Mapping the Blue Frontier: The Ocean's Hidden Economy

Mapping the Blue Frontier: The Ocean's Hidden Economy

mappingthebluefrontiertheoceanshiddeneconomy2
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Speaker: [00:00:00] 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.

Speaker 2: Seagrass, not to be confused with seaweed, is actually grass that grows on the sea floor. But seagrass is actually a kind of infrastructure. They protect the coastlines, they nurture fisheries, and they lock away carbon.

So it's a triple win.

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

Speaker 3: Hi, Puja, and welcome to Esri and the Science of Where Podcast

Speaker 2: Thank you for having me.

Speaker 3: Pooja, I had the chance to visit your offices, and the work you're doing is fascinating, so let's start [00:01:00] there.

Can you tell us what Fugro does?

Speaker 2: Sure. If you've ever wondered who maps the parts of the planet that you don't see on Google Maps, that's us. So we're a global geo data specialist. We help our clients understand the surface and the subsurface of the Earth, and that covers the land, the sea, the land beneath the seabed.

It also includes the tricky bits that are wet and wavy and miles from shore. So think of Fugro as giving the planet an MRI scan so that engineers, governments, communities, et cetera, can all make safe and sustainable decisions. Our traditional base includes, uh, offshore wind, so the energy, uh, the energy world, um, infrastructure and governments.

So if you think of, uh, of an, of an offshore wind farm, before you even build an offshore wind farm, we scan the seabed to ensure that turbine foundations don't wobble around, you know? We're increasingly working with the likes of tourism or, or insurances or, or fisheries and coastal cities that are, that are [00:02:00] seeking, uh, resilience.

Speaker 3: Pooja, can you tell me about your role at Fugro?

Speaker 2: Um, so 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, the partnership, and the product pathways to actually make that stick. My team's job is essentially to shrink the distance between measurement and meaning.

Speaker 3: So you're talking about coastal resilience data, you're talking about ocean data, but I've also heard you, Pooja, talk about organizations being data rich but information poor. Can you kind of translate that to the, the data that they're collecting about the ocean and, and the opportunity that organizations have?

Speaker 2: Indeed, data rich but information poor. Um, I'll go back to my example of Google Maps, right? So if you go to Google Maps and you go into the ocean, you'll most likely see an expanse of blue on your screen. You can zoom in all you like. All that you'll see is blue pixels, right? So Google Maps doesn't really help you in the [00:03:00] ocean, and why is that?

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

Um, in fact, uh, we, we know a lot more about the moon and, and about Mars than we know about our own sea floor. There's a whole expanse of, of water above the sea floor between the surface and the sea floor that we know virtually nothing about. Um, I think we know less than 4% of it. You have all kinds of variety on the sea floor.

You have very flat areas. You have mountains even taller than Mount Everest on the sea floor. So mapping of the sea floor to give you the exact shape and contours of the, of the shape, uh, and, and other parameters that, that, that belong, so, so classifying the sea floor into different kinds of parameters- Uh, you know that there is, there is a certain amount of coral cover here, there's a certain amount of, you know, seagrass there.[00:04:00]

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. And that's why it's really important to have, you know, open interoperable systems. Um, and, and we work very closely with the UN Ocean Decade, uh, and that's something they really champion.

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

Speaker 3: Pooja, this is a good opportunity to pivot to this idea of, of the blue economy, uh, as it's called. It, 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, um, participants in the blue economy need about the ocean that you're really providing?

Speaker 2: The beauty of data is that you capture the data once, and you can use the data for so many different things. Um, if you think of cruise lines and shipping, right? [00:05:00] 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?" Right? If you think of a tourism board, they might be concerned about things like, you know, is my beach stable? Where should we plant sea grass, or where should we restore reefs as natural breakwaters? Uh, if you think of fishers and, and aquaculture, um, questions that they may typically ask are, you know, how are habitats shifting?

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

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

Speaker 3: And I imagine with a lot of these industries, a lot of these organizations, they don't know what they need.

How do you help them [00:06:00] understand what data they can harness from, from the ocean that you're providing?

Speaker 2: Uh, you bring up a great point, and that's something we, we have been thinking really hard about, um, because data is really only useful if it's relevant and timely. Um, and for that, you do need expertise.

The great part about working at Fugro is that we have access to a whole toolbox of, of data collection technologies, modeling technologies, visualization technologies, and partnering with yourselves at Esri, that, that only multiplies our capabilities even further. Because we have this range of different technologies, and what we're doing together actually is, is building these sort of AI-assisted tools to automate some of this expertise.

So if we're able to train these AI with the expertise that we've gathered as Fugro, as Esri, over the last, I don't know, 60, 70, 80 years that we've been around, um We could enable users to just ask a question in plain language, right? So you could say something like, "Where is my [00:07:00] erosion risk for the next 10 years on this beach?"

Now, that is not a data question. That is a question that will enable this person to, um, to make decisions about their property, for instance. Now, if an AI could convert that into, "This is what you need to be able to determine that erosion risk," and give you the right level of datasets, enable you to, you know, um, make the right decision based off the right data, then we think we're, we're, we're, uh, we're succeeding.

Um, and ideally, you need to know nothing about data, um, uh, to be able to make these, uh, to make, to, to be able to make these decisions.

Speaker 3: So Pooja, it's really about removing some of the complexity, uh, of asking questions of the data and, and getting value from the data.

Speaker 2: Exactly.

Speaker 3: So what are some of the risks if these organizations or these industries don't get a complete picture of the data that's relevant to their industry or their problem?

Speaker 2: Yeah, I've thought a lot about this, and I think the best analogy that I can think of is, is with driving. [00:08:00] So 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, are a big blur, right?

And making nearsighted decisions is always a mistake on the long run. It always costs so much more to undo or redo later on. So, uh, 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, you can course-correct as you go, and you don't get into big, big trouble if, uh, if, if you make the wrong decision.

Speaker 3: I love that analogy, Pooja. It really kind of drives home the point of, of the importance of relevant data. What do you think the future holds for ocean science, the blue economy, and those companies, communities that are deeply linked to the oceans?

Speaker 2: So, um, from all of my years now looking, looking at the ocean, looking at data, I think I see three big shifts.[00:09:00]

The first is having AI-driven ocean digital twins. So, uh, you probably know what a digital twin is. It is a digital replica of the physical world. So as the physical world changes, the digital replica also changes, and that enables you to make decisions from behind your desktop. Now, having, you know, streaming bathymetry layers, but also waves and habitats and infrastructure and risks into living models that actually forecast and actually predict, uh, you know, when, when changes can happen, it's a bit like your, your weather app gives you a weather forecast, right?

It tells you it's gonna rain in half an hour. Um, but then, um, you know, soon we, we should be at a point where we can check other kinds of parameters, just like we check the weather. So for instance, you can check coastal risk. You can check the state of the biodiversity. Uh, you can check how many fish are in your little aquaculture plot.

You, you should be able to do that in- on an app just like you check the weather, and that would change, I think, everything for planners, for insur- insurers, and for communities. The second big shift I can think of [00:10:00] is the world thinking nature positive design as a default. I think we are... As a, as a planet, we need to move to hybrid solutions that combined, combine engineering defenses, engineering, uh, structures with ecosystems.

Now, you can think of mangroves or sea grasses or coral reefs as, you know, frontline protection And why, why is this important? It's because biodiversity, you know, all of those colorful fish and coral reefs that you see in all of these beautiful nature movies, it's not just beautiful, it actually is functional.

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

And b- because unfortunately we live in a world where, where the predominant language is money, um, I think [00:11:00] that will be an important step towards, uh, towards ensuring that, um, um, yeah, that, that nature positive becomes a part of our thinking. So the third, uh, the third big shift that I, that I see coming is that, uh, that transition towards autonomous and space-enabled mapping at scale.

It's already starting, but the future is really about robots and satellites working in tandem. And, you know, satellite analytics, they let us map water depth, clarity, habitats all the way from space. So that means that fusion between continental scale mapping and very detailed insights without a single ship leaving port.

But I, I see this, this sort of shift towards autonomous in space really enabling that opt- uh, ambitious target of mapping the entire seabed by 2030.

Speaker 3: So 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?

Speaker 2: So it's...

Imagine if you, if you make that medical analogy again, it's like using X-rays, MRIs, ultrasounds, the [00:12:00] whole suite of, of, of tools to really understand the human body, except it's for the ocean. So for instance, when it's shallow, when it's very clear water, we, we can very easily see through all of that using satellite data.

Um, and then if you want to go a little bit deeper, um, and especially if you want to look at it in, in a lot more detail in, in three dimensions, we use a technique called LiDAR. So LiDAR, uh, helps you really paint the nearshore environment in exquisite 3D, uh, detail. It's quite easy in shallow waters because light can penetrate quite, quite well.

But as you go deeper, um, the light di- dies out at a certain depth. Um, as you know, deep, uh, below the, the, the, the ocean surface, it gets quite dark. So then optical technologies don't really work. You need to start using sound for mapping. Uh, so at, at, at those deeper waters, we use a technology called multi-beam sonar, so it's, it's a sound-based technology, to really map those depths.

Um, and as we want more and more detailed maps, we start [00:13:00] using, uh, smaller vehicles equipped with these kind of sensors that actually go closer range. So you can call them little robots that go under the, uh, into the, onto the seabed, um, and collect this information. So that really gets us to, to, to understand the, um, uh, the details of the, of the sea.

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

The great part about using these technologies is quite often you don't need to have people anymore going out, uh, into the ocean for months on end to collect data Um, that keeps them out of harm's way. Um, it also reduces emissions. Um, and, and of course, robots don't really get seasick. So, um, I could give you an example of, of a project where we are [00:14:00] actually using all of these different technologies to solve one problem.

So, uh, this is a project we are actually doing in, in Italy. So, uh, one ... I don't know if, if, if you've heard of, uh, of, of, of sea grass. Not to be confused with seaweed. It's actually grass that grows on the sea floor. Now, most people haven't heard of sea grass because, hey, out of sight, out of mind. You don't see them unless you actually go underwater.

But sea grass is actually a kind of infrastructure. Healthy sea grass meadows, they protect the coastlines, they nurture fisheries, and they lock away carbon, so it's a triple win. In fact, these sea grass meadows also reduce wave energy by up to 50%, which makes it a very nice thing to have on a, on a c- on a coastline that's prone to, uh, uh, to storm surges.

Uh, but also they, they store carbon dioxide almost 35 times faster than tropical rainforests. But they're disappearing because, you know, our oceans are warming, they're getting more acidic. Um, they are disappearing at the rate of approximately a football field every 30 minutes, [00:15:00] so that's really, really concerning.

So, um, in Italy what they're doing is they have this program called the Marine Ecosystem Restoration Program, and what they've undertaken is mapping the sea grass across the entire coastline. We're talking about almost 8,000 kilometers of coastline. You don't want to take, like, 20 years to map this because you don't want the data to be old as soon as, you know, you're done with the project.

And we're putting together 13 different technologies, ranging from satellites all the way to robots in the seabed to, to, to get those, those big-picture information across the whole country, but also to the level of detail of every single individual leaf to really check, you know, which parts of the sea grass are healthy and which are not.

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

Speaker 3: So sea grass is one very important kind of driver and, and [00:16:00] reason.

What are some of the other reasons it's important that we collect data about the oceans and about the, uh, coast?

Speaker 2: The ocean is, is, I think, it, it is really the life support system of the planet, and it's also a massive economic engine. So everything you can think of, from food to shipping to tourism, to even the internet itself.

I mean, believe it or not, over 95% of intercontinental data traffic flows through sub-sea cables, so cables that are on the sea floor. And you need to be able to, you know, install these, uh, these cables. You need to be able to maintain these cables. All of that needs data. Uh, we cannot manage what we cannot measure, and there's a lot of sub-sea infrastructure on, on, on the sea floor.

So telecom cables is one of them. But you can also imagine energy pipelines. Um, all of that needs, needs, uh, needs to be mapped and, uh, needs to be maintained and monitored. Um, mapping the sea floor also underpins things such as tsunami early warning systems. So when we say mapping the ocean, it really is [00:17:00] about protecting.

It's about protecting people, economies, and ecosystems. I, I talk about biodiversity and climate change as two sides of the same coin because, uh, you can't solve one without solving the other.

Speaker 3: Thank you, Puja, for joining us and, and speaking to the, to the listeners. It's been great having you, and, um, thanks again.

Speaker 2: Thank you for having me.

Speaker: Thanks for listening to the Esri and the Science of Our podcast, and thanks to Puja Mahapatra. If you like this episode, please share it with a colleague