and cheaper than ever before. Meaning we now have the ability to monitor Earth and collect so many different types of data than ever before. From monitoring radio frequency signals (Hawkeye360, Kleos, Unseenlabs) to catch illegal fishing to understanding our weather better using radio occultation signals, from navigation satellites (Spire, GeoOptics). From keeping track of greenhouse gas emissions (GHGSat, Bluefield, MethaneSat) and pinpointing the emitters to keeping an eye on the energy efficiency of the buildings we live and work in (SatelliteVu). From monitoring the spread of wildfires (ConstellR, OroraTech) to enhancing the prediction of crop yields and plant health (ScanWorld). Several hundred satellites from tens of companies (Planet, Maxar, Airbus etc.) are already up in space taking pictures of the planet several times a day, enabling us to gather data even during nights and cloud weather (Capella Space, Iceye, Synspective etc.).

If you follow me on LinkedIn, you might have seen that there are numerous other applications, all of them potentially multi-billion dollar markets, especially if we combine the data from satellites with other sources of data. It is not very different from any other type of software — build SaaS-like applications based on satellite data capitalising the developments in artificial intelligence and data visualisation. Various platforms and marketplaces (Up42, Astraea, Skywatch, Descartes Labs) are coming up to help put together all this data in one place. Data from space is most certainly a compulsory component for helping us solve the biggest challenge of our generation — climate change: from reporting climate risk and insurance risk (Sust Global, Jupiter Intelligence) to reporting ESG data (RSMetrics), which is becoming a norm in the financial services sector. Powered by cloud computing for EO (even attracting the likes of Amazon Web Services, Google Cloud) and Microsoft Azure), Earth observation data can provide ‘insights-from-space’ as a service, for all sorts of verticals — from energy and retail to utilities and agriculture. Observing the Earth from the stratosphere (~50 km) is only going to lead to high-resolution imagery, resulting in better efficiencies for the AI-powered object detection and change monitoring algorithms.

We will probably be even able to capture videos from space (Sen) and observe our planet in real-time. Even better, we could even process all these data in space, thanks to expected developments in edge computing in the next decade, and just beam down the necessary analytics and insights we need, instead of the petabytes of data, like we do today. All of this is incredible. Like the app revolution enabled by the iPhone, data from space can enable a revolution of applications to help us build a sustainable future, to understand our planet and make better business decisions. But what if …

The Bubble Bursts

A lot of innovations pass through the trough of disillusionment and never make it back to the slope. How likely is that some of the innovations mentioned earlier never reach their commercial potential and crash out of the market? Based on the history of technology innovation, quite likely. So, what can we do to minimise them?

Insights, not pixels

As an ex-software engineer, playing with pixels of imagery from satellites has been the coolest thing I have done recently, combining different types of data from space and trying to develop algorithms to automatically spot emissions from factories and training the algorithm to detect building in a packed city (hint: I failed!). This was probably because I am very passionate about Earth observation and the insights we can get out of satellite data. Unfortunately, I don’t think the vast majority of users want to go through this process, except the imagery specialists who love their raster data, geospatial platforms and maps. Sure, satellite imagery is cool, but I have found that more people are ready to give the images likes on social media than there are to spend money on them. Worse, even the pixel lovers find it extremely to acquire satellite data — both at the right price and at the right time. One of the popular ones believes that the current business model of selling pixels is broken. Marketplaces and cloud-enabled platforms may fix that problem for the minority of geospatial users, but the vast majority of data analysts and software engineers need analytics & insights spoonfed to them. I am guessing that they will happily pay, the right price, for something that makes their day job easier and fills a gap that they didn’t know could be solved with data from space. And, of course, unless we commoditise the data, we might not able to leverage all the insights we could, and the iPhone moment will perhaps never come. Perhaps, it is time to focus more on insights and less on pixels.

2. Solve problems using satellite data, not hoping for satellite data to solve some problems

I moved to the space industry a few years ago, and got into the world of Earth observation serendipitously. I am neither an expert in satellite manufacturing, nor a remote sensing scientist. I have neither built a unicorn company in this sector, nor invested capital into companies. But, something that I do know is people start companies is to try and solve problems, hopefully in a commercially viable way, with some level of market pull i.e. customers ready to pay for that solution. Unfortunately, there is a lot of technology push within the Earth observation industry, without any sort of market pull. Several companies develop new technologies and then hope to find problems to solve using technology. Shouldn’t we be starting companies focusing on solving problems first based on the technology? The reality is we are not even sure what the total addressable market is, and the kind of demand that exists for solutions based on satellite data. In fact, the solutions created are just being matched to solve potential problems. In other words, the innovations are being made to wait for its magical billion-dollar market, instead of actually going and competing for the share of the pie. More often than not, this solution-based on-problem approach is only valid in the defence and security market, which has been in the plateau of productivity phase, for decades and will continue to be. So, if we do need to cross the chasm, we probably need to go out, talk to the paying customers and develop solutions to solve problems, probably with a vertical-centric approach.

3. Evangelise and democratise

Let’s be honest, even if we have figured out the challenges in licensing, distributing and pricing satellite data, focused on solving specific problems in verticals and emphasised selling insights than pixels, this technology is still not something people outside the “ bubble” easily understand. Apple heavily evangelised the Mac to developers — it was the first graphical user interface ever developed with applications, differing so much from the earlier command-based computers. To start the app ecosystem, Apple developed the SDK and made it extremely easy for developers to write code and publish it on their App Store (ok, Android made it easier!). This created a whole job profile in the world — app developers, who still kind of rule the job market, along with data analysts and software engineers. This was all possible because Apple and Google decided to play the long-term game, opened up their technology and evangelised their app ecosystems. So, there is no use if we actively evangelise our innovation and do great marketing while the actual data is locked up somewhere accessible only through complicated licensing, distributing and pricing. If we want this to be our iPhone moment, we might want to focus on value creation in the application layer, than on the data and platform layers, allowing for actual democratisation of the data.

Do I really think all the innovations will make it past the trough of disillusionment? No, but I hope that they do in some form or the other. I am not a pessimist, in fact, I am quite the opposite. I switched careers into the space industry because I am sincerely passionate and excited about the potential of applications of space technologies. The dreamer inside me believes that Earth observation data will definitely unlock multiple multi-billion-dollar markets across verticals, traversing throughout the value chain with benefits becoming harder to quantify — similar to how data from navigation satellites have become the core of the app economy. Just like how the unicorns of the past decade— Uber, Instacart and Tinder etc. — are not considered space-tech companies (but still heavily rely on space technologies), I believe the unicorns of the next decade will start to rely on Earth observation data based on some of the innovations mentioned above. We just need to make sure we do not slide through the trough and let the bubble burst. I am convinced that we are passing through the iPhone moment for Earth observation and the space industry in general. If you are curious about what will be my part, please watch this space for some updates in the new year.

Post Scriptum

I started the “Hype Cycle” analysis as a personal research activity, and somehow I ended up doing the exercise for the overall space industry. I really do believe that this iPhone moment is going to continue for the next few decades, as we continue working on the innovations across the space industry. I may or may not a post on this in the new year. But I just wanted to leave it here, for your feedback and comments during the holiday period. As mentioned before, even the world’s best technology analysts failed in their predictions of the iPhone in 2007, so in reality, you probably shouldn’t take this amateur analyst too seriously!