Space-based imagery and data collection, long the preserve of governments and scientists, is coming down to earth, says Alistair Maclenan.
Sixty years ago this August, the American satellite Explorer VI took the very first, crude and scratchy picture of the Earth from space. At that time, it would have taken a lot of imagination to foresee what was to follow: an armada of earth observation satellites, placed into orbit by a multibillion-dollar industry to image every spot of the Earth’s surface.
Our capacity to monitor our planet from space has grown spectacularly over the intervening decades. In the beginning, it was only the governments of the world’s richest countries who could marshal the staggering amounts of money, technology and expertise needed to launch a camera roughly the size and weight of a large car into orbit, keep it there and get it to relay its view of our home planet back to teams of waiting scientists.
More recently, deep-pocketed corporations have joined them: their efforts are reflected in the number of people who are comfortable using online satellite maps, for example. However, it has been a small minority that has benefited from space-based monitoring and management of natural and man-made resources. Now, everything is changing.
The cost of sending satellites into space is dropping fast, partly due to a vertiginous drop in the size of the sensors that can now deliver usable imagery from space. Many of today’s earth observation satellites are no bigger than a shoe box and weigh roughly the same as five bags of sugar. CubeSats – prosaically named, as they are ten-centimetre cubes – are small, light and thus relatively inexpensive to build and launch.
So now satellites are within range of organisations that would never previously have been able to contemplate their own earth observation capabilities: poorer countries, smaller companies, universities and organisations with niche interests that were overlooked when the focus was on huge, extremely expensive platforms.
This new hardware has become viable at the same time as new processing software has arrived. Artificial intelligence (AI) systems, drawing on the cloud’s seemingly unlimited processing power and storage, are teaching themselves how to pick out ever-more valuable information from an ever-expanding amount of earth observation data.
In 1991, marketing writer Geoffrey Moore argued that for any technology to be successful, it must ford the chasm that exists between the small number of early adopters and the massed ranks of the “early majority”. Earth observation is ready to take the long leap across that chasm and become a mainstream application.
Satellites are within range of organisations that would never previously have been able to contemplate their own earth observation capabilities.
To most people, ‘space’ means an astronaut tethered to the outside of the International Space Station, wielding the world’s most expensive spanner. Fewer link it with satellites and sensors – earth observation people get upset if you call them cameras – orbiting hundreds of miles above their heads. But it’s the latter that’s arguably made the bigger difference to life here on earth.
In 1972, just a few years after Apollo 11 had ferried three men to the moon and back, America’s National Aeronautics and Space Administration (NASA) successfully launched their Earth Resources Technology satellite - later dubbed Landsat – into orbit above a largely unsuspecting population. Whilst the returning astronauts rightly received a ticker-tape parade through the streets of New York, the team that designed and operated what became the first satellite of the world’s longest running earth observation programme, has been completely overlooked.
And, without trying to sound too much like a petulant six-year old, that’s not fair. The Landsat series of satellites – models 7 and 8 are in operational orbit and 9 is planned for a 2020 launch – has provided over eight million individual scenes (or photographs, if you insist) of the Earth’s surface. NASA has gone on to develop an extensive range of other earth observation platforms, as have the space agencies of France, India, Brazil, Nigeria, China, Sweden, Japan, Kazakhstan, South Korea, Argentina, Dubai, Indonesia, Russia and Europe.
Imagery from these platforms has been used to find energy sources, manage responses to natural disasters, plan the development of cities and transport networks...
Imagery from these platforms has been used to find energy sources, manage responses to natural disasters, plan the development of cities and transport networks, report the effects of climate change and increase the number of people on earth who can drink safe water, breathe clean air and have enough food to eat. Earth observation is used to track the progress of each of the seventeen Sustainable Development Goals set by the United Nations in 2015.
However, these state-backed programmes have mainly consisted of large, single satellites. Useful as they are for getting a macroscopic picture of life on earth – the type of big picture overviews useful to governments – they do not provide the kinds of data that would make earth observation useful to everyone. That is, there is no reason to jump Geoffrey Moore’s market chasm.
So, the question remains: can space-based imagery be made as simple and useful as, say, location information from GPS?
Let’s take a step back. A photograph provides a record of what was where at a given point in time. That’s why, for example, the police use them to record evidence at crime scenes. Earth observation scenes perform that same function but over an area of hundreds of square miles and using wavelengths of light beyond those visible to humans. In fact, they are used for police work too: illegal shipping, logging and construction can all be detected and tracked from space.
But since a single satellite takes around fifteen days to return to the same spot, those dodgy ships can be a long way away before action can be taken. As can a lorry-load of lumber. An illegal road bulldozed through a nature reserve won’t go away, but by the time the satellite confirms the construction has taken place, the damage will have been done.
Improving the effectiveness of this monitoring means taking pictures more frequently. But since a satellite’s orbital speed is constant, the only way to achieve this is to increase the number of satellites in orbit. Two satellites will halve the time between images of the same part of the planet. Four will quarter it. Eight will… well, you get the point. As did several companies, who raised hundreds of millions of dollars of private capital to build constellations of tiny satellites.
Like the smartphone market that this development mirrors, the increased use of standardised components and mainstream programming languages means more people can work within the industry.
In early 2017, the Indian Space Research Organisation (ISRO) set a world record by launching one hundred and four satellites from a single rocket, eighty-eight of them ‘Doves’ – three CubeSats stuck together. They were built by Planet, a San Francisco-based company which has raised over US$300 million, as part of a push to image the entire Earth every day.
That kind of feat will soon become less exceptional. Late last year, as part of the European Space Agency’s Space 4.0 strategy, five companies presented their progress towards providing commercially-viable ‘micro-launchers’. These mini-rockets will carry around 350 kilograms or less. That’s tiny by the satellite industry’s standards, but it’s enough to deliver nano-satellites into space and will encourage the development of new launch sites such as those proposed in Scotland, New Zealand and the Azores.
Constellations of low-cost satellites offer obvious redundancy benefits – losing one of a group of 100 satellites doesn’t mean the mission is over as it would if that was the only satellite – but they also accelerate their own development. If something isn’t working or could be done better, no problem. Just swap in a new component or upgrade the software and launch the new satellite. When a satellite cost half a billion and took four years to build, that was impossible.
And like the smartphone market that this development mirrors, the increased use of standardised components and mainstream programming languages means more people can work within the industry. It’s not just for rocket scientists any more.
CubeSats’ diminutive size means they have their limitations. Their spatial resolution is comparatively feeble: they can only discern objects on the ground that are more than about three metres in length, whilst their one-tonne cousins can pick out a schoolchild’s regulation thirty-centimetre ruler. However, it is the incredible improvements they offer in temporal resolution that have been a driving force in new applications.
For example, organisations tasked with protecting the world’s forests no longer need to have one “eye in the sky”. They can now cast their gaze over areas of interest often enough to take preventative action, rather than just providing forlorn images of scarred landscapes for inclusion in yet another report about how bad illegal deforestation is getting.
And they can enlist help. If the smartphone has given individuals the chance to be news photographers, daily earth observation can provide the chance for everyone to be a local environmental champion. Daily updates will allow people to monitor their own streets, villages and towns and to contribute evidence to local governance.
So, job done? Well, not quite. Every technological advance produces new challenges alongside its benefits. More data isn’t, in and of itself more useful. It only becomes useful when it is turned into information that can support better decision making. Mapping the planet everyday creates petabytes of imagery – more than even an army of analysts could work through in search of insight before the next day’s images arrive.
Daily updates will allow people to monitor their own streets, villages and towns and to contribute evidence to local governance.
That brings us to the last plank of our chasm-spanning bridge: artificial intelligence. AI is still very much an infant industry but the amount of money and attention being lavished on it, reflect the potential and the need for it to be up and running as soon as possible.
There are over seventy companies listed on the European Space Agency’s “Food & Agriculture” web page, many of them start-ups, who are working to deliver the information that food-producers need to keep feeding a hungry planet, using data made freely available by ESA’s Copernicus programme - a hugely ambitious mission that has so far seen the agency launch seven ‘Sentinel’ satellites and provide a vast library of observation imagery. Ceaseless algorithms sift all types of earth observation data, combined with that collected from in-situ sensors, weather forecasts and so on, to provide farmers with ‘actionable’ information about the health of their crops.
A prime example of this is the British-based agronomy company Agrimetrics which, in partnership with Airbus and Microsoft, is using AI to delineate the boundaries of all 1.45 million fields in the UK and attach environmental, soil and crop information to each field. Farmers will be sent analyses of this remarkable dataset to help them make more timely decisions as to when to apply nutrients or herbicides and increase their yields. Aggregating this kind of information will also allow other companies to provide those further down the food delivery chain with early predictions about short-falls or gluts in a specific crop or food. That should help ensure availability in supermarkets whilst mitigating price spikes – a mounting concern as climate change continues to kick in.
Earth observation is unquestionably at a tipping-point. The combination of cheaper hardware, easier access to space and insight-on-demand from artificial intelligence are the foundations of a bridge over Moore’s market chasm.
But will the industry actually cross over to the mass market? Both GPS and weather forecasting have made the trip; who doesn’t pick up their phone to find out the best route to their destination or to know if they will need an umbrella when they get there? And we use both without understanding the underlying science of either technology.
As we have seen, earth observation already has an indirect influence on people’s lives, whether it is helping their food to grow, making their cities safer or ensuring their homes are heated or cooled. It will have a direct impact when suppliers place each user at the origin of the image – as online maps already do – and tailors the information to their hyper-local needs.
Now individuals have the chance to understand their impact on their own environment – and crucially, to act upon that understanding to the benefit of themselves and everyone else.
Monitoring air quality or the heat loss from our homes, for example, are just two of the many measurements that have previously been performed by the state, or which require a costly ground-based survey. But now individuals have the chance to understand their impact on their own environment – and crucially, to act upon that understanding to the benefit of themselves and everyone else. Those in power will need to work out how to sustainably feed, house and move a growing population on a finite land-mass with finite resources; each of us needs to understand our roles and responsibilities within the solutions they come up with.
Technologies drawn from every scientific discipline on earth will be needed to respond to these challenges. But the view from above them all, looking down on every square inch of the planet, might just be the one that provides the answers.
Alistair Maclenan has worked within the geospatial and earth observation industry for twenty years, and runs the specialist marketing agency, Quarry One Eleven. He is also the Chair of The British Association of Remote Sensing Companies.