September 26, 2025 • 19 mins
Fighting overfishing with AI is transforming how we protect the ocean. A new study revealed that nearly half of all coastal marine protected areas (MPAs) showed fishing vessel presence, with many ships operating “dark” without AIS tracking. This means that even in places meant to be safe havens for biodiversity, industrial fishing has been creeping in unnoticed.
Satellites and artificial intelligence are changing that reality. By detecting untracked vessels and guiding patrols, this technology is already leading to arrests in Gabon, better enforcement in Palau, transparency in Chile, and effective oversight in the UK Blue Belt program. In this episode, I’ll break down the science behind the study, the risks remote MPAs face, and the real-world success stories that give us hope.
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Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:00):
illegal fishing vessels thoughtthat they can hide, but satellites
and AR are catching them in theact in marine protected areas.
Today I'll show you how thisnew technology is turning the
tide for ocean conservation.
When I read a recent study, I wasshocked to see how many fishing vessels
were detected inside marine protectedareas, especially the more remote ones.
(00:21):
These are places we imagine as untouched.
But in reality, they're often thehardest to enforce and the easiest
for illegal fishers to exploit.
That hit me personally because MPAsare supposed to be our ocean's havens.
but here's the good news.
Satellites and AI are changing the game.
We're finally catching vesselsthat thought that they can hide,
(00:42):
and enforcement is startingto get smarter and stronger.
In this episode of the How to Protectthe Ocean Podcast, I'm gonna share
real world examples of how these toolsare already protecting the ocean and
why it gives me hope for the future.
So let's start the show.
Hey everybody.
Welcome back to another exciting episodeof the How to Protect the Ocean Podcast.
I'm your host, Andrew Lewin, andthis is the podcast where you find
(01:04):
out what's happening with the ocean,how you can speak up for the ocean,
and what you can do to live fora better ocean by taking action.
Today we're gonna be talking abouta lot of different things, all
combined into one terrific story.
We got AI, we got satellite imagery,we got synthetic aperture radar,
which is like a really cool satellite.
We've got machine learning.
We got AIS, which is automaticidentification system.
(01:27):
we got marine protected areas.
We got illegal fishing, fishing boats.
There's all in one enforcement.
It's a very exciting story, allpacked in one research paper in
the research journal science.
Now we're gonna be going a little beyondthat because this research paper showed
an increase in illegal fishing activityin marine protected areas, especially
those that were further away from thecoast, so more remote, and they spent
(01:50):
longer within those time, four hours.
Per vessel in marine protectors per year.
Not a really great story in terms ofoptimism, but then I wanted to go a little
bit further and I found some examples ofopportunities where satellites, AI and
machine learning were used to detect anenforce, of course, and prevent further
(02:10):
illegal fishing in marine protected areas.
So we're gonna talk all aboutthat on today's episode,
which I can't wait to do that.
But first, before we get into that, ifyou are interested in marine stuff, you
wanna learn about the ocean, you wannalearn more about these conservation
stories, you can get more information eachand every weekday with our newsletter.
Just go to speak up for
(02:31):
That's speak up for blue.com, allone word slash newsletter to get
access to our newsletter and getinformation on ocean conservation
in your inbox five days a week.
It has all of our podcast stuff,news articles that are coming out,
something that's very interesting
each and every day, check it out.
Speak up for blue.com/newsletter.
Let's get back into the story.
(02:52):
This is really interesting.
So this is how they use it.
They use Synthetic Aperture, ApertureRadar SAR, satellite imagery,
combined with AIS data, which isAutomatic Identification System
and AI and machine learning todetect industrial fishing vessels.
So essentially what they didis they took the satellite
imagery, which is really cool.
It's not like your regular satellite.
It basically takes the surfaceof the water and makes it really
(03:15):
like an impenetrable marker.
it looks like concrete and then it takesfishing vessels and makes them dark.
So you can actually detect fishingvessels each and every way.
It's really cool.
They use it to monitor a lot,anything at the surface, they
know where the boundaries ofthe marine protected areas are.
They can find out where these fishingvessels are, so they overlay a map or a
polygon of where these boundaries are.
'cause they're invisible normally.
(03:35):
We don't see an actual physical barrierin the ocean that goes down the water
column to prevent people from coming inand fishing in marine protected areas.
Now, before we go further, marineprotected areas are areas where
they protect any kind of extractiveactivity, including illegal fishing.
It's usually to protect fish, allowsfish to grow bigger, allows fish
to grow more in terms of number andbigger so that they spill over the
(03:59):
boundaries of the marine protected areas.
And they get fished by fishermenlegally, but they're not allowed.
The fishermen are not allowedinside the boundaries of the marine
protected areas because that iswhere they're allowed to grow.
They're special areas, andso we need to protect them.
These fishing vessels willcome in because you know why?
Nobody's there to watch them.
Because the ocean is massiveand you can't just keep, you
(04:21):
know, boats there all the time.
It's expensive.
It's almost impossible to do that.
So we have satelliteimagery like sar, right?
the satellite imagery allows, thispicture to be taken at some point in time.
To find out if there's anyillegal boats that are in there.
AIS data, Automatic Identification System,is placed on some of these boats that
allows it and detects the GPS coordinatesof where they are at any point in time.
(04:45):
Well, within a certain interval.
I think sometimes it's seconds.
I've worked with this data before.
You could really see, like if you lookat worldwide and how this AIS has done
for those boats, which are still a lot.
Those boats that use it, you canactually see tracks all over the
world and where these boats havegone, what flags they're flying.
It's really cool data.
Hard to get ahold of.
It's usually managed and kept bythe Coast Guard, but I've worked
(05:05):
with it when I worked in government.
It's really cool data to have.
So you have these boats.
So you know where they are.
We know which boats are where,and then we have the satellite
imagery to detect which boats arewithin the marine protected areas.
And then you can findout basically on speed.
So if they're trolling, youcan see how they slow down.
All this different type of stuff, youcan find out all this with this data,
and of course, AI and machine learningcan quicken that processing speed so
(05:28):
you can catch 'em almost in the act.
So if they're coming to a border,you know where they're going.
You can like basically deploy CoastGuard vessels or whatever the vessels
are for each country to get outand to enforce this illegal fishing
activity to prevent it from happening.
So the faster the authoritiescan get on it, the better.
So AI and machine learning help it.
So you got satellites
and AIS to detect the illegal activity.
(05:49):
And you have AIS and machinelearning to deploy the enforcement,
to go out and catch them.
So that's what the story was essentially.
They focused on coastal marine protectedareas globally between 2022 and 2024.
Only coastal MPAs that are largerthan one kilometer squared were
considered since Ramona MPAs oftenlack consistent satellite data coverage.
(06:11):
Okay.
SAR satellite data coverage.
So prevalance of fishing in MPAs,they detected industrial fishing
happened in 47% of coastal MPAsworldwide during the study period.
So that's only within two years.
So many of the vessels detected 67% wereuntracked by public monitoring system.
So no AIS so the satellites candetect all the boats that are there.
(06:31):
The AIS can identify which boatshave AIS and which boats don't.
If you don't have AIS andyou just see a boat there.
Why aren't we being able to see this?
This is consistent with otherstudies that show 75% of the
fishing vessels around the world donot have AIS, they are untracked.
This is very scary in terms of what ishappening with fishing and illegal fishing
because we can't track these boats.
(06:52):
More effort needs to be done to trackevery single fishing vessel that is around
anywhere.
So having untracked vessels, not good.
So surprisingly, the most restrictiveMPAs where extractive activity is
supposed to be prohibited at all costs,still had a lot of untracked vessels.
About 80% of detections inthose MPAs were on track.
So that makes sense becausethey're not supposed to be there.
(07:14):
So why would you have atracked vessel in there?
So that makes sensebut still pretty scary.
So the effectiveness or the lack thereofwas not just tied to how restrictive
the MPA is, like legally from byIUCN standards, but more strongly
to remoteness and size of the MPA.
So large and remote MPAs hadmore phishing vessel detections.
Now, what's interesting to me isI wonder if we actually talk to
(07:36):
these fishers if they even careabout the boundaries or they are
just going where the fish are now.
Ideally in the marine protectiveareas because they work so well,
you will see bigger and more fish.
And so that's why they'reprobably going within those areas.
so the average fishing vessel inside theMPAs was around four hours per square
kilometer per year when both trackedand untracked vessels were counted.
(07:58):
That's a lot of time.
I know that sounds weird, but that'sa lot of time thinking about how often
these fishing vessels go into these areaswhere there's marine protected areas.
So that is somethingthat is not good, right?
That's a lot of time inthese marine protected areas.
So the density and presence of fishingvessels, so tracked and untraced in
MPAs correlate more strongly withMPA size and remoteness rather than
(08:18):
the formal protection category.
So it's not as if it's just, hey,it's protection, it's actually this
size and the remoteness of the MPA.
So here's the thing.
We do have gaps in monitoring, right?
That is one of the limitationsthat this study identifies.
So public tracking systems, AIS miss alarge portion of the phishing activity.
Untracked vessels make up a largeand major invisible pressure.
(08:41):
That's something that wecan't see through AIS.
If you can't see the data on a map,
it's really difficult, even thoughthere's so much data, there's so many
more vessels that are go on tracked.
We also have to worry about paper parks.
It's a risk when MPAs aredesignated, which takes a long
time to designate them when they'redesignated, they need to be enforced.
If they're not enforced, they'rejust considered paper parks,
meaning that they're on paper.
(09:02):
We see them on maps, but wedon't actually enforce them.
And so without the lack of sufficientenforcement and monitoring, we
may see considerable phishingin these areas, which kind of
nullifies the point of the MPA.
We also need to integrateOnTrack surveillance.
So using things like SAR, likethe satellite machine learning and
combining multiple data sources improvesunderstanding of true phishing pressor.
(09:25):
So a lot of the times when we do thesestudies, we have to understand how much
pressure there is in phishing withinthese MPAs or just around the world.
When you don't have the ability toidentify who's fishing and who's not,
or what's tracked and what's not trackedlike what fishing vessels aren't tracked,
we lose the ability to understandthe true phishing pressure.
So if we only look at trackedvessels, we only get a snapshot
(09:48):
of what's actually happening.
It's only a small representationwhen we have more vessels that
are untracked, this can't be done.
This is up to the fishing fleetsor even the countries that allow
fishing vessels to fly their flags.
That's a whole thing.
If you look at my recent interviewwith Dan Skerritt, you'll understand
what these flags do and how easyit is to manipulate these flags
(10:09):
and to fly under a different flag.
To be able to do prettymuch whatever you want.
When these countries are not enforcingany of their laws, or if they even have
laws, they may not have as many laws.
So in integrating this information,surveillance, so SAR machine
learning, AI, combining multiple datasources improves the understanding
of true phishing pressures.
Then you have model predictions.
(10:30):
So because of limitations, not allvessels are greater than 15 meters.
Variable satellite coverage, which ishard to get total satellite coverage
whenever you want because they'rein orbit and they only fly around
certain areas once or twice a day.
Distinguishing transitversus fishing vessels.
So some are just in transit, someare actually actively fishing.
And then the metrics that are estimates,actual fishing effort in some marine
(10:52):
protectors may be higher, especiallyin places with weaker AIS coverage.
So the fact that there's so manyvariables, we're not there physically
all the time, these enforcement people,and we are seeing it from like, you
know, orbit and we're seeing thingslike from a digital landscape, like
on a GIS or a mapping tool and onlyseeing data points and maybe missing
data points from untracked vessels.
(11:14):
There are a lot of underestimationsthat are happening right now, and we
have to assume that there's more fishingpressure around the world, especially
within these marine protected areas.
So now that's the bad news.
I know this a lot and I appreciate you.
You hand me the good news is coming.
There are a lot of things that wecan do and there are a lot of things
that are being done, and I thinkthat's something really interesting.
Detecting dark vessels with SAR and AI.
(11:36):
So here's how it works.
SAR satellites can detect ships.
I just kind of mentioned it, regardless ofthe weather or lightning, so that's good.
AI models match SAR detections with AISdata to flag quote unquote dark vessels.
Those that are not transmitting AIS.
So, like I said before, the satelliteimagery can actually detect what's
in the marine protected areaboundary, even though the AIS, like
(11:57):
the DOT doesn't come up on a map.
So an example of this is a 2025study found that 67% of vessels
inside the MPAs were untracked.
This is the study thatwe just talked about.
So now that we can detect untrackedvessels, we're gonna be able to
understand how many of these untrackedvessels are gonna be there and maybe
be able to deploy these vesselsthrough like AI prediction models or
(12:17):
machine learning prediction models.
So authorities can prioritize patrolstowards areas with high track vessel
activity, closing a major enforcement gap.
That's something that's really important.
So here's another thing that they can do.
Guiding patrols with real-time alerts.
So AI driven analytics turn raw satellitedetection into real-time alerts for
coast guards and fisheries officers.
(12:38):
So an example is the country.
Gavin partnered with NGOs and GlobalFishing Watch to use satellite data
to direct naval patrols leading tothe arrest of industrial trawlers
operating illegally in MPAs.
So instead of patrolling blindly,authorities can intercept in real
time saving fuel and resources.
That's a big, big win and a great example.
Then you have the legaland court backed evidence.
(13:00):
So satellite imagery combined withvessel tracks creates verifiable evidence
admissible in legal or policy disputes.
So an example, in Europe, courtrulings upheld trawl bans and MPA
strengthened by satellite basedevidence showing incursions.
So we see the actual stuff in courtsaying, Hey look, we may not have
caught these vessels right away,but we know this is happening.
(13:22):
We know the vessels.
We're able to track themthrough AIS and satellites.
Now we can give them the business, right?
We can give them those courtdecisions where they're not gonna be
very happy and they're gonna be fine.
Now, those court decisions can be tougherif we put the right laws in place, and
that's another issue, but that's somethingthat we need to worry about in the future.
So that provides a lot of like ablack box record that regulators and
(13:45):
cords can use to uphold restrictions.
Now you've got persistent oversight ofremote MPAs using that satellite imagery.
and AI large scale surveillance.
Remote MPAs are too vastfor constant petroleum.
We can't do it, but the UK Blue Beltprogram uses daily satellite imagery
or monitoring for Tristan Una's,I think that's how you pronounce
it, remote MPA to detect potentialillegal activity with alerts directing
(14:08):
patrols to areas to be avoided.
It prevents remote MPAs becomingpaper parks by providing
consistent low cost oversight.
So again, directing patrols throughquick processing of this data to
say, Hey, we actually found somethingwhen we're able to, and we're gonna
direct these patrols to enforce.
Over time, that's going todecrease what's happening.
(14:29):
In Palau in 2025,
using the combined satellite surveillancewith long range drones to enforce its
National Marine Sanctuary covering oneof the world's largest no-take zones.
So they use satellites to detectsuspicious vessels, drones to verify
and collect high resolution imageryand AI models confirming phishing
activity, so the gear types, thepatterns of behavior, and et cetera.
(14:52):
So it creates a layered monitoringsystem, Increasing deterrence while
reducing cost of ship based patrol.
So think about this again.
It's not just blindly patrolling the waterwhere you'll never be able to find this.
If you ever played battleship, ifyou ever played the game battleship,
before you hit your first boat, you'reblindly trying to hit like a 10 or B
this, or B five or something like that,and then you finally hit something.
(15:14):
Well, that's doing it blindly.
But imagine if you had somebody behindyou to just kind of be like, Hey.
You know what?
A 10 is actually gonna miss.
Let's go B five.
You're gonna hit thebig battleship, right?
And it's having somethingthere to direct you.
And now I know for the game that'scheating and don't cheat in battleship.
The person you're playingagainst is not gonna like that.
But here we have to cheat alittle bit to get into it.
(15:34):
And just by using data, we canbetter inform our patrols and save
on a lot of money for patrolling.
So then you got the promotionof transparency and deterrent.
So publicly sharing satellitedetected vessel activity,
pressures fleets to comply.
So just that public pressureallows us to say, Hey.
This fishing vessel's awful.
Where do they work?
(15:54):
Oh, they work for such and such.
That's who sells to such and such place.
Don't buy from them.
That public pressure, as we've seen,like in cancellation society that
we live in today, that could helpdeter boats from doing such a thing.
So Chile publishes industrial andartisanal fishing vessel tracks
on global fishing watch and usesAI analysis to plan patrols.
They just publicly just put it out there.
(16:16):
So the transparency itselfbecomes a deterrent.
Knowing your vessels, movements maybe visible to NGOs, journalists, and
the public reduces rule breaking.
So think about that.
Just think about these thingsthat are actually working in
countries where we can do better.
We've been doing better.
It is a very difficult challenge tomanage fisheries across the globe,
(16:37):
especially in areas in the high seaswhere countries don't really have
a lot of ability to enforce, but intheir own boundaries, in the exclusive
economic zone where they can enforcethings, it becomes a bigger picture.
And if you can use things like AI,you can use things like satellite
imagery, AIS, any kind of GPS technology'cause there's others than AIS,
(16:58):
you can use, drones even to directpatrols to say, Hey, you know what?
We found the vessel.
Boom, let's go get 'em and let's enforcewhat we're trying to do and let's
protect this marine protected area.
Truly and really decrease the amountof paper parks that we actually have.
We know marine protected areas work.
But we need to help them by enforcingthem from extractive activities
(17:20):
like illegal phishing, and we cando that using the new technology.
It's being done.
Although we can detect a lot of stuff,have bad stuff happening now we can really
focus on remote areas, larger remoteareas to say, Hey, we need to invest more
of this technology or more money intothis technology to detect things that
are illegal activities such as phishing,and be able to enforce it better.
(17:40):
That's the episode for today.
I thought I would do alittle bit of a deep dive.
I know this is a longer episode thanwe normally do, but I thought this was
really interesting and it's somethingthat we need to continue to invest.
So what you can do specificallyas an individual is support places
like the global Phish watch, right?
Support organizations like the OceanConservancy, Oceana, World Wildlife Fund.
(18:03):
These are all organizations, largeorganizations, international organizations
that have global partners, not only froma conservation side, but also on the
fishing side because you know, there'sa lot of fishing partners that want to
make sure that fishing is sustainableand that they're following the rules and
be able to stomp out illegal activity.
Let's reward the fishers that aredoing things legally and let's, you
(18:25):
know, enforce the rules for fisherswho are doing things illegally.
You can do that by supporting theseorganizations who are out there
actively doing this type of stuff.
So that's something Iwanted to talk about today.
I wanted you to know aboutmore and more and more.
We're gonna be covering thesethings in the future, so
I'm really happy to do that.
If you have any questions or comments,leave a comment If you're watching this
(18:45):
on YouTube, in the comment section below.
And of course, if you're listeningto the audio version, which I love
the fact that you're listening to theaudio version, start off on audio.
Always will do audio.
Please get ahold of meby going to the website.
Speak up for blue.com/contact.
Just fill out the form or youcan just hit me up on Instagram
at How to Protect the Ocean.
Just DM me.
I would love to chat with you.
I'd love to hear yourquestions and comments.
(19:06):
And that's it for today's episode ofthe How to Protect the Ocean Podcast.
I'm your host, Andrew Lewin fromthe True Nord Strong and Free.
Have a great day.
We'll talk to you next timeand happy conservation.
illegal fishing vessels thoughtthat they can hide, but satellites
and AR are catching them in theact in marine protected areas.
Today I'll show you how thisnew technology is turning the
tide for ocean conservation.
When I read a recent study, I wasshocked to see how many fishing vessels
were detected inside marine protectedareas, especially the more remote ones.
(00:21):
These are places we imagine as untouched.
But in reality, they're often thehardest to enforce and the easiest
for illegal fishers to exploit.
That hit me personally because MPAsare supposed to be our ocean's havens.
but here's the good news.
Satellites and AI are changing the game.
We're finally catching vesselsthat thought that they can hide,
(00:42):
and enforcement is startingto get smarter and stronger.
In this episode of the How to Protectthe Ocean Podcast, I'm gonna share
real world examples of how these toolsare already protecting the ocean and
why it gives me hope for the future.
So let's start the show.
Hey everybody.
Welcome back to another exciting episodeof the How to Protect the Ocean Podcast.
I'm your host, Andrew Lewin, andthis is the podcast where you find
(01:04):
out what's happening with the ocean,how you can speak up for the ocean,
and what you can do to live fora better ocean by taking action.
Today we're gonna be talking abouta lot of different things, all
combined into one terrific story.
We got AI, we got satellite imagery,we got synthetic aperture radar,
which is like a really cool satellite.
We've got machine learning.
We got AIS, which is automaticidentification system.
(01:27):
we got marine protected areas.
We got illegal fishing, fishing boats.
There's all in one enforcement.
It's a very exciting story, allpacked in one research paper in
the research journal science.
Now we're gonna be going a little beyondthat because this research paper showed
an increase in illegal fishing activityin marine protected areas, especially
those that were further away from thecoast, so more remote, and they spent
(01:50):
longer within those time, four hours.
Per vessel in marine protectors per year.
Not a really great story in terms ofoptimism, but then I wanted to go a little
bit further and I found some examples ofopportunities where satellites, AI and
machine learning were used to detect anenforce, of course, and prevent further
(02:10):
illegal fishing in marine protected areas.
So we're gonna talk all aboutthat on today's episode,
which I can't wait to do that.
But first, before we get into that, ifyou are interested in marine stuff, you
wanna learn about the ocean, you wannalearn more about these conservation
stories, you can get more information eachand every weekday with our newsletter.
Just go to speak up for
(02:31):
That's speak up for blue.com, allone word slash newsletter to get
access to our newsletter and getinformation on ocean conservation
in your inbox five days a week.
It has all of our podcast stuff,news articles that are coming out,
something that's very interesting
each and every day, check it out.
Speak up for blue.com/newsletter.
Let's get back into the story.
(02:52):
This is really interesting.
So this is how they use it.
They use Synthetic Aperture, ApertureRadar SAR, satellite imagery,
combined with AIS data, which isAutomatic Identification System
and AI and machine learning todetect industrial fishing vessels.
So essentially what they didis they took the satellite
imagery, which is really cool.
It's not like your regular satellite.
It basically takes the surfaceof the water and makes it really
(03:15):
like an impenetrable marker.
it looks like concrete and then it takesfishing vessels and makes them dark.
So you can actually detect fishingvessels each and every way.
It's really cool.
They use it to monitor a lot,anything at the surface, they
know where the boundaries ofthe marine protected areas are.
They can find out where these fishingvessels are, so they overlay a map or a
polygon of where these boundaries are.
'cause they're invisible normally.
(03:35):
We don't see an actual physical barrierin the ocean that goes down the water
column to prevent people from coming inand fishing in marine protected areas.
Now, before we go further, marineprotected areas are areas where
they protect any kind of extractiveactivity, including illegal fishing.
It's usually to protect fish, allowsfish to grow bigger, allows fish
to grow more in terms of number andbigger so that they spill over the
(03:59):
boundaries of the marine protected areas.
And they get fished by fishermenlegally, but they're not allowed.
The fishermen are not allowedinside the boundaries of the marine
protected areas because that iswhere they're allowed to grow.
They're special areas, andso we need to protect them.
These fishing vessels willcome in because you know why?
Nobody's there to watch them.
Because the ocean is massiveand you can't just keep, you
(04:21):
know, boats there all the time.
It's expensive.
It's almost impossible to do that.
So we have satelliteimagery like sar, right?
the satellite imagery allows, thispicture to be taken at some point in time.
To find out if there's anyillegal boats that are in there.
AIS data, Automatic Identification System,is placed on some of these boats that
allows it and detects the GPS coordinatesof where they are at any point in time.
(04:45):
Well, within a certain interval.
I think sometimes it's seconds.
I've worked with this data before.
You could really see, like if you lookat worldwide and how this AIS has done
for those boats, which are still a lot.
Those boats that use it, you canactually see tracks all over the
world and where these boats havegone, what flags they're flying.
It's really cool data.
Hard to get ahold of.
It's usually managed and kept bythe Coast Guard, but I've worked
(05:05):
with it when I worked in government.
It's really cool data to have.
So you have these boats.
So you know where they are.
We know which boats are where,and then we have the satellite
imagery to detect which boats arewithin the marine protected areas.
And then you can findout basically on speed.
So if they're trolling, youcan see how they slow down.
All this different type of stuff, youcan find out all this with this data,
and of course, AI and machine learningcan quicken that processing speed so
(05:28):
you can catch 'em almost in the act.
So if they're coming to a border,you know where they're going.
You can like basically deploy CoastGuard vessels or whatever the vessels
are for each country to get outand to enforce this illegal fishing
activity to prevent it from happening.
So the faster the authoritiescan get on it, the better.
So AI and machine learning help it.
So you got satellites
and AIS to detect the illegal activity.
(05:49):
And you have AIS and machinelearning to deploy the enforcement,
to go out and catch them.
So that's what the story was essentially.
They focused on coastal marine protectedareas globally between 2022 and 2024.
Only coastal MPAs that are largerthan one kilometer squared were
considered since Ramona MPAs oftenlack consistent satellite data coverage.
(06:11):
Okay.
SAR satellite data coverage.
So prevalance of fishing in MPAs,they detected industrial fishing
happened in 47% of coastal MPAsworldwide during the study period.
So that's only within two years.
So many of the vessels detected 67% wereuntracked by public monitoring system.
So no AIS so the satellites candetect all the boats that are there.
(06:31):
The AIS can identify which boatshave AIS and which boats don't.
If you don't have AIS andyou just see a boat there.
Why aren't we being able to see this?
This is consistent with otherstudies that show 75% of the
fishing vessels around the world donot have AIS, they are untracked.
This is very scary in terms of what ishappening with fishing and illegal fishing
because we can't track these boats.
(06:52):
More effort needs to be done to trackevery single fishing vessel that is around
anywhere.
So having untracked vessels, not good.
So surprisingly, the most restrictiveMPAs where extractive activity is
supposed to be prohibited at all costs,still had a lot of untracked vessels.
About 80% of detections inthose MPAs were on track.
So that makes sense becausethey're not supposed to be there.
(07:14):
So why would you have atracked vessel in there?
So that makes sensebut still pretty scary.
So the effectiveness or the lack thereofwas not just tied to how restrictive
the MPA is, like legally from byIUCN standards, but more strongly
to remoteness and size of the MPA.
So large and remote MPAs hadmore phishing vessel detections.
Now, what's interesting to me isI wonder if we actually talk to
(07:36):
these fishers if they even careabout the boundaries or they are
just going where the fish are now.
Ideally in the marine protectiveareas because they work so well,
you will see bigger and more fish.
And so that's why they'reprobably going within those areas.
so the average fishing vessel inside theMPAs was around four hours per square
kilometer per year when both trackedand untracked vessels were counted.
(07:58):
That's a lot of time.
I know that sounds weird, but that'sa lot of time thinking about how often
these fishing vessels go into these areaswhere there's marine protected areas.
So that is somethingthat is not good, right?
That's a lot of time inthese marine protected areas.
So the density and presence of fishingvessels, so tracked and untraced in
MPAs correlate more strongly withMPA size and remoteness rather than
(08:18):
the formal protection category.
So it's not as if it's just, hey,it's protection, it's actually this
size and the remoteness of the MPA.
So here's the thing.
We do have gaps in monitoring, right?
That is one of the limitationsthat this study identifies.
So public tracking systems, AIS miss alarge portion of the phishing activity.
Untracked vessels make up a largeand major invisible pressure.
(08:41):
That's something that wecan't see through AIS.
If you can't see the data on a map,
it's really difficult, even thoughthere's so much data, there's so many
more vessels that are go on tracked.
We also have to worry about paper parks.
It's a risk when MPAs aredesignated, which takes a long
time to designate them when they'redesignated, they need to be enforced.
If they're not enforced, they'rejust considered paper parks,
meaning that they're on paper.
(09:02):
We see them on maps, but wedon't actually enforce them.
And so without the lack of sufficientenforcement and monitoring, we
may see considerable phishingin these areas, which kind of
nullifies the point of the MPA.
We also need to integrateOnTrack surveillance.
So using things like SAR, likethe satellite machine learning and
combining multiple data sources improvesunderstanding of true phishing pressor.
(09:25):
So a lot of the times when we do thesestudies, we have to understand how much
pressure there is in phishing withinthese MPAs or just around the world.
When you don't have the ability toidentify who's fishing and who's not,
or what's tracked and what's not trackedlike what fishing vessels aren't tracked,
we lose the ability to understandthe true phishing pressure.
So if we only look at trackedvessels, we only get a snapshot
(09:48):
of what's actually happening.
It's only a small representationwhen we have more vessels that
are untracked, this can't be done.
This is up to the fishing fleetsor even the countries that allow
fishing vessels to fly their flags.
That's a whole thing.
If you look at my recent interviewwith Dan Skerritt, you'll understand
what these flags do and how easyit is to manipulate these flags
(10:09):
and to fly under a different flag.
To be able to do prettymuch whatever you want.
When these countries are not enforcingany of their laws, or if they even have
laws, they may not have as many laws.
So in integrating this information,surveillance, so SAR machine
learning, AI, combining multiple datasources improves the understanding
of true phishing pressures.
Then you have model predictions.
(10:30):
So because of limitations, not allvessels are greater than 15 meters.
Variable satellite coverage, which ishard to get total satellite coverage
whenever you want because they'rein orbit and they only fly around
certain areas once or twice a day.
Distinguishing transitversus fishing vessels.
So some are just in transit, someare actually actively fishing.
And then the metrics that are estimates,actual fishing effort in some marine
(10:52):
protectors may be higher, especiallyin places with weaker AIS coverage.
So the fact that there's so manyvariables, we're not there physically
all the time, these enforcement people,and we are seeing it from like, you
know, orbit and we're seeing thingslike from a digital landscape, like
on a GIS or a mapping tool and onlyseeing data points and maybe missing
data points from untracked vessels.
(11:14):
There are a lot of underestimationsthat are happening right now, and we
have to assume that there's more fishingpressure around the world, especially
within these marine protected areas.
So now that's the bad news.
I know this a lot and I appreciate you.
You hand me the good news is coming.
There are a lot of things that wecan do and there are a lot of things
that are being done, and I thinkthat's something really interesting.
Detecting dark vessels with SAR and AI.
(11:36):
So here's how it works.
SAR satellites can detect ships.
I just kind of mentioned it, regardless ofthe weather or lightning, so that's good.
AI models match SAR detections with AISdata to flag quote unquote dark vessels.
Those that are not transmitting AIS.
So, like I said before, the satelliteimagery can actually detect what's
in the marine protected areaboundary, even though the AIS, like
(11:57):
the DOT doesn't come up on a map.
So an example of this is a 2025study found that 67% of vessels
inside the MPAs were untracked.
This is the study thatwe just talked about.
So now that we can detect untrackedvessels, we're gonna be able to
understand how many of these untrackedvessels are gonna be there and maybe
be able to deploy these vesselsthrough like AI prediction models or
(12:17):
machine learning prediction models.
So authorities can prioritize patrolstowards areas with high track vessel
activity, closing a major enforcement gap.
That's something that's really important.
So here's another thing that they can do.
Guiding patrols with real-time alerts.
So AI driven analytics turn raw satellitedetection into real-time alerts for
coast guards and fisheries officers.
(12:38):
So an example is the country.
Gavin partnered with NGOs and GlobalFishing Watch to use satellite data
to direct naval patrols leading tothe arrest of industrial trawlers
operating illegally in MPAs.
So instead of patrolling blindly,authorities can intercept in real
time saving fuel and resources.
That's a big, big win and a great example.
Then you have the legaland court backed evidence.
(13:00):
So satellite imagery combined withvessel tracks creates verifiable evidence
admissible in legal or policy disputes.
So an example, in Europe, courtrulings upheld trawl bans and MPA
strengthened by satellite basedevidence showing incursions.
So we see the actual stuff in courtsaying, Hey look, we may not have
caught these vessels right away,but we know this is happening.
(13:22):
We know the vessels.
We're able to track themthrough AIS and satellites.
Now we can give them the business, right?
We can give them those courtdecisions where they're not gonna be
very happy and they're gonna be fine.
Now, those court decisions can be tougherif we put the right laws in place, and
that's another issue, but that's somethingthat we need to worry about in the future.
So that provides a lot of like ablack box record that regulators and
(13:45):
cords can use to uphold restrictions.
Now you've got persistent oversight ofremote MPAs using that satellite imagery.
and AI large scale surveillance.
Remote MPAs are too vastfor constant petroleum.
We can't do it, but the UK Blue Beltprogram uses daily satellite imagery
or monitoring for Tristan Una's,I think that's how you pronounce
it, remote MPA to detect potentialillegal activity with alerts directing
(14:08):
patrols to areas to be avoided.
It prevents remote MPAs becomingpaper parks by providing
consistent low cost oversight.
So again, directing patrols throughquick processing of this data to
say, Hey, we actually found somethingwhen we're able to, and we're gonna
direct these patrols to enforce.
Over time, that's going todecrease what's happening.
(14:29):
In Palau in 2025,
using the combined satellite surveillancewith long range drones to enforce its
National Marine Sanctuary covering oneof the world's largest no-take zones.
So they use satellites to detectsuspicious vessels, drones to verify
and collect high resolution imageryand AI models confirming phishing
activity, so the gear types, thepatterns of behavior, and et cetera.
(14:52):
So it creates a layered monitoringsystem, Increasing deterrence while
reducing cost of ship based patrol.
So think about this again.
It's not just blindly patrolling the waterwhere you'll never be able to find this.
If you ever played battleship, ifyou ever played the game battleship,
before you hit your first boat, you'reblindly trying to hit like a 10 or B
this, or B five or something like that,and then you finally hit something.
(15:14):
Well, that's doing it blindly.
But imagine if you had somebody behindyou to just kind of be like, Hey.
You know what?
A 10 is actually gonna miss.
Let's go B five.
You're gonna hit thebig battleship, right?
And it's having somethingthere to direct you.
And now I know for the game that'scheating and don't cheat in battleship.
The person you're playingagainst is not gonna like that.
But here we have to cheat alittle bit to get into it.
(15:34):
And just by using data, we canbetter inform our patrols and save
on a lot of money for patrolling.
So then you got the promotionof transparency and deterrent.
So publicly sharing satellitedetected vessel activity,
pressures fleets to comply.
So just that public pressureallows us to say, Hey.
This fishing vessel's awful.
Where do they work?
(15:54):
Oh, they work for such and such.
That's who sells to such and such place.
Don't buy from them.
That public pressure, as we've seen,like in cancellation society that
we live in today, that could helpdeter boats from doing such a thing.
So Chile publishes industrial andartisanal fishing vessel tracks
on global fishing watch and usesAI analysis to plan patrols.
They just publicly just put it out there.
(16:16):
So the transparency itselfbecomes a deterrent.
Knowing your vessels, movements maybe visible to NGOs, journalists, and
the public reduces rule breaking.
So think about that.
Just think about these thingsthat are actually working in
countries where we can do better.
We've been doing better.
It is a very difficult challenge tomanage fisheries across the globe,
(16:37):
especially in areas in the high seaswhere countries don't really have
a lot of ability to enforce, but intheir own boundaries, in the exclusive
economic zone where they can enforcethings, it becomes a bigger picture.
And if you can use things like AI,you can use things like satellite
imagery, AIS, any kind of GPS technology'cause there's others than AIS,
(16:58):
you can use, drones even to directpatrols to say, Hey, you know what?
We found the vessel.
Boom, let's go get 'em and let's enforcewhat we're trying to do and let's
protect this marine protected area.
Truly and really decrease the amountof paper parks that we actually have.
We know marine protected areas work.
But we need to help them by enforcingthem from extractive activities
(17:20):
like illegal phishing, and we cando that using the new technology.
It's being done.
Although we can detect a lot of stuff,have bad stuff happening now we can really
focus on remote areas, larger remoteareas to say, Hey, we need to invest more
of this technology or more money intothis technology to detect things that
are illegal activities such as phishing,and be able to enforce it better.
(17:40):
That's the episode for today.
I thought I would do alittle bit of a deep dive.
I know this is a longer episode thanwe normally do, but I thought this was
really interesting and it's somethingthat we need to continue to invest.
So what you can do specificallyas an individual is support places
like the global Phish watch, right?
Support organizations like the OceanConservancy, Oceana, World Wildlife Fund.
(18:03):
These are all organizations, largeorganizations, international organizations
that have global partners, not only froma conservation side, but also on the
fishing side because you know, there'sa lot of fishing partners that want to
make sure that fishing is sustainableand that they're following the rules and
be able to stomp out illegal activity.
Let's reward the fishers that aredoing things legally and let's, you
(18:25):
know, enforce the rules for fisherswho are doing things illegally.
You can do that by supporting theseorganizations who are out there
actively doing this type of stuff.
So that's something Iwanted to talk about today.
I wanted you to know aboutmore and more and more.
We're gonna be covering thesethings in the future, so
I'm really happy to do that.
If you have any questions or comments,leave a comment If you're watching this
(18:45):
on YouTube, in the comment section below.
And of course, if you're listeningto the audio version, which I love
the fact that you're listening to theaudio version, start off on audio.
Always will do audio.
Please get ahold of meby going to the website.
Speak up for blue.com/contact.
Just fill out the form or youcan just hit me up on Instagram
at How to Protect the Ocean.
Just DM me.
I would love to chat with you.
I'd love to hear yourquestions and comments.
(19:06):
And that's it for today's episode ofthe How to Protect the Ocean Podcast.
I'm your host, Andrew Lewin fromthe True Nord Strong and Free.
Have a great day.
We'll talk to you next timeand happy conservation.
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