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Visualize Landsat Images
Sep 2, 2025
Changing the way you visualize satellite images can provide important contrast and information without conducting formal analysis. This tutorial will demonstrate how to easily create false-color satellite images using Landsat imagery. Check out my website for more: https://opensourceoptions.com How to download Landsat images:
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0:01
Welcome to open source options. I have
0:04
QGIS open right now with some LANCAT
0:07
imagery. You can see right here I have
0:09
true color pulled up and you can see
0:12
various details with true color. But if
0:14
I turn off this true color and show you
0:16
this uh color infrared image, you see
0:20
the healthy vegetation pops in red and
0:23
water starts to pop in those dark blue
0:26
colors. Today I'm going to show you how
0:29
you can visualize LANCAT satellite
0:32
imagery very easily in QGIS
0:36
uh and show different band combinations
0:38
to get these false color composits that
0:40
can be super useful for display or for
0:43
analysis. So let's go ahead and get
0:45
started. But first make sure you know
0:48
how to download LANCAT data. I showed
0:50
you how to do that in a previous video.
0:53
We're going to be working with those
0:54
downloaded data. The second thing, go
0:57
check out opensource options.com.
1:00
There may not be courses there yet, but
1:02
I am working on the first course that's
1:04
going to be there. All the courses on
1:06
opensource options.com are going to be
1:08
completely free. Okay. Uh that's how
1:12
we're going to do it. Free courses, free
1:13
GIS, remote sensing, and programming
1:15
courses for everyone. The catch, it's
1:17
going to be slow coming out because it's
1:19
just me working on them, but they will
1:20
be quality professional courses. Now,
1:24
into the LANCAT data, I'm just going to
1:27
start a whole new project here to show
1:28
you how to do this from the beginning.
1:31
So, I'm going to go in. I'm going to
1:32
grab some downloaded LANCAT data. I'm in
1:35
my LANCAT data folder here. I'm going to
1:37
come down to uh this lens set image
1:40
right here and I'm going to come in and
1:44
grab bands one through 7. So I'm going
1:46
to push shift and grab bands one through
1:49
7 and add these in to QGIS. Now I showed
1:53
you how to do this in a previous video,
1:55
so go refresh yourself if you've
1:57
forgotten how to do that. Now I'm going
1:59
to come back to layers here. The thing I
2:02
want to do is I want to create a virtual
2:04
raster. Right now, these are all
2:06
separate layers. They're all separate
2:08
images. I want to combine these into one
2:10
multi-layer image, which will make it
2:13
much easier to show these different band
2:16
combinations as we change our display.
2:18
So, to do that, I'm going to go to
2:20
raster, miscellaneous, build virtual
2:23
raster. I'm going to select my inputs. I
2:26
want to select bends 1 through 7. When
2:29
you do this, make sure they are all in
2:30
the correct order. If they are not
2:32
listed in the correct order, then you
2:34
will have a very hard time knowing which
2:36
band number corresponds to which LANCAT
2:40
image or which LANCAT band. Once you
2:42
have this, click okay on the top up
2:44
here.
2:46
Now, you want to make sure you place
2:47
each input file into a separate band. We
2:51
can leave the other defaults. I will
2:53
save this to a uh a file so we can come
2:56
back and access it if we need to. And
2:59
these are this image here uh that starts
3:03
with the 039030.
3:07
Going to open that up and I'm going to
3:09
save this as I'm just going to call it
3:12
as our stacked images VRT.
3:15
And I'm going to click save
3:19
and I'm going to click run. And I'll
3:22
click close. So I zoomed out too far.
3:25
We'll fix that in a sec. Now I'm going
3:27
to remove all these individual bands.
3:30
Remove layers. And I'll remove this
3:32
layer.
3:35
And I'll right click here and select
3:38
zoom to layer. Now you can see we have
3:40
some color.
3:43
Now there's going to be a trick to this.
3:46
This is not true color. We're just
3:48
showing bands one. Band one is red. Band
3:51
two is green. Band three is blue. What
3:54
we need to do is assign the correct band
3:57
to the correct color to get true color.
4:00
So let's show you how we can figure out
4:02
this information. If I go in um
4:06
and I just searched here for LANCAT band
4:09
combinations and these are for Lancet
4:12
the Lancet 8 and 9 OI which is the data
4:16
we are using. So we can see here that
4:18
for true color we can use the band
4:21
combination 432 for LANCAT 89. If you're
4:25
using different LAN set you can see how
4:26
those would look here. The other thing
4:29
you can search for is
4:32
LANCAT band wavelengths.
4:39
And we can come to LANCAT 8 and take a
4:41
look at this
4:45
here if it ever loads. There it goes.
4:47
And if we scroll down, you can see it
4:50
gives us the band names like blue,
4:52
green, red, near infrared, short wave
4:54
infrared. And also the wavelengths uh in
4:58
micrometers here. And so we can use
5:00
these if we don't know uh which band
5:04
goes to blue, green or red, and we find
5:06
another band combination that we want to
5:08
try. All right, let's go back to QGIS.
5:12
Let's go back and look at these. So true
5:14
color is going to be 432. Let's go uh
5:17
visualize that to start.
5:20
So, QGIS, we're going to change red to
5:23
four, green to three, blue to two. And
5:27
there you go. You can see we now have
5:29
that true color image looking as it
5:32
should. All right. Now, let's try to do
5:36
uh a color infrared. Very easy. We just
5:39
change this to five 4 3. And now we have
5:45
color infrared. And you can see how that
5:47
vegetation really stands out. It's that
5:50
bright red. We can see those irrigated
5:52
fields next to the unerrigated uh lands.
5:56
And we can see that water becomes these
5:58
very dark colors uh blues to getting
6:01
into black. And then we can see this
6:03
vegetation here that's not irrigated.
6:05
The natural vegetation uh is a little
6:07
darker red. And if we zoom in on these
6:09
valley bottoms where there's probably
6:10
some riparian water, some water,
6:12
riparian vegetation, we can see they're
6:14
brighter red. So, this can be a very
6:16
useful combination for visualizing
6:19
vegetation. Let's go take a look at some
6:21
of these other combinations combinations
6:24
we might try. We can try Oops. Let me
6:26
reset that. We can try uh this urban
6:29
faults color,
6:33
which is going to be 764. Let's go give
6:35
that one a try. QGIS. So we just come
6:38
and go seven,
6:41
six, four. And this will help us
6:44
identify urban areas. And so if we zoom
6:46
in where it's urban, indeed we can see
6:48
some definition in that urban zone.
6:52
Pretty cool. And let's go take a look.
6:56
Well, before we take a look at that, let
6:57
me explain what is happening. So I
7:00
showed you in the last image or the last
7:02
video where we downloaded the images how
7:04
every band is just a simple grayscale
7:06
image uh by itself is just scaled with a
7:09
single color and we just see that
7:11
variation in that single band. Now what
7:14
we are doing is we're displaying these
7:16
different bands with different colors.
7:17
So in this instant B instance band 7
7:21
which if we go back here to this which
7:25
is our shortwave infrared is being
7:28
displayed in the color red. Instead of
7:31
showing red as red, we're showing the
7:32
shortwave infrared as red. Band six,
7:36
which is also shortwave infrared but at
7:39
a different wavelength is being
7:41
displayed as green. And band four, which
7:43
is red, is being displayed as blue. And
7:47
so we change the values for those
7:49
colors, we get these unique um
7:53
unique color hues describing different
7:56
land cover types. So it's a really cool
7:58
way to visualize our data. All right,
8:01
let's go take a look at another one of
8:02
these color combinations and let's try
8:06
this one for vegetative analysis, uh
8:09
which is going to be 654.
8:12
Let's go back to QGIS. And again, we'll
8:14
just change this to six, this to five,
8:17
and that to four. And here you can see
8:20
we get the vegetation popping out in
8:23
green on some of those unveated or drier
8:26
areas coming out in that pink color.
8:29
This is a really neat way to look at
8:31
things. Again, our water is very dark.
8:33
it absorbs um most of the most of the
8:39
light from band six and five. That's a
8:42
really neat way to to see our
8:44
vegetation. And if you notice the last
8:46
one, we'll take a look at this. We can
8:48
just change that to 754 for our
8:51
shortwave infrared and we're going to
8:53
get a very similar result. But you'll
8:55
notice here, let's look at this one
8:57
particular area. It looks like this may
9:00
have been a forest fire and we can see
9:01
that really pops in that red when we
9:03
change to a different wavelength for a
9:05
shortwave infrared.
9:08
Okay, so you can see how visualizing
9:10
Lancet data with these different band uh
9:13
with with these different band
9:14
combinations and these different false
9:16
color composite images can give you a
9:19
lot of information without conducting a
9:22
formal analysis. All right, everyone.
9:24
Thanks for watching. I hope you found
9:26
this useful. I hope that this helps you
9:28
understand LANCAT imagery a little
9:30
better and helps you make some great
9:32
visualizations. If you have questions or
9:34
suggestions for other videos, leave them
9:36
in the comments below. Again, thanks for
9:38
watching and have a wonderful day.
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