Eyes on Earth Episode 123 – Bathymetry Mapping
Detailed Description
This Eyes on Earth episode is the third in our series on using Landsat for coastal studies. We talk to physical geographer Jeff Danielson about bathymetry and how it is critical for coastal modeling. Bathymetry captures the shape of underwater topography, and satellite-derived bathymetry helps fill in areas where there are data gaps. Even though Landsat was designed to image land, it’s a big part of this work because of its systematic temporal coverage. Besides that, high-resolution data from sonar and lidar are too labor intensive to collect everywhere. Therefore, they use all these sources together to get a better picture of bathymetry, especially in remote areas. This modeling helps with studying changes to shorelines such as storm surge, sediment transport, and flood damage.
Details
Sources/Usage
Public Domain.
Transcript
TOM ADAMSON:
Hello everyone and welcome to another episode of Eyes on Earth, a podcast produced at the USGS EROS Center. Our podcast focuses on our ever-changing planet and on the people here at EROS and across the globe who use remote sensing to monitor and study the health of Earth. My name is Tom Adamson.
This summer, we did a series of three podcasts on coastal studies and are learning the variety of ways Landsat, with its 50-plus-year archive, is useful in studying the world’s changing coastlines. We’ve talked about changes to beaches in California and how that coastline may change in the future because of sea level rise and coastal erosion. Then we talked about how Landsat data back to the 1980s is being used to see where shorelines are eroding and where they are growing around the entire coastline of Australia.
For the final episode in this series, we’re talking to Jeff Danielson about bathymetry. Jeff is a physical geographer and the Coastal National Elevation Database Applications project chief at the USGS EROS Center. So Jeff, let’s start with, what is bathymetry.
JEFF DANIELSON:
Bathymetry is a geophysical variable where it captures the bottom of the oceans, the depths of the oceans. Bathymetry is the submerged topography under the water.
ADAMSON:
And why is mapping bathymetry important for coastal modeling?
DANIELSON
Bathymetry is critical for all aspects of coastal modeling. So if you do sediment transport modeling, if you do wave modeling, if you do flood modeling as you project water from the ocean on land, you have to understand the slope going from offshore to onshore. So the bathymetry captures the shape of the underlying topography. So as you move on shore, you have to have that knowledge of where waves are going and how they’re being projected on shore. So bathymetry is a critical variable for coastal modeling across different applications.
ADAMSON:
OK, I see why you’re calling it a variable then, a critical variable for that kind of modeling.
DANIELSON:
You know it’s like land surface topography is a variable on land; bathymetry is a variable for under the water.
ADAMSON:
OK. That’s great. That makes sense. Why do we need good maps of bathymetry?
DANIELSON:
Good maps of bathymetry are needed for, you know, charting like for ships and navigation. That is one reason for having good bathymetry, but having good maps of bathymetry is important for science and applications. There’s lots of areas that don’t have bathymetry or lack sufficient density of bathymetry and so U.S. agencies were trying to acquire more bathymetry to support efforts like Seabed 2030 and to try and map bathymetry at 100-meter spacing for every sounding across the earth, for example, from using modern systems like sonar and lidar. Satellite-derived bathymetry is not really part of that mapping because of the accuracy of the satellite data coming in for bathymetry.
But there is a lack of bathymetry really across the world when you look at sufficient density of bathymetry. So we’re trying to do more mapping through the NOMEC, which is the National Ocean Mapping, Exploration and Characterization, and that’s where we’re trying to expand the coverage of mapping bathymetry across U.S. waters.
ADAMSON:
You mentioned lidar, and your team uses lidar and other high-resolution data for coastal mapping, but you recently had a study that used Landsat to estimate water depth in areas close to shore. But Landsat was designed to image the land. You know, Landsat. You can get higher resolution with lidar, right? So how is Landsat useful in this mapping? How does Landsat get incorporated with that?
DANIELSON:
This all started with the USGS Coastal National Elevation Database project. CoNED creates regional topobathymetric models using bathymetry from both lidar and sonar based sources and also merges that with land-based topographic data. But there is a lack of data across the U.S. coastline in the near shore where there’s voids, and there’s also more voids in the areas further offshore where satellite data could be used to fill in those gaps.
Also, if you go outside of the U.S. like into the Pacific islands, there is no data available, so satellite is the only source available. You know, Landsat and Sentinel and other sources have the ability to cover large areas, and they allow us to be able to measure the depth by using various methods. One is by using a band ratio where we can actually calibrate the ratio to a known depth, or we can use a method that we just published by Minsu Kim, where we can physically derive the bottom information by resolving other properties such as water column and aerosol and other factors that we can derive from the bands of Landsat. And then we can estimate what is that known depth from the Landsat signal.
ADAMSON:
Well, there’s plenty of areas in the entire world that are just so remote that you can’t get to do this kind of lidar mapping. Is that what it comes down to?
DANIELSON:
Right. Airborne lidar covers more area than boats, so boats are, you know mapping with sonar is probably the most expensive way to map bathymetry. Lidar would be second given that you can cover more area with planes. The satellite gives you the most coverage of all. You know, but also satellite-based bathymetry is the lowest accuracy in terms of the levels of bathymetry. So, I mean, sonar probably is the most accurate with lidar being second and satellite being third. So it’s the most area with Landsat but you have the lowest accuracy with Landsat or satellite-based observations.
ADAMSON:
There’s some give and take here.
DANIELSON:
Exactly.
ADAMSON:
I mean, you’re taking the benefit of Landsat being so systematic in its coverage, covering the globe, at least the land, every 8 days between Landsat 8 and 9. But it’s now also covering some of those, did you call it near shore or a little bit farther away from the coastline areas? And that’s where what you’re finding helpful?
DANIELSON:
We’re finding that, you know, Landsat data can be used to fill these critical gaps that we’re seeing. You know, there’s the near shore, it’s problematic for boats because of safety and hazards. So NOAA, for example, can’t collect data closer to 0 to 4 meters because of safety and navigation. So there is always a gap along the near shore. Lidar typically is useful for filling those voids. But also you have problems with trying to fly lidar everywhere. I mean it’s just lidar is expensive and you can do it in piecemeal fashion. You can’t do it systematically like Landsat. So there’s always going to be gaps along the near shore globally. You see gaps in Alaska, for example, with the Alaska coastal mapping up there, you know, where satellite-derived bathymetry will be useful in trying to help fill in some of those gaps until high-resolution surveys can be done.
You know, working in the Pacific, you know, islands, you know, it’s just logistically very challenging to do airborne surveys out there, to do sonar surveys out there. You know, it takes time and resources. It takes a lot of money. So in some ways, you know, using satellite-based systems, you know, gives us a first cut to fill in those maps and to at least have a baseline starting point with, you know, bathymetric coverage.
ADAMSON:
Considering, like I said, that Landsat was designed to image land, in relatively simple terms, can you tell us how Landsat measures sea floor depth?
DANIELSON:
We use the visible bands of Landsat, once again, to— we use the green band mostly cause that basically gives us penetration for the water column. So we can actually see the bottom reflectance using Landsat data.
ADAMSON:
And the Landsat visible bands are those colors red, green, and blue.
DANIELSON:
And we use primarily green and blue.
ADAMSON:
How deep of water can you see through?
DANIELSON:
So we’re able to resolve bathymetry using Minsu’s method, for example, down to about 25 meters actually, you know, which is actually pretty incredible. You know, other methods can get deeper and we thought initially this method would maybe, you know, get us down to about 10 meters, but we’re seeing better depth than we thought from this method.
Obviously, the accuracy is better as you go more shallow, so as you go deeper the accuracy compared to known data is probably a little bit worse, but you know it still gives us data that, you know, it’s still giving us valid data. You just need to, as a scientist, know that you might need to filter it depending on how you want to use it, and there’s also known uncertainties that come with it.
ADAMSON:
OK. But you know what those uncertainties are and maybe you can kind of work around them, or how do those work?
DANIELSON:
Yes, you could definitely account for those uncertainties in the data products. Right now our methods are still research. We’re still producing papers. You know, we’re not producing systematic products right now from these methods. We’ve just published a paper in the Journal of Remote Sensing that talks about this physics-based, satellite-derived bathymetry approach using Landsat OLI data. But our next project is going to test Sentinel and also WorldView, other sensors that have higher spatial resolution than Landsat, which also gives us to a point that Landsat Next I think will be a game changer for satellite-derived bathymetry. With the increased channels, the bands, you know, adding a violet and you know more coastal bands will be helpful for like improving the atmospheric correction of Landsat data over the water. You know, right now EROS does produce a Landsat aquatic reflectance product. And Minsu actually did also add in a sort of improved version of atmosphere correction in his algorithm that we work with, but having more bands is helpful for atmospheric correction. That’s a known fact. You know, the more channels you have in the visible is helpful to resolve those different optical properties. But also Landsat Next provides an increased spatial resolution from 30 to 10 meters, which gives us a real sweet spot for satellite-derived bathymetry. A lot of folks like Sentinel because of that 10-meter resolution. Landsat at 30 right now is a little bit coarse for satellite-derived bathymetry.
Landsat has a tremendous time series, and that is the real strength of Landsat is the time series. We’re looking at change and bathymetry does change. So there is a need to use satellite data to look at change across the sea floor. You can still get some of that information. You have to still take into consideration, you know, the accuracy of your data. Certainly, Landsat can be used for that purpose. You know, there are some challenges to doing satellite-derived bathymetry. I wanted to mention that for doing satellite work with— and this goes for all optical-based methods. Bathymetry from these systems require clear water, so you can’t do it like for example in the Mississippi River or the Missouri River. You have to have clear water. You have to have, you know, bright bottoms or bottoms that have some type of reflectivity. If you have a very dark substrate, it’s much more difficult to see that reflectance from the satellite data or from any lidar-based source for that matter. Sonar works differently since it uses sound waves, so you know when you work with the optical-based systems, we use the reflectivity.
ADAMSON:
Think of these areas like where a river flows into the ocean and it’s carrying sediment with it. That probably gets in the way.
DANIELSON:
Very, very difficult. You know, I would say right now we’re testing our methods in the Florida Keys, in Puerto Rico—
ADAMSON:
Ah, clear water in those places.
DANIELSON:
—in Guam, the water is pretty clear. The Pacific Islands work great because the water’s pretty clear. But also you could do it really great right now in the Great Lakes. I mean the Great Lakes, if you’re not aware, are becoming more clear because of the zebra mussels. So they’re actually helping to clear the water even though they’re really bad for the environment.
ADAMSON:
Yeah, yeah. But it gives you clear water. We might as well take benefits where we can get them.
DANIELSON:
Exactly.
ADAMSON:
In a way you have to learn that your method is good, starting with these clear water areas and then see how you could adapt it or see how it could work where the water is a little bit more muddy.
DANIELSON:
We have to build and prototype these methods in clear water, because that’s where your best conditions are, but certainly you can try satellite-derived bathymetry in less clear environments. We are trying to test it, for example, in rivers now for the National Geospatial Program to see if we can map some of these areas with satellite-derived bathymetry. We’ve tried it up in Alaska, where the water is not as clear and we’re able to get some bathymetry.
We’re also trying it, for example, in the Chesapeake Bay, which is not clear, but you can still get something in some areas. So the answer is not always yes or no completely. You can get partial areas mapped in these areas, but you have a better chance of getting more complete coverage where the water is more clear. You know, obviously satellite data can be very useful for looking at coastal change because it can be used for mapping shorelines. So shoreline mapping, trying to capture the shoreline extent, is different than mapping the bathymetry. I mean, those are different things, but satellites are very useful for looking at shoreline change.
ADAMSON:
That’s really the land—
DANIELSON:
That’s the land interface.
ADAMSON:
There you go. The land-water interface. You can see what’s going on there with these optical—
DANIELSON:
You can see the shoreline.
ADAMSON:
You’re trying to see under that.
DANIELSON:
Yeah, coastlines are, they’re very dynamic because of all different types of erosional factors. You have, you know, waves, you have impacts of longshore current changes, you know, so there’s a lot of reasons why, you know, coastlines are— storms, so hurricanes. We look at, you know, after every hurricane or a major storm, we see lots of impact on the coastlines. Waves, obviously, are a big factor in coastlines. They are a huge impact and how they affect the coastline and so there’s a constant need to monitor what is changing along U.S. coastlines, I mean the USGS Coastal Marine Hazards and Resources Program of the USGS, you know, they have the mandate to look at shoreline change along the U.S. coastlines, and they use lidar, but they’re also using satellite-based technologies to look at that.
ADAMSON:
OK, we want to use whatever’s available to be able to get that done.
DANIELSON:
Absolutely. And actually, satellite data provides that temporal repeat frequency.
ADAMSON:
What do you hope people can do with this, especially with this method of using Landsat to measure bathymetry?
DANIELSON:
I’m a firm believer that there’s different ways to map satellite-derived bathymetry. This is one method using Landsat. We’re going to be testing it with other sensors like Sentinel, WorldView. We also published a method that uses stereo-based photogrammetry called SAT CD that uses commercial Maxar data to derive bathymetry and topography. But also you can use other methods that use, for example, a band ratio approach that I was talking about. I’m a believer in using and having a toolkit of methods to derive satellite-based bathymetry, but you know the overall goal in my mind is how we can fill in these missing gaps of data. And I think you know Landsat given its repeat coverage every 16 days, every 8 days if you combine both Landsat 8 and Landsat 9, you know there’s chances of getting cloud-free data, so clouds are also a problem with satellite-derived bathymetry. You don’t want clouds you don’t want haze. But, you know, there’s a better chance of getting a cloud-free scene using Landsat than other systems, and especially if you were to sort of also, you know, mix some Landsat with Sentinel then you have the combination of both to try and attack the problems of cloud-free data. Over some of these areas like in the Pacific islands where the water is clear, but you have more clouds, so you have to, so you really want to have more satellite-based observations.
ADAMSON:
And I should clarify, Sentinel that you’re talking about is from the European Space Agency. That’s an earth observing satellite system that they have. What are the other benefits of having this capability? What are people gonna do with this?
DANIELSON:
People are going to use the bathymetry data for doing what we do with CoNED, which is spatial integration of data. So CoNED is going to take the bathymetry from Landsat. It’s going to stack it with other datasets, so the lidar and sonar, prioritize it based on accuracy and frequency and resolution to create the most comprehensive topobathymetric model from these different data sources. CoNED produces an output 1-meter surface. So we will take Landsat and oversample and use it to create the overall model based on where we want to use it. But, and then folks use CoNED for doing all kinds of, you know, coastal modeling with sediment transport, you know, looking at storm surge, looking at coastal flooding, looking at sea level rise, looking at hydrodynamic modeling, you know, wave modeling.
ADAMSON:
All those changes that are just always happening anyway and be able to model what’s going to happen with these types of changes.
DANIELSON:
Right, you know, I mean I still think that, you know, in the short term, the Pacific islands is where Landsat is going to have a lot of success as well as all the other satellite systems because the water is clear and you know, and there is a lack of data in those areas. I mean, it’s a big ocean out there and there’s lots of, there’s actually small pieces of land, but there’s lots of water around those land areas. And it really takes a lot of time to cover it by boat to get sonar and, you know, high-resolution coverage and lidar is very expensive given that it’s hard to deploy out there. So in the short term, that’s one region of the world that’s going to take advantage of satellite-based bathymetry.
Let’s just take the people living on the Marshall Islands, for example. Their whole nation is about, it’s just a few meters above sea level. You know, they are very susceptible to sea level rise, if there’s changes in king tides, they have tremendous amounts of flooding to their infrastructure, to their properties, to their way of life. You know, it’s very important to understand how flooding happens on those islands, and without bathymetry you can’t do that.
ADAMSON:
I’d like to thank Jeff Danielson for joining us on this episode of Eyes on Earth. You can find our previous episodes in this series about mapping coastlines on our website. And check out our social media accounts to watch for all future episodes. You can also subscribe to us on Apple and YouTube podcasts.
VARIOUS VOICES:
This podcast, this podcast, this podcast, this podcast, this podcast is a product of the U.S. Geological Survey, Department of Interior.