In this video tutorial we use Sentinel-1 data for agricultural monitoring
using a large time series of 25 images acquired throughout one year we will see how the
temporal backscatter changes for different types of crop
For this tutorial we're going to use subsets given that we have a very long time series
The processing will be much faster if we work with subset images, I will open these images in SNAP
These images have been subsetted prior to this exercise
and that was done by
using the raster
subset function
Here you can specify a subset by geographic coordinates
So these images were acquired throughout 2016
Rather than processing each image individually, we're going to use the batch processing function of SNAP
We will also use the graph processing function which enables us to create a processing chain
We go to tools graph builder and
Here we can
specify our processing chain
First we will do a calibration
So we go to radiometric calibration, then we will apply
By the way to create a process you right click with the mouse select add and here you can select a process
So now we will include speckle filtering
Then we will do terrain correction
Radar geometric terrain correction
And finally we'll do a conversion to dB
Raster, data conversion, linear to from dB
Now we need to connect these various processes you can do that by hovering the mouse icon
At the edge of the of each process until the red arrow appears and then clicking and dragging
To the next process so we had calibration then speckle filter
then terrain correction
linear to db and finally
Writing an output image
We can modify the parameters of each of these processes by clicking on each one
We'll leave most as default will only make a few changes
So the speckle filtering will select a Lee filter
the terrain correction we can leave all this default
linear to from dB
and right
Now it's important to note at this stage that we do not run this
processing chain on a single image
What we want to do is run this processing chain on the entire batch
So first we need to save this
processing chain by clicking on save
And we will call this
Agriculture
graph
Now we close this window
and we select
tools
batch processing and
Here we can select this icon to add all the open products
in the list to be batch processed and
Then we load the processing chain to be applied on all of these images
And here you see along the top
The different tabs corresponding to each process in the processing chain
Now we can specify an output folder
And we can select run
The process may take some time given that is applying
various different processes to an entire batch
But at this point you can go and take a coffee or you can do something else while the process is running
When the process finishes it opens all of the output images in the product Explorer window
However the output file name is the same as the input file name
So here we'll have 25 duplicated images, so we'll have 50 images in total
At this point the easiest thing to do is to close all of the images
So select close all products
And then open only the output images
This way we are sure to have only the output images open in the viewer
What we will do now is to
Stack these images together
Into one file with which we can look at different RGB combinations
We go to radar
co-registration
stack tools, create stack and
Here we can add all of the images open
In the create stack tab here we select
Product geolocation as the initial offset method here we have not
Updated the orbit information of the products
But the product geolocation is accurate enough for our purposes
For the output we can rename the file keeping only the
the common parts of the file name
which are common toward the 25 images and
Then here we can select run
Now we can look at some RGB composites of this time series
For example we can look at a polarimetric composite of
images of
the same date
So for example we can select
VV of the first image acquisition on the 12th of January we can assign the VV channel to red
VH channel to green
and for blue we can assign the difference between the VH and the VV
And this is what we get
Another RGB composite, we could do is to look at images of the same polarization but for different dates
so again we go to window open RGB image window and
Here for example we could select only the VH channel
but
of images acquired every four months
We have three channels
So if we assign images acquired every four months then we have an even distribution throughout the year
So the first image can be January the second one can be May
And then for the blue channel we can assign the VH image acquired in September
In the beginning of September
And here we have a very colorful RGB composite of images acquired on different days
What we will do now is to look at
Some fields where we know the crop type
And we have some shape files, which we will overlay onto these fields
So we can open these shape files by going to the layer manager
And selecting the plus icon
selecting ESRI shapefile and
browsing to where we have our shape files so here we have
A field boundary of crops corresponding to these different crop types
We can do that for all of the shapefiles that we have
So here we have fields of known crop types
And we will look at the backscatter signature over time not just for these three days of this RGB composite
but of the entire time series
We can do that by going to view
Tool windows
Radar time series
In the settings we can insert all of the products we have open minus
The stack image
This function works with individual images not with the stack so we remove the stack from the list and then we click on apply
Then we can close this window
And if we select the filter then here we can select which channel
we wish to view for example if you want to see the VH
backscatter over time then we select that and then click on OK and
here we can see the
Temporal backscatter throughout the entire time series for every pixel
On the image and as we move the mouse cursor over the image
as a mouse cursor hits a particular pixel we can see the
backscatter signature over time of that pixel
What we will now do is to compare the backscatter of individual pixels
So first we need to select those pixels, and we do that
by going to
view tool windows pin manager
We can place pins over
particular fields for example
We can start with the potato
Field we can place a pin over this field and we can rename this pin potato
Then we can place a pixel over the spring wheat field and call this spring wheat
We can also change the color here
Sugarbeet
Let's make this red
Winter barley
made this different color
And then winter wheat
And we can make this maybe green
And now if we select this icon here show for all pins
Then here we can see the backscatter signature
Of all the pins compared in the same plot
What's interesting to note is that the signature is the same for some periods of the year
But for other periods there's quite a big difference in the backscatter of the different crop types
The backscatter signature over time varies considerably over different areas
So it may not be possible to derive a unique backscatter signature. That's valid for the same crop in all areas
however this release gives you an indication of the differences in backscatter for different crops over time
I hope you enjoyed the tutorial and thank you for watching
