Mapping the Blue Frontier: The Ocean's Hidden Economy

Mapping the Blue Frontier: The Ocean's Hidden Economy

MAPPING THE BLUE FRONTIER: THE OCEAN'S HIDDEN ECONOMY

INTRO:
Welcome to the Esri and the Science of Where podcast. We barely understand what covers most of our planet, the ocean. Because the ocean is constantly in motion, it's harder to analyze the rich information beneath the waves. Pooja Mahapatra studies ocean data to support both the blue economy and protect our coastlines.

She says that even simple seagrass is the ocean equivalent of the Amazonian rainforest.

POOJA MAHAPATRA:
Seagrass, not to be confused with seaweed, is actually grass that grows on the seafloor. But seagrass is actually a kind of infrastructure. It protects coastlines, nurtures fisheries, and locks away carbon. So it's a triple win.

INTRO:
Pooja Mahapatra tells Esri's John Lenahan how a deeper understanding of the ocean is fundamental to life.

JOHN LENAHAN:
Hi, Pooja, and welcome to the Esri and the Science of Where podcast.

POOJA MAHAPATRA:
Thank you for having me.

JOHN LENAHAN:
Pooja, I had the chance to visit your offices, and the work you're doing is fascinating, so let's start there. Can you tell us what Fugro does?

POOJA MAHAPATRA:
Sure. If you've ever wondered who maps the parts of the planet that you don't see on Google Maps, that's us. We're a global geodata specialist. We help our clients understand the surface and the subsurface of the Earth, and that covers the land, the sea, and the land beneath the seabed.

It also includes the tricky bits that are wet, wavy, and miles from shore. Think of Fugro as giving the planet an MRI scan so that engineers, governments, communities, and others can make safe and sustainable decisions.

Our traditional base includes offshore wind, the energy world, infrastructure, and governments. If you think of an offshore wind farm, before you even build it, we scan the seabed to ensure that turbine foundations don't wobble around. We're increasingly working with the likes of tourism, insurance, fisheries, and coastal cities that are seeking resilience.

JOHN LENAHAN:
Pooja, can you tell me about your role at Fugro?

POOJA MAHAPATRA:
I lead strategy for our solutions on the topic of climate and nature. Essentially, I help turn complex data into actionable decisions and try to build the governance, partnerships, and product pathways to actually make that stick. My team's job is essentially to shrink the distance between measurement and meaning.

JOHN LENAHAN:
You're talking about coastal resilience data and ocean data, but I've also heard you talk about organizations being data-rich but information-poor. Can you translate that to the data they're collecting about the ocean and the opportunity organizations have?

POOJA MAHAPATRA:
Indeed, data-rich but information-poor. I'll go back to my example of Google Maps. If you go to Google Maps and go into the ocean, you'll most likely see an expanse of blue on your screen. You can zoom in all you like. All you'll see is blue pixels. Google Maps doesn't really help you in the ocean. Why is that?

There are two reasons. First of all, the ocean is vast, and it's really expensive to get meaningful data from the ocean and from the ocean floor, which means that it's still largely unmapped. As of the middle of this year, only about 27 percent of the world's ocean floor has been mapped to modern standards.

In fact, we know a lot more about the moon and Mars than we know about our own seafloor. There's a whole expanse of water above the seafloor, between the surface and the seafloor, that we know virtually nothing about. I think we know less than 4 percent of it.

You have all kinds of variety on the seafloor. You have very flat areas. You have mountains even taller than Mount Everest on the seafloor. Mapping the seafloor gives you the exact shape and contours, as well as other parameters that classify it. You might know that there's a certain amount of coral cover here or a certain amount of seagrass there.

Ocean data is often very fragmented. It's really tough for a coastal planner to stitch it all together into one clear decision because no one cares about data. They need the answers to their questions. That's why it's really important to have open, interoperable systems. We work very closely with the UN Ocean Decade, and that's something they really champion.

That's why it's critical to have this sort of information rather than just heaps and heaps of data that no one can really make sense of.

JOHN LENAHAN:
Pooja, this is a good opportunity to pivot to this idea of the blue economy, as it's called. It refers to the many industries reliant on the ocean, from coastal fishing to Caribbean tourism, let's say. What kind of information do these participants in the blue economy need about the ocean that you're providing?

POOJA MAHAPATRA:
The beauty of data is that you capture it once, and you can use it for so many different things. If you think of cruise lines and shipping, questions that they would typically ask are, "Where are currents today? Where are the shoals today? What sort of routing would save fuel and time?"

If you think of a tourism board, they might be concerned about things like, "Is my beach stable? Where should we plant seagrass, or where should we restore reefs as natural breakwaters?"

If you think of fishers and aquaculture, questions they may typically ask are, "How are habitats shifting? Can we forecast water quality?"

And then if you think of the financial sectors, like insurers or lenders, what they might be interested in is, "What is the compound coastal risk? If you look at storm surge, sea level rise, erosion, and all of that together, how do we price this risk?"

It's not really just science that we're talking about when we talk about having good data and good analytics. It's really about livelihoods. The better the data, the fairer and faster the decisions will be.

JOHN LENAHAN:
And I imagine with a lot of these industries and organizations, they don't know what they need. How do you help them understand what data they can harness from the ocean that you're providing?

POOJA MAHAPATRA:
You bring up a great point, and that's something we've been thinking really hard about, because data is really only useful if it's relevant and timely. For that, you do need expertise.

The great part about working at Fugro is that we have access to a whole toolbox of data collection technologies, modeling technologies, and visualization technologies. Partnering with Esri only multiplies our capabilities even further.

Because we have this range of technologies, what we're doing together is building AI-assisted tools to automate some of this expertise. If we're able to train these AI systems with the expertise that we've gathered as Fugro and Esri over the last 60, 70, or 80 years that we've been around, we could enable users to just ask a question in plain language.

You could say something like, "Where is my erosion risk for the next 10 years on this beach?" That is not a data question. That is a question that will enable this person to make decisions about their property, for instance.

If an AI could convert that into, "This is what you need to be able to determine that erosion risk," give you the right level of datasets, and enable you to make the right decision based on the right data, then we think we're succeeding. Ideally, you need to know nothing about data to be able to make these decisions.

JOHN LENAHAN:
So Pooja, it's really about removing some of the complexity of asking questions of the data and getting value from the data.

POOJA MAHAPATRA:
Exactly.

JOHN LENAHAN:
What are some of the risks if these organizations or industries don't get a complete picture of the data that's relevant to their industry or their problem?

POOJA MAHAPATRA:
I've thought a lot about this, and I think the best analogy I can think of is driving. I have terrible eyesight. I have pretty thick glasses. I would never get into a car and drive without my glasses, and I would not advise anyone else to do so because, while driving, the world is still there, but the details that actually keep you safe are a big blur.

Making nearsighted decisions is always a mistake in the long run. It always costs so much more to undo or redo later on. Having good data is like having the right pair of glasses while you're driving, so you can make the right decisions as you go, course-correct as you go, and don't get into big trouble if you make the wrong decision.

JOHN LENAHAN:
I love that analogy, Pooja. It really drives home the importance of relevant data. What do you think the future holds for ocean science, the blue economy, and those companies and communities that are deeply linked to the oceans?

POOJA MAHAPATRA:
From all of my years looking at the ocean and looking at data, I think I see three big shifts.

The first is having AI-driven ocean digital twins. You probably know what a digital twin is. It is a digital replica of the physical world. As the physical world changes, the digital replica also changes, and that enables you to make decisions from behind your desktop.

Having streaming bathymetry layers, but also waves, habitats, infrastructure, and risks, in living models that actually forecast and predict when changes can happen is a bit like your weather app giving you a weather forecast. It tells you it's going to rain in half an hour.

Soon, we should be at a point where we can check other parameters just like we check the weather. For instance, you can check coastal risk. You can check the state of biodiversity. You can check how many fish are in your little aquaculture plot. You should be able to do that in an app just like you check the weather, and that would change everything for planners, insurers, and communities.

The second big shift is the world thinking of nature-positive design as a default. As a planet, we need to move to hybrid solutions that combine engineered defenses and structures with ecosystems.

You can think of mangroves, seagrasses, or coral reefs as frontline protection. Why is this important? Because biodiversity, all of those colorful fish and coral reefs that you see in beautiful nature movies, isn't just beautiful. It is actually functional.

Healthy ecosystems can dampen storm surges, stabilize shorelines, store carbon, and support fisheries. The co-benefits are immense. I definitely see a movement toward valuing nature as a resource, to a point where basically we should be able to put a dollar value on any kind of ecosystem.

Because, unfortunately, we live in a world where the predominant language is money, I think that will be an important step toward ensuring that nature-positive thinking becomes part of our decisions.

The third big shift I see coming is the transition toward autonomous and space-enabled mapping at scale. It's already starting, but the future is really about robots and satellites working in tandem.

Satellite analytics let us map water depth, clarity, and habitats all the way from space. That means a fusion between continental-scale mapping and very detailed insights without a single ship leaving port. I see this shift toward autonomous and space-enabled technology really enabling that ambitious target of mapping the entire seabed by 2030.

JOHN LENAHAN:
Now that we've talked about bathymetry, how do you collect data about the ocean? What are the techniques? What are the technologies? How do you do it?

POOJA MAHAPATRA:
Imagine the medical analogy again. It's like using X-rays, MRIs, ultrasounds, the whole suite of tools to really understand the human body, except it's for the ocean.

For instance, when it's shallow and the water is very clear, we can very easily see through all of that using satellite data. If you want to go a little bit deeper, and especially if you want to look at it in a lot more detail in three dimensions, we use a technique called lidar. Lidar helps you paint the nearshore environment in exquisite 3D detail.

It's quite easy in shallow waters because light can penetrate quite well. But as you go deeper, the light dies out at a certain depth. Deep below the ocean surface, it gets quite dark, so optical technologies don't really work. You need to start using sound for mapping.

In those deeper waters, we use a technology called multibeam sonar, a sound-based technology, to really map those depths. As we want more detailed maps, we start using smaller vehicles equipped with these kinds of sensors that actually go closer range. You can call them little robots that go underwater and collect this information. That really gets us to understand the details of the sea.

We have a whole range of tools in our toolbox, everything from satellite data, drones, and planes to large vessels that can collect data in the depths of the ocean, as well as robots, uncrewed vessels, and AUVs, autonomous underwater vehicles, that can collect data very close to the seabed.

The great part about using these technologies is that quite often you don't need to have people going out into the ocean for months on end to collect data. That keeps them out of harm's way. It also reduces emissions. And, of course, robots don't really get seasick.

I could give you an example of a project where we are actually using all of these different technologies to solve one problem. This is a project we're doing in Italy.

I don't know if you've heard of seagrass. Not to be confused with seaweed. It's actually grass that grows on the seafloor. Most people haven't heard of seagrass because, hey, out of sight, out of mind. You don't see it unless you actually go underwater.

But seagrass is actually a kind of infrastructure. Healthy seagrass meadows protect coastlines, nurture fisheries, and lock away carbon, so it's a triple win. In fact, these seagrass meadows also reduce wave energy by up to 50 percent, which makes them very nice to have on a coastline that's prone to storm surges.

They also store carbon dioxide almost 35 times faster than tropical rainforests. But they're disappearing because our oceans are warming and getting more acidic. They are disappearing at the rate of approximately a football field every 30 minutes, so that's really concerning.

In Italy, they have a program called the Marine Ecosystem Restoration Program, and what they've undertaken is mapping the seagrass across the entire coastline. We're talking about almost 8,000 kilometers of coastline.

You don't want to take 20 years to map this because you don't want the data to be old as soon as you're done with the project. We're putting together 13 different technologies, ranging from satellites all the way to robots on the seabed, to get that big-picture information across the whole country, but also to the level of detail of every individual leaf to really check which parts of the seagrass are healthy and which are not.

This is informing the government so it can make restoration plans and prioritize areas to work on first. It's about data collection, but with all of the analytics and insights that will enable them to make these decisions.

JOHN LENAHAN:
So seagrass is one very important driver and reason. What are some of the other reasons it's important that we collect data about the oceans and the coast?

POOJA MAHAPATRA:
The ocean is really the life-support system of the planet, and it's also a massive economic engine. Think of everything from food and shipping to tourism and even the internet itself.

Believe it or not, over 95 percent of intercontinental data traffic flows through subsea cables, cables that are on the seafloor. You need to be able to install these cables. You need to be able to maintain these cables. All of that needs data.

We cannot manage what we cannot measure, and there's a lot of subsea infrastructure on the seafloor. Telecom cables are one example. But you can also imagine energy pipelines. All of that needs to be mapped, maintained, and monitored.

Mapping the seafloor also underpins things such as tsunami early warning systems. So when we say mapping the ocean, it really is about protecting people, economies, and ecosystems.

I talk about biodiversity and climate change as two sides of the same coin because you can't solve one without solving the other.

JOHN LENAHAN:
Thank you, Pooja, for joining us and speaking to the listeners. It's been great having you, and thanks again.

POOJA MAHAPATRA:
Thank you for having me.

OUTRO:
Thanks for listening to the Esri and the Science of Where podcast, and thanks to Pooja Mahapatra. If you liked this episode, please share it with a colleague.