Welcome to the EROS User Experience Webinar Series,
where we talk to staff at EROS to learn more about the data, tools and services
coming out of the USGS Earth Resources
Observation and Science, or EROS, Center.
Today's webinar is entitled EMIT: Imaging Spectroscopy, Surface
Mineralogy, and Greenhouse Gas Products and Resources Available from the LP DAAC.
I'm your host, Danielle Golon, the Remote Sensing User Services
lead here at EROS in Sioux Falls, South Dakota.
The time is currently 12 p.m.
central, so let's go ahead and get started.
First, a few logistics: to ensure the best audio
experience, all participants have been muted.
If you have any questions during the webinar, please enter them in the chat
and we will address those questions at the end of the webinar.
Today's webinar is being recorded.
The recording will be available on the LP DAAC’s website and the USGS trainings
YouTube channel, as well as the USGS Media Gallery in the next couple of weeks.
The presentation will then also be available on the LP DAAC website.
At the start and end of the webinar, we will have a few polling questions.
These polls are optional,
but your answers help us create a better user experience in the future.
These polling questions will be available via the Polls or Forms feature of Teams,
and I will also be adding the questions to the chat for our audience members
who are not able to use
those features in teams based on your organization's settings.
If that feature does not work for you, please feel free to answer
the questions in chat,
but you only need to answer the questions once, so either answer them in the polls
feature or in the chat, whichever works best for you.
You should now be able to see the first set of polling questions.
Today's webinar will consist of a presentation
followed up by a question and answer session.
Today's speaker will be Erik
Bolch, a remote sensing scientist for NASA's Land Processes
Distributed Active Archive Center, or LP DAAC here at the USGS EROS.
Erik's work focuses on providing user support for LP DAAC data
sets and services through the creation of tutorials, scripts and guides.
Erik also supports and contributes to NASA's application for extracting
and exploring analysis ready samples, or APPEEARS,
an application designed to make accessing and subsetting Earth science
remote sensing data easy and straightforward.
Erik’s presentation will provide an overview of EMIT data,
products and resources available from the LP DAAC.
Once Erik has finished his presentation, we will transition over to an optional set
of final polling questions and then we will move on to a Q&A portion
of the webinar.
We have several user services staff members as well as members
of the Open Science team here at EROS on the line, to help answer
any questions you may have throughout the webinar,
please feel free to add your questions or feedback through that webinar chat, and
we'll answer those questions or feedback we receive at the end of the webinar.
We will try to answer all of your questions within the time allotted,
but if we're not able to address your questions during the Q&A portion,
we will follow up with you offline.
If there's a future webinar topic
you'd like us to cover, please feel free to suggest that in the chat as well.
And with that, it's my pleasure to introduce today's speaker, Erik Bolch.
Take it away, Erik.
Hey, everybody.
Today I'm going to talk a little bit about EMIT, kind of focus
on the products available from the LP DAAC and some of our resources.
And I'm hoping today after this
talk, everybody will have a basic understanding of the mission.
Know a little bit about imaging spectroscopy
and then also what products are available from the LP DAAC and then where
to find resources to help them work with the data.
So I'm going to mention a lot of different links and websites.
I believe Danielle is going to share those in the chat.
They're also going to be at the end of the slideshow.
The slides will be made available probably around the time the video is,
so you'll be able to get back and access anything referenced here.
And so first of all, I just want to talk a little bit about the Land Processes
Distributed Active Archive Center or LP DAAC.
It's located at the United States Geological Survey's Earth Resources
Observation and Science Center
in Sioux Falls, South Dakota, and the LP DAAC organization
has been part of a 30 year long partnership between the USGS and NASA,
and we host and archive land process related data from the Emet mission.
To give a little bit of background
about the EMIT mission: that's the Earth Mineral Dust source InvesTigation.
And so what its objective is, is to map mineral surface composition
across the globe.
And this is important because wind erodes and kicks up surface minerals.
You can see some nice pictures here of dust being carried from Africa
up across the ocean.
And so you can see this dust can be transported vast distances.
And it has an effect on radiative forcing.
And so radiative forcing is essentially the change in energy flux
in the atmosphere that's caused by natural or anthropogenic factors.
And so here they wanted to determine essentially whether there's a net warming
or cooling effect.
And so depending on what type of dust,
what the composition is, it'll absorb more energy when it's in the atmosphere.
And so iron rich dust it's typically darker will absorb more energy,
while clay rich dust, which is pale yellow or white, is more reflective.
And this can have maybe a cooling effect.
So the way they're mapping these dust sources is with imaging spectroscopy.
And so the Emit instrument is an imaging spectrometer.
It's a push broom instrument mounted on the International Space Station.
And so what that means is it scans line by line as it passes over the Earth.
It has 1200 plus parallel spectrometers.
And so each one is going to capture a full spectrum
of wavelengths from 450 to 2500 nanometers.
As it passes over the Earth, it builds what's called an image cube.
You can think of this is like a 3D cube, like on the right
where you've got your spatial information.
And then for each pixel within that space, you'll have a full spectrum
which can tell you all sorts of information about what you're looking at.
For example, here in this radiant spectrum figure,
the blue, green and red channels are indicated.
And you can tell sort of since there's a peak in the green that we're probably
looking at vegetation because of that, and because there's the typical dip
you see past the red that's related to chlorophyl absorption.
And so since this full spectrum captures so much information
about what's happening to photons as they make their way to the sensor,
there's a lot of applications you can map things like natural hazards,
light features of aquatic ecosystems, minerals.
You can look at things like wildfires and map greenhouse gas emissions
from point sources.
And you can examine different things related to water resources
in the cryosphere.
And so depending on your application here, there's various EMIT products.
Sort of the two base ones would be the radiance,
the At-sensor Radiance, and the surface reflectance.
Sort of depending on what your application is, you can use either of these products
just to sort of highlight how the spectra relate to these things.
I've got some images of different spectra, and you can see
how widely the signature of things like minerals vary.
If you look at the top center, you can see these are all different minerals
and they have very different features along the visible near-infrared spectrum.
Additionally, you can examine things like ecosystem diversity
because there is a correlation between diversity of of spectra, basically
the amount of colors you see versus the biodiversity in an area.
This is specifically mostly focused on plants because they're stationary.
And that's much easier to get information about when you're only capturing
a snapshot.
Additionally, you can tell things about snow and ice, like the grain size,
whether it's covered in dust, all sorts of things based on the spectrum.
And lastly, you could detect different gases in the atmosphere,
like CO2 emissions and methane emissions.
I'll talk a little bit more about that later.
So the EMIT sensor, it does only collect data over a certain masked region.
Here you can see in the bottom right
the original target mask from 2022 through 2023.
And this is mainly focused over arid dust source regions.
Since then the mission has been extended,
and so the coverage has also been extended to include most of ConUS
or the continental United States as well as Europe.
And so this expanded coverage is still sort of limited.
And that's due to downlink constraints from the International Space Station.
So there's a lot of factors that go into
whether data is collected over your area of interest.
Besides just the mass,
the instrument only is going to collect data if there's favorable solar geometry.
So that means only if the sun is above a certain angle in the sky.
And also because the instrument is on the International Space Station,
the orbit is more complicated than if it was free flying satellite.
So there's not a standard revisit time.
For the revisit time, I've got a figure here
that sort of illustrates, the median revisit over areas within
the original target mass was about 10 to 11 per year,
so you can still expect to get some coverage over most regions.
But this does vary over time, and based on the position of the Earth
and the orbit of the ISS.
And one last factor that's always a concern
with remote sensing engines is their their clouds or not.
And so if you do see black lines across the images, if you're looking at the data,
this is where the onboard cloud screener
has automatically removed some cloudy regions
and this happens to allow more data to be downlinked from the space station.
So now that we've kind of talked about the coverage,
I want to talk about the products that are available from the DAAC
I'm not going to read these
on the table on the left, because I'm going to talk about them
all individually, but all of the data for the EMIT missions are available
at no cost for download, and it's also all available in the Earth
Data Cloud, which is AWS storage on the us-west-2 region.
And so if you're working within that cloud, you can use direct
S3 access to work and process the data.
And typically working right beside it is going to speed things up for you.
And then I want to mention sort of the main resource
or probably the easiest resource if you walk away with one is going to be
just the LP DAAC website.
Here you can find information and pretty much all the other links
we're going to share today or somewhere on this page.
And so if you want to search about a specific product,
you can easily find a description, a user guide, and more information
about specific products and links to our resources on this page.
So now let's get into how do we find the data.
So the recommended method would be to use our data search.
If you want to use a graphical interface or the CMR search API
if you want to do it programmatically.
And here I've got an image of our data search, and you can just
search EMIT in quotes to find all the EMIT specific products.
Right now there's six and there's actually one here that's shown
because I'm logged in and I have access to one extra one as far
as this tool goes, you can use it for temporal and spatial filtering.
You can add granules to a list and save that as a text file,
so you can access it programmatically later,
or you can do some filtering and save it as a project
that you can come back to later.
So a lot of really nice features for working with the data or data search.
So I'll also mention the visions tool which you can use to find the data.
And this is hosted by JPL and it's part of the mission.
The advantage here is that you can actually see forecast coverage,
which allows you to go out.
If you're going to do some build campaign to validate
whatever data you want to collect, you can see ahead of time.
Think about two weeks where it's going to overpass
in case you need to go out and do your field data collection.
So now I'm going to start talking a little bit about the products,
the At-sensor radiance, which is the EMITL1BRAD product.
It's got two assets.
It's got a radiance asset and an observation asset.
And so the observation is going to include things like sensor path length,
two sun and two sensor
angles, different information you might want for quality purposes.
And then the radiance
is going to be your radiance cube like I had talked about before.
This is distributed in NetCDF4 format and it's hierarchical.
So it has multiple groups.
The root group is going to have the data.
And then there's two other groups
the location group which has a spatial information.
And then the sensor band parameters which has spectral information
like the forward path maps and the wave.
So if we go back to the location this data is delivered in a non corrected,
spatially raw format.
So this is essentially a spectrally corrected cube from the sensor.
And so with that
there is a geometry lookup table included in the location group.
And what this allows you to do is re project the scene onto a geographic grid.
And this is a little different than like a geo transform.
This is really just a lookup table that has indices from the raw data.
And so you can use that to pull the spectra for each down track
or cross track position into the geographic.
So the reflectance product or estimated surface
reflectance is going to have a very similar format to the radiance.
Here there's a couple different assets.
There's a surface reflectance.
There's a surface reflectance uncertainty which is the uncertainty associated
with that.
And then there's a mask file which has things like a cloud mask, aerosol
optical depth and some other expanded masks for quality purposes.
These are also in NetCDF4 format.
Here we've got the dimensions,
and those are going to be the same as the radiance as well.
One thing to note is if you're getting the last scene
from an orbit, the down track dimension can vary.
It can be longer, so it can go up to double
the size of a normal scene, which would be 2560.
So that's sort of
a little summary of the reflectance, the estimated mineral identification
and band depth, which is the L2B product, consists of the mineral ID,
the band depth, and then also the mineral uncertainty.
And this is also provided in a non ortho corrected format.
Similarly with the geometry lookup table in here a bit of an explanation.
So there are these groups: group one and group two.
In this case they don't refer to the minerals;
they're referring to ranges in the absorption spectra.
So group one is things detected within the range of the visible and one micron.
And group two is things in the range of 2 to 2.5 microns.
And this is sort of based on the tetra
quarter software that they use to identify the minerals.
And so instead of spectral metadata, this file is going to have your
mineral metadata.
And so that basically has an explanation of what is the most similar
target from the spectral library used to do this identification.
And then also some blanks.
You can get back and actually see the spectra of that material.
So it has a URL as well as a record there.
The next product is it's going to be the estimated methane enhancement product.
And so this file is a cloud optimized GeoTIFF format.
And it is already ortho rectified.
So it's going to be easier to work with.
One thing about this this is not a concentration exactly.
But it's an estimate of the quantity above or below
background methane concentration.
And so this is provided in parts per million meters,
not just parts per million.
And that's because the vertical extent of plumes detected by this method
you don't really have a vertical extent.
And so you're not sure exactly the full size of the plume spatial.
The EMITL2B product, the estimated methane plume complex,
is essentially a delineated plume that's made from the enhancement data.
And this is identified and then confirmed
by a manual review process to sort of mitigate false positives.
It's also in a cloud optimized GeoTIFF.
And there's a JSON file that goes with it to help for visualizing some GIS tools.
And these file sizes are based on the plume extent.
So they vary.
And this is probably the easiest way to work with the methane data
if you're interested in doing that.
Lastly, I want to talk about the aggregated
mineral spectral abundance and uncertainty.
This is just a single file used for Earth system models.
And so it's going to have the mineral abundance
for the predefined minerals of interest for this mission.
And it's also in a netCDF4 format.
And each pixel is point five degrees.
And so just to mention again if you go to our website, you can get a user guide,
which is going to have all the details I just shared and more about each product.
And then also an algorithm theoretical basis document
which sort of explains how the product is created.
The EMIT mission is really leaned into open science.
And so all of the workflows for processing the different products
and doing the calibration and even the visualization tool,
the visions visualization tool, are all publicly available.
And they're in this GitHub repository that you can go see.
And so now I'm going to talk a little bit about our publicly available resources.
Our main repository is the EMIT Data Resources repository.
This is on GitHub.
Within this repository there's guides for finding the data, guides
for data search and for using CMR API to do a search in Python.
And there's a bunch more that I'm going to talk through,
but contributions are welcome.
We really appreciate any feedback we get and try to make improvements
to this regularly.
And so I mentioned the geometry lookup table and the fact that the data is in
raw format. It needs to be ortho rectified.
So we have some nice Python Jupyter notebook tutorials on
how to do that, how to produce an auto rectified output.
And then you can also export that and save it.
So it works more easily in jazz software
within here we've also got examples of how to extract point data.
Lots of times when you're working with spectral data,
you just want to extract the points and use them to build some sort of model
or classifier.
You can easily just take a CSV of points and extract that from the data,
and end up with a nice table that you can use in your model,
sort of like on the right side here
we've got some simple spatial subsetting examples where you can say,
since the image data is very large, being about 1.8GB,
you can subset that down to whatever your region of interest
is, just using a polygon, and then save that example as well.
And lastly, for our normal reflectance and radiance sort of data products,
we have this interactive plotting tool where you can essentially hover over
an RGB image of the data, and it will display
what the current pixel spectra looks like.
And then you can also click
to add points to the figure that'll add them to this plot on the left.
And then you can also export this as a CSV.
So really nice for just sort of exploring the spectra,
which is usually a major part of this sort of research.
Outside of the main radiance and reflectance resources,
we also have some resources for the greenhouse gas products.
This is for the plume product.
So what we have here is the ability to find and visualize a plume extent.
And then you can show that in an interactive plot
you can use this to sort of find what plumes are.
You're interested in and see they overlap and look at them.
In a time series,
you can also generate what's essentially a spectral fingerprint of methane.
And so for this we show an example of extracting radiant spectra.
One falls within a plume and then one that falls outside of a plume.
But it has a similar sort of surface background.
So with this figure on the left you can see
the black line here is essentially the absorption coefficient of methane.
And then you can see to an and out of plume ratios
which essentially follow the same sort of signature.
You can see how the methane affects the radiance if it's present.
And also we have how to build
a standardized time series of a location and map all the plumes.
Here, it's got like a slider bar.
You can move the slider and see the methane emissions
from this landfill and Jordan a bunch of different dates and times.
And then we have an example of calculating the integrated mass.
And for the kilograms of methane within the plume.
And then here we have a visualization where we've plotted
the mass of methane in each of the plumes from this location over time.
And then we've also incorporated here whether or not
there was not an observation, but there was an overpass,
whether that was actually a cloud or there was no plume.
Outside of those resources, we also have AppEEARS,
the application for extracting and exploring analysis ready samples.
This is our subsetting tool.
And we recently added the EMITl1B radiance and the EMITL2A reflectance to this.
You can use it to subset spatially.
And what this does is it's going to reduce the amount of local computing resources
that you need, and also somewhat simplify working with the data sets.
If you really want to work with this data in ENVI, you can use this tool
as just an ENVI converter over your region of interest.
And also it'll perform a point extraction, similar to what I showed in
one of our other resources.
And lastly, it supports ortho rectified or non ortho rectified outputs
which depending on your application you may want to stay working with non
ortho rectified data.
And just to sort of showcase how AppEEARS works, here on
the left is the typical form you see to submit a request.
For points, you can put in a request name and then you can upload a CSV
that has coordinates.
Here, it’ll accept up to four columns.
So you can do an ID, a category, a latitude, and longitude.
You can upload that and it'll appear in this box on the right.
Or you can manually enter that information here.
I'm just submitting a request that has 50 points.
And then I want to get all the EMIT data that exists
from the 1st of January until the end of June of 2023.
So to select those dates and then I can select products down at the bottom.
And here I've just selected the reflectance.
And then I've selected all the layers.
And so what this gives you with the point request is going to be a CSV file
that looks something like up in the top right.
It's basically just going to extract all that data.
And you'll have the relevant metadata and the spectral reflectance.
You can also do this
to get the quality information, like from the mask or the uncertainty.
This is going to do a huge amount of data volume reduction.
So to do this locally you would have needed to download
or access 27.5GB of data.
But using AppEEARS,
you can submit this request and just get back a 12.3MB CSV file.
So huge amount of data reduction and reduction in the amount of work
you have to do.
For area requests, the form is similar and you have sort of similar performance
in terms of data reduction.
So you look at the form: the major difference here
is that you can also specify your file format output,
whether you want to ortho rectify and what projection you want.
And so here I just wanted to showcase that you can select any format as an output.
And so when you do that for this same sort of spatial polygon that was uploaded,
it's going to return a 1 to 1 file from inputs to outputs for netCDF.
For ENVI, there's going to be a couple extra files.
So you're going to have a header for each for like your reflectance.
But then you'll also have a location which is essentially the elevation.
And then additionally if you do a non ortho rectified request,
you would have a geometry lookup table file and header also for each request.
So here you're taking 27.5GB down to just 800.
And you only have to download the data you choose.
So rate reduction simplifying getting data over this region.
Lastly, I'll mention one more resource that we have.
We have the VSWIR Imaging and Thermal Applications learning and Science
repository.
That's a mouthful that you can just remember VITALS.
And the purpose of this repository is just to demonstrate the synergies
between the VSWIR thermal sensors like EMIT and ECOSTRESS.
Since they're both on the space station and they have overlapping fields of view,
you can do some pretty interesting stuff with the data.
And we have some example Jupiter notebooks that do things
like finding concurrent data for two different sensors,
how to process and open both these data sets.
And then we also have some examples that show calculating canopy water content
from EMIT and comparing that to the land surface
temperature for some different classes within the Dangerman preserve.
And lastly, we will go at the NASA SVG Technical Interchange meeting.
We're actually going to do a workshop where we walk through the VITALS
repository.
If you're going to be at the SVG workshop, please attend.
This is on May 30th and it'll also be virtual I believe,
although I don't have the details on that, I'm sure that's something
that will be Googleable in the near future.
And so that's all I have for today.
Please reach out and contact us if you have any questions.
I'll pass it back to Danielle. Great.
Thank you for a great presentation, Erik.
For those of the webinar,
I'm adding links to the chat right now that I have some final information
about EMIT and more information about how to sign up for our next webinar.
At this time.
We'll now move on to our final polling question.
So I'll go ahead and turn those on, as well as add them to the chat right now.
So you should now be seeing the polling questions on your screen.
Again, those are optional.
But these feel free to take a few minutes to answer those questions.
I will also be posting in the chat right now.
For those of you
that aren't able to use the polling feature due to your organization settings.
Reminder: they are the same set of questions
for the polling feature as well as in the chat.
In the past, we've had some users where they couldn't use the forms feature,
so you only need to answer them once, and during that time,
if you have any final questions or feedback about EMIT, the LP DAAC,
or any USGS EROS web based tools, perhaps any features you'd like to see
added in the future, please add those to the chat now as well,
and we'll give you a few moments to answer those polling questions.
All right.
It does look like we have some people answering now.
So with that, I don't see any specific questions in the chat, but
if anyone on the line has any questions, please do feel free to let me know.
The one question that I wanted to make sure we covered: Erik, you did
mention AppEEARS - how can users log into AppEEARS?
What sort of account do they need?
To log into AppEEARS, you just need an EarthData login,
and that's something you would need to download EMIT data anyway and you can,
I think
we've shared the link to sign up for that and I can put it in the chat again.
Perfect. Thank you.
And it looks like we do have a question that came in from Mohammed.
So thank you Mohammed.
How do you get EMIT ten minerals data from the L2B products.
So there is a list of the ten EMIT minerals.
I'm not sure
if that's publicly available, but you can use that to extract the data.
And if you reach out to me, that's something I can find and get for you.
Or if you want to get it from the EMIT team, you can join the EMIT
Slack and ask, and that's something they'll happily provide.
Perfect. Thank you Eric.
See if we have any additional questions that roll in.
For right now, it looks like that's all the questions we have for today.
Don't forget, if you do have additional questions later
on about EMIT or any data, tools or services from the LP DAAC,
you can always email our team at lpdaac@usgs.gov.
I'll throw that email in the chat.
So thank you again everyone for joining us today.
We hope to see you at our next webinar in the future.
If you would like to be notified of upcoming webinars, please do sign up
for the EROS User Group by emailing us custserv@usgs.gov .
And that link was mentioned in the chat earlier.
But with that, we'll thank you all for joining us today.
The team will stay on for a few more minutes
in case we have any additional questions that come in.
But again, thank you everyone for joining us.
If you do have more questions, do feel free to add them to the chat now.
And yes, if anyone on the call has any interest
in joining the EMIT Slack channel, you pass along your email to that
lpdaac@usgs.gov or enter it into the chat, and we'll make sure to get you added.
All right.
It looks like that's all the questions we have today.
So thank you again Erik for a great presentation
and we'll conclude this webinar.
Thanks again for joining us. Have a nice day.