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This remote sensing workshop is

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designed for spatial analysis

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personnel for creating live

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vegetation fractional cover maps

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with Sentinel data. We will

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show download and import,

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optical and SAR image data, use

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image-processing tools to

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transform the satellite data to

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maps that represent live

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vegetation cover, use SAR image-processing

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tools to create maps

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indicating the vegetation cover density, 

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add value to the

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produced maps by portraying

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thematic information with color

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rendering. The objective is,

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although the procedures learned

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can be applied to processing of

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any raster data, this course is

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specific to the production of

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live cover status and change

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maps in the management of NRT [Northern Rangelands Trust]

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natural resources. For

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downloading Sentinel optical and

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SAR data, this is the Copernicus

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Open Access Hub. The link is

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provided in the handbook.

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One has to register to download data.

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We can go change our layer.

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Let's bring up the

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satellite image.

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OK

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We can zoom in and

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zoom out.

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We are OK. 

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That is the navigation tool.

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Then, we go for selection, and we

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take an area of interest, drop

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this down. OK. The sensing period,

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when we want to collect the data,

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I usually go month to month.

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Let's see if we have any data.

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We'll take January 1. You can go

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to any year, any period, and all

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this data is free of cost. 

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And, we have different...

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You can take the radar data is

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Sentinel-1. The optical data is

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Sentinel-2. We take Sentinel-2,

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and you can select 2A

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and 2B. Both these satellites

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are in tandem, five days of

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difference in collection of data

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and product type, and 1C is non-

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atmospheric corrected data, and

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2A is atmospherically corrected data

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so we select 2A. 

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Next, we hit the search button, and it

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gives you the number of images

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over that area in that period.

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If you go see, it seems like

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January 2 was also very cloudy

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over our area of interest, you

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can just scroll down. 

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This image looks good, if you want to

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look at it. We select this,

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which is this image. Then, go view it. 

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It brings to the image,

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it brings up the image. You can

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see all the detail here. And then if

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you're OK, this has a lot of

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clouds, but if it's a cloud-free

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image and you're OK with the image,

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you hit the download

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button, or we close it, and you can

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go and search each image.

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That's the problem.  I'm in the, I have to be

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in this mode. You select the

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image, and it goes to that

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particular image. You can go and

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look at your images and see if

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they are cloud free, you

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download them. OK? Similarly, you

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can go up here again.

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You can change your satellite.

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You go to Sentinel-1. You select the 

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platform 1A or 1B. 

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So the product type will be, we select GRD 

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SLC is Single Look Complex 

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which is used when

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applying inSAR processing.

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GRD is Ground Range Detected,

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is georeferenced data projected

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using Earth ellipsoid model.

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For polarization, we take both

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VV and VH. In sensor mode, we

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take IW which is Interferometric Wide. 

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It gives us a swath of 250

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kilometers. We hit OK.  

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That shows our coverage, and similarly,

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you select the image that you want,  

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and you can view it and then download.

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For live vegitation 

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map products, nine 

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Sentinal images were used. Here, as example,

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I will use two Sentinel images,

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which cover part of the core and

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NRT region. So open image data in

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SNAP. We go to File, 

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Import, Optical Sensors, Sentinel-2,

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L2A, that is atmospherically 

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corrected data. Go to the

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right folder. We bring up Tile 5

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and Tile 8. I'm calling my nine

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images as tiles 1 to 9. So we

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go to 819. We go to

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Tile 5, May, original, and we open

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this folder and select the XML

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and import products. 

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Another way of bringing in the product

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is go to the Folder, Tile 9, and

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just drag and drop the XML file.

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We right click on the product,

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Open RGB Image Window. Select

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the bands for false color 

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composite.

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OK. Do the same for the next one. OK. 

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So now we have two tiles, one and two.

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We can display these tiles 

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vertically. As we scroll this

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image up, we can see the vertical, this overlap

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overlap right here. Now we will

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mosaic these images. To mosaic 

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the images, we first have to

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resample a requirement in SNAP

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Processing. Go to Raster,

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Geometric Operations, 

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resampling. 

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It's the first product. We can

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rename this. Make it shorter.

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OK, Save as di-map and go

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to the libr...

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to the folder you want to save

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it in. We have a folder created

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and resampling parameters, and

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it should be... [no speaking]

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We will select

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band 4, and... [no speaking]

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[no speaking] Resampling is bi-linear, and 

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we hit Run. So this shows that the tile

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has been successfully resampled,

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and now the product is opened in

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SNAP. We hit OK. Close this  

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and run the same on our second image.

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We have both the tiles resampled.

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Next, we go and mosaic

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them. So we add the images,  

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which is one and two. Open, and 

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we will give it a name. This is S2A.

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We select our folder, 

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which is... 

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So we are in Tile 9 and 8. 

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We select Mosaic, and select, Go to Image

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Project Definition, Custom,

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CRS reference system. We take it 

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as WGS84. Next, we go and set

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our pixel size. Zero. We will display

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our source products and zoom

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into the area. Then we have

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Variable Conditions. We go and

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select the bands we need.

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We want mosaic. We will select Band 3, 

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Band 4, and Band 8. 

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OK, and then we run it. 

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It is very important that each time we

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create a new band, we must save

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the product, Save Product.

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This is the two tile mosaic May 2019 image. Let's view the RGB.

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This is a false color image. In

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Remote Sensing, false color is

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preferred over the natural color

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because the use of NIR band

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increases the spectral

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separation and thus enhances the

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interpretability of the data.

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The vegetation is all in shades

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of red. Next, we create the

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MSAVI2. MSAVI2 is the

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abbreviation of modified soil

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adjusted vegetation index. 

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This index was selected for this

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project as it has proven

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capability to minimize the soil

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influence in remote sensing data

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and can easily be used in an

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operational mapping system.

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Before we apply the MSAVI2 equation 

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we will scale Band 4

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and Band 8. We go to Band Math 

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and give it a name. Go to Edit

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Expressions. Band 400, and hit OK

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After scaling Band 4 and 8,

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we apply the MSAVI2 equation

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using these scale bands.

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Band Maths

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Edit it for the 

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expression. The formula, 

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the equation is there in the

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handbook. We can just copy it

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and paste it, and hit OK.

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Displayed here is the MSAVI2

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band created. Next step is the

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calibration of this satellite,

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MSAVI2. The model equation to be

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used here was created using the

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MSAVI2 calculated from field and

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satellite data collected at the

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same land surface locations.

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Using the equation, the

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satellite MSAVI2 is calibrated

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to field MSAVI2. Right click 

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on the product Band Maths, 

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Edit Expression. We have the equation

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in our handbook. Paste it and

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hit OK. This calibrated

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satellite, MSAVI2 to field

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MSAVI2 will be used to replace

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the field MSAVI2 in the equation,

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field MSAVI2 to vegetation LFC

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calibrations. The detailed

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explanation of the procedure is

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given in the USGS Open-File 

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Report referenced in the 

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handbook. Now we create the

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live vegetation fractional cover

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map using the developed model

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equation 2. Right click on the

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Product, Band Maths, Edit

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Expression. We will copy the

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expression from the handbook, 

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the model expression. Here, we

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have multiplied the vegetation

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map by 2.55

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to stretch 0 percent to 100 

295
00:15:12,400 --> 00:15:14,766
percent range to the full 8U 

296
00:15:14,766 --> 00:15:18,266
range of 0 percent to 255 percent.  

297
00:15:18,266 --> 00:15:20,866
Next hit OK. 

298
00:15:20,866 --> 00:15:24,199
We have created

299
00:15:24,200 --> 00:15:27,900
a May 2019 veg status map. Next,

300
00:15:27,900 --> 00:15:28,100


301
00:15:28,100 --> 00:15:30,400
we will convert the veg map from

302
00:15:30,400 --> 00:15:32,466
decimal format to integer format.

303
00:15:32,466 --> 00:15:37,666
We go to Raster, Data Conversion,

304
00:15:37,666 --> 00:15:37,766


305
00:15:37,766 --> 00:15:46,299
Convert Datatype. We select 

306
00:15:46,300 --> 00:15:51,966
the product. We will change the name,

307
00:15:51,966 --> 00:15:57,699
VegMap. Go to the right

308
00:15:57,700 --> 00:16:01,266
folder, select the folder. In

309
00:16:01,266 --> 00:16:03,932
the Processing Parameters,

310
00:16:03,933 --> 00:16:04,899


311
00:16:04,900 --> 00:16:08,000
select the image that you want

312
00:16:08,000 --> 00:16:18,900
converted. We will select 8U. We

313
00:16:18,900 --> 00:16:32,500
will truncate it. Run it. Once

314
00:16:32,500 --> 00:16:34,500
it's done, the product will open

315
00:16:34,500 --> 00:16:47,900
in SNAP. We see here that the

316
00:16:47,900 --> 00:16:51,500
product is opened here. We close this. 

317
00:16:51,500 --> 00:16:59,400
As I said before, every

318
00:16:59,400 --> 00:17:01,900
time you create a product

319
00:17:01,900 --> 00:17:05,900
or a band, you have to save the

320
00:17:05,900 --> 00:17:10,100
product. Save Product. Also, we

321
00:17:10,100 --> 00:17:12,800
see that when we convert it,

322
00:17:12,800 --> 00:17:12,900


323
00:17:12,900 --> 00:17:15,500
it keeps the same name of the Band

324
00:17:15,500 --> 00:17:15,800


325
00:17:15,800 --> 00:17:20,200
image file. We will display this.

326
00:17:20,200 --> 00:17:25,833
[no speaking]

327
00:17:25,833 --> 00:17:40,799
OK.  We go to Pixel Information. You can 

328
00:17:40,800 --> 00:17:43,700
see the value at that point

329
00:17:43,700 --> 00:17:47,700
where your cursor is. Just to

330
00:17:47,700 --> 00:17:49,100
show the difference, we will go

331
00:17:49,100 --> 00:17:50,800
to the Band before it was

332
00:17:50,800 --> 00:17:53,800
converted to an integer.

333
00:17:53,800 --> 00:17:55,000


334
00:17:55,000 --> 00:18:00,400
We highlight it. Go to the Product.

335
00:18:00,400 --> 00:18:02,700
Go to Pixel Information,

336
00:18:02,700 --> 00:18:06,500
and you see the decimals there.

337
00:18:06,500 --> 00:18:07,800


338
00:18:07,800 --> 00:18:19,733


339
00:18:19,733 --> 00:18:22,699
We will now create 2019-2018 difference vegetation

340
00:18:22,700 --> 00:18:27,400
map. We must have both the 2018

341
00:18:27,400 --> 00:18:30,100
and 2019 vegetation

342
00:18:30,100 --> 00:18:30,300


343
00:18:30,300 --> 00:18:34,300
map products open in SNAP. So we 

344
00:18:34,300 --> 00:18:37,000
have 2019 up here. We will go

345
00:18:37,000 --> 00:18:38,700
and bring up our 2018

346
00:18:38,700 --> 00:18:39,300


347
00:18:39,300 --> 00:18:48,666
map. OK. Next, we go to

348
00:18:48,666 --> 00:18:57,299
Band Math. In the handbook you

349
00:18:57,300 --> 00:18:58,666
will see that we have done...

350
00:18:58,666 --> 00:19:00,366
I've shown the process of using

351
00:19:00,366 --> 00:19:00,466


352
00:19:00,466 --> 00:19:05,866
2018 map. Here, we will use 2019

353
00:19:05,866 --> 00:19:09,099
and we will name the project, 

354
00:19:09,100 --> 00:19:20,100
name the Band as 2018 VegMap... 

355
00:19:20,100 --> 00:19:27,600
then go to Edit. OK. 

356
00:19:27,600 --> 00:19:34,666
Expression. We have to dropdown

357
00:19:34,666 --> 00:19:38,232
and select the 2018 image. 

358
00:19:38,233 --> 00:19:45,066


359
00:19:45,066 --> 00:19:55,699
And index. I'll go before that,

360
00:19:55,700 --> 00:20:05,866
sorry. We selected before. Then times

361
00:20:05,866 --> 00:20:11,199
one. We want to copy it

362
00:20:11,200 --> 00:20:15,233
into this folder. OK and OK.

363
00:20:15,233 --> 00:20:16,999


364
00:20:17,000 --> 00:20:38,700
[no speaking] As we had seen that we get an

365
00:20:38,700 --> 00:20:40,866
error message. So before we do

366
00:20:40,866 --> 00:20:43,399
anything, we go and save the

367
00:20:43,400 --> 00:20:46,400
file and save it as a session.

368
00:20:46,400 --> 00:20:51,900
Save Session As, and save it,

369
00:20:51,900 --> 00:20:53,266
give it a name.

370
00:20:53,266 --> 00:21:08,599
2019-2018DiffVegMap. Save it in the

371
00:21:08,600 --> 00:21:11,000
folder and hit Save. OK. 

372
00:21:11,000 --> 00:21:16,200


373
00:21:16,200 --> 00:21:19,400
Here we see that a virtual band has

374
00:21:19,400 --> 00:21:22,000
been created. We go right-click

375
00:21:22,000 --> 00:21:28,700
and Convert Band. Then we go

376
00:21:28,700 --> 00:21:30,600
here to the Product

377
00:21:30,600 --> 00:21:40,800
and go Save Product.

378
00:21:40,800 --> 00:21:42,700
It is very important that you

379
00:21:42,700 --> 00:21:44,000
save the product. Otherwise,

380
00:21:44,000 --> 00:21:47,800
when you reopen the product, it will not... the

381
00:21:47,800 --> 00:21:50,800
band will not be there. [no speaking] OK.

382
00:21:50,800 --> 00:22:10,866
OK, and we will display it, right there.

383
00:22:10,866 --> 00:22:14,099


384
00:22:14,100 --> 00:22:16,466
We now have the 2019 and 2018

385
00:22:16,466 --> 00:22:20,899
veg maps in the same product

386
00:22:20,900 --> 00:22:23,400
folder. We will now calculate

387
00:22:23,400 --> 00:22:25,200


388
00:22:25,200 --> 00:22:28,500
the difference image.

389
00:22:28,500 --> 00:22:29,300


390
00:22:29,300 --> 00:22:31,766
Go to the product, right-click Band

391
00:22:31,766 --> 00:22:38,566
Maths, and change the file name.

392
00:22:38,566 --> 00:22:52,699


393
00:22:52,700 --> 00:23:00,000
Edit Expression. This is our

394
00:23:00,000 --> 00:23:02,700
expression, one difference. 

395
00:23:02,700 --> 00:23:03,800


396
00:23:03,800 --> 00:23:08,700
We select 2019 and we

397
00:23:08,700 --> 00:23:11,400
select 2018. OK, OK, and OK.

398
00:23:11,400 --> 00:23:29,700


399
00:23:29,700 --> 00:23:30,800
Displayed is the difference

400
00:23:30,800 --> 00:23:33,400
vegetation map. Now we will

401
00:23:33,400 --> 00:23:35,400
transform this decimal to an

402
00:23:35,400 --> 00:23:41,766
integer format. Right-click Band

403
00:23:41,766 --> 00:23:45,766
Maths and we will give it a name,

404
00:23:45,766 --> 00:23:45,866


405
00:23:45,866 --> 00:23:53,166
difference veg map 2019

406
00:23:53,166 --> 00:23:54,299


407
00:23:54,300 --> 00:23:56,000
2018

408
00:23:56,000 --> 00:23:56,300


409
00:23:56,300 --> 00:24:07,700
and 16 S. Edit

410
00:24:07,700 --> 00:24:18,900
Expression. Select the... We will first go and

411
00:24:18,900 --> 00:24:20,500
take a function. We want to convert it, 

412
00:24:20,500 --> 00:24:21,200


413
00:24:21,200 --> 00:24:31,100
round it. Where is it? Round. We

414
00:24:31,100 --> 00:24:33,966
select this, and we select a

415
00:24:33,966 --> 00:24:35,866
difference map. OK and OK.

416
00:24:35,866 --> 00:24:50,799


417
00:24:50,800 --> 00:24:52,666
Displayed is the difference map

418
00:24:52,666 --> 00:24:57,499
that we just created. Every time

419
00:24:57,500 --> 00:25:00,500
SNAP creates a virtual band, we 

420
00:25:00,500 --> 00:25:02,400
have to go and convert the band

421
00:25:02,400 --> 00:25:16,000
and save the product. After the

422
00:25:16,000 --> 00:25:18,100
product has been saved, we will

423
00:25:18,100 --> 00:25:19,600
go and display the band again.

424
00:25:19,600 --> 00:25:25,000
Displayed is the 16S integer

425
00:25:25,000 --> 00:25:28,500
image we just created. We will

426
00:25:28,500 --> 00:25:33,500
go and we look at the histogram,

427
00:25:33,500 --> 00:25:37,900
and we will clip it to 100. So, the 

428
00:25:37,900 --> 00:25:40,800
minimum value is -114,

429
00:25:40,800 --> 00:25:41,100


430
00:25:41,100 --> 00:25:44,700
and the maximum is 163. 

431
00:25:44,700 --> 00:25:46,500


432
00:25:46,500 --> 00:25:52,000
Basically 163 is an outlier. The values are between... the highest

433
00:25:52,000 --> 00:25:59,500
value goes to 113. We go to 

434
00:25:59,500 --> 00:26:12,566
Band Maths. -114 is to zero and the high 

435
00:26:12,566 --> 00:26:13,099


436
00:26:13,100 --> 00:26:15,466
upper limit, we will set it to

437
00:26:15,466 --> 00:26:18,999
100. We'll give it a file name

438
00:26:19,000 --> 00:26:23,200
and Edit Expression. We'll

439
00:26:23,200 --> 00:26:25,800


440
00:26:25,800 --> 00:26:30,800
select an operator if/then. 

441
00:26:30,800 --> 00:26:35,666
This will be our band, 16S.

442
00:26:35,666 --> 00:26:39,532


443
00:26:39,533 --> 00:26:47,033
If it is greater than 100, zero, 

444
00:26:47,033 --> 00:27:02,166
then it is 100, else it is equal 

445
00:27:02,166 --> 00:27:11,166
to this. OK. OK and OK.

446
00:27:11,166 --> 00:27:17,132


447
00:27:17,133 --> 00:27:19,433
Displayed here is the clipped 

448
00:27:19,433 --> 00:27:22,766
to 100 difference vegetation map.

449
00:27:22,766 --> 00:27:24,966


450
00:27:24,966 --> 00:27:26,166
If you look at the histogram,

451
00:27:26,166 --> 00:27:26,266


452
00:27:26,266 --> 00:27:27,866
you'll see that the minimum

453
00:27:27,866 --> 00:27:28,299


454
00:27:28,300 --> 00:27:32,900
still shows is -114 and the max

455
00:27:32,900 --> 00:27:36,500
is 100. This will be truncated 

456
00:27:36,500 --> 00:27:38,100


457
00:27:38,100 --> 00:27:43,233
when we convert this image to 8U. 

458
00:27:43,233 --> 00:27:45,599
Again, it's a virtual band.

459
00:27:45,600 --> 00:27:52,200
We convert it to Convert Band, 

460
00:27:52,200 --> 00:27:56,100
and go

461
00:27:56,100 --> 00:27:57,533
Save Product. [no speaking] 

462
00:27:57,533 --> 00:28:09,733


463
00:28:09,733 --> 00:28:12,466
So the Clip 100 image band is being

464
00:28:12,466 --> 00:28:12,599


465
00:28:12,600 --> 00:28:14,966
created. To display it, we

466
00:28:14,966 --> 00:28:16,666
double-click on the band. 

467
00:28:16,666 --> 00:28:16,766


468
00:28:16,766 --> 00:28:21,499
Next we're going to scale the 0 to 100

469
00:28:21,500 --> 00:28:24,400
to 0 to 255.

470
00:28:24,400 --> 00:28:25,900
[no speaking]

471
00:28:25,900 --> 00:28:33,666
We go to Band Maths. 

472
00:28:33,666 --> 00:28:41,799
Name the image. Edit Expression.

473
00:28:41,800 --> 00:28:46,100
We'll use the expressions as

474
00:28:46,100 --> 00:28:48,066
given in the handbook. We'll use 

475
00:28:48,066 --> 00:28:48,932
the round functions.  

476
00:28:48,933 --> 00:28:55,933
[no speaking]

477
00:28:55,933 --> 00:29:06,033
[no speaking]

478
00:29:06,033 --> 00:29:44,199
And this... 114 divided by (114--100))*255). 

479
00:29:44,200 --> 00:29:47,366
We have couple of parenths here.

480
00:29:47,366 --> 00:30:11,799
One, two. OK, and OK, and OK. Display the

481
00:30:11,800 --> 00:30:13,800
scaled image from  to 255. 

482
00:30:13,800 --> 00:30:15,900
If you go and look at the histogram,

483
00:30:15,900 --> 00:30:19,000
you see the scale image, 0 to 255.

484
00:30:19,000 --> 00:30:25,666
Virtual Image Band, Convert Band, 

485
00:30:25,666 --> 00:30:38,166
and Save Product. 

486
00:30:38,166 --> 00:30:40,099
After saving the product, we display

487
00:30:40,100 --> 00:30:44,000
the band. OK next step is to 

488
00:30:44,000 --> 00:30:48,866
convert the 16S to 8U numerical format. 

489
00:30:48,866 --> 00:30:51,266
We go  

490
00:30:51,266 --> 00:30:54,532
to Raster, 

491
00:30:54,533 --> 00:30:55,099


492
00:30:55,100 --> 00:31:07,800
Data Conversion, Convert Data Type.

493
00:31:07,800 --> 00:31:12,566
And our source is 2019.  

494
00:31:12,566 --> 00:31:20,966
And we want to... convert the 

495
00:31:20,966 --> 00:31:22,799
 difference image. 

496
00:31:22,800 --> 00:31:27,900
DiffVegMap 

497
00:31:27,900 --> 00:31:38,633
2019-2018

498
00:31:38,633 --> 00:31:43,699
We write it. Here put, oops!

499
00:31:43,700 --> 00:31:44,800
black and white.

500
00:31:44,800 --> 00:31:53,000
OK it will go to the 

501
00:31:53,000 --> 00:31:55,700
Mosaic, same folder. Select

502
00:31:55,700 --> 00:31:57,300
Processing Parameters. We'll go

503
00:31:57,300 --> 00:32:01,600


504
00:32:01,600 --> 00:32:04,566
to the image. We want to convert it. 

505
00:32:04,566 --> 00:32:05,332
We want to convert it to 8U.  

506
00:32:05,333 --> 00:32:06,566
it. We want to convert it to 8U.

507
00:32:06,566 --> 00:32:06,666


508
00:32:06,666 --> 00:32:08,166
We will truncate it to  and run

509
00:32:08,166 --> 00:32:10,066


510
00:32:10,066 --> 00:32:10,599


511
00:32:10,600 --> 00:32:15,100
We will truncate it to zero. 

512
00:32:15,100 --> 00:32:15,966


513
00:32:15,966 --> 00:32:18,799
and run it. 

514
00:32:18,800 --> 00:32:38,666
[no speaking while file renders]

515
00:32:38,666 --> 00:32:40,932
The conversion to 8U from 16S

516
00:32:40,933 --> 00:32:41,499


517
00:32:41,500 --> 00:32:43,466
provides a less complex data

518
00:32:43,466 --> 00:32:46,666
structure for color renditions

519
00:32:46,666 --> 00:32:48,799
and GIS applications.

520
00:32:48,800 --> 00:33:02,100
 

521
00:33:02,100 --> 00:33:08,133
Now we will export this product created the 8U format product.  

522
00:33:08,133 --> 00:33:11,933
We click on the Product. Go to

523
00:33:11,933 --> 00:33:17,333
File, Export. We will export in

524
00:33:17,333 --> 00:33:17,433


525
00:33:17,433 --> 00:33:19,333
this format which is recognized 

526
00:33:19,333 --> 00:33:26,333
by QGIS. Slash and go to the folder. 

527
00:33:26,333 --> 00:33:27,533


528
00:33:27,533 --> 00:33:34,233
[no speaking while going to the folder] 

529
00:33:34,233 --> 00:33:49,833


530
00:33:49,833 --> 00:33:54,933
We have created the vegetation status map, and the vegetation difference map. Next, we will

531
00:33:54,933 --> 00:34:00,633
develop a color ramp for both

532
00:34:00,633 --> 00:34:03,233
these maps. We go to the

533
00:34:03,233 --> 00:34:07,033
Vegetation Status Map and hit

534
00:34:07,033 --> 00:34:07,533


535
00:34:07,533 --> 00:34:09,433
Color Manipulation, which gives 

536
00:34:09,433 --> 00:34:11,933
you the histogram. We will set

537
00:34:11,933 --> 00:34:18,433
it to 100. OK. So now, we will apply

538
00:34:18,433 --> 00:34:21,433
the colors that we have given

539
00:34:21,433 --> 00:34:23,999
in the handbook. There's color 1

540
00:34:24,000 --> 00:34:28,533
and 2 for the vegetation status

541
00:34:28,533 --> 00:34:31,699
map. To set the colors, to

542
00:34:31,700 --> 00:34:34,033
change colors, I'll just show

543
00:34:34,033 --> 00:34:35,899
you how we do it. You click on

544
00:34:35,900 --> 00:34:39,133
this, and you can get the colors here.

545
00:34:39,133 --> 00:34:42,099
Next, if you click on this,

546
00:34:42,100 --> 00:34:44,933
you can go and change the text, 

547
00:34:44,933 --> 00:34:51,133
and if you click between the 

548
00:34:51,133 --> 00:34:54,433
two sliders, left-click, you

549
00:34:54,433 --> 00:34:54,833


550
00:34:54,833 --> 00:34:59,133
can add a new slider. To remove

551
00:34:59,133 --> 00:35:03,933
a slider, you go left-click on

552
00:35:03,933 --> 00:35:05,699
the slider and you can remove

553
00:35:05,700 --> 00:35:08,800
the slider and you can add a

554
00:35:08,800 --> 00:35:08,900


555
00:35:08,900 --> 00:35:14,100
slider also from here. 

556
00:35:14,100 --> 00:35:15,500


557
00:35:15,500 --> 00:35:17,733
So we will select the lower limit and

558
00:35:17,733 --> 00:35:22,233
choose our color. So we have the

559
00:35:22,233 --> 00:35:24,299
color. This dialog appears.

560
00:35:24,300 --> 00:35:27,900
We'll select the RGB, either you

561
00:35:27,900 --> 00:35:28,733


562
00:35:28,733 --> 00:35:41,066
can give the RGB colors. [no speaking while  color selections are being made] 

563
00:35:41,066 --> 00:35:51,932
And hit OK. Next, we will take the

564
00:35:51,933 --> 00:35:55,133
upper limit, choose the color

565
00:35:55,133 --> 00:35:58,633
RGB, and we can give the color

566
00:35:58,633 --> 00:36:08,733
code, which is 9ACD32, and OK.

567
00:36:08,733 --> 00:36:18,066
We don't need the center slider, 

568
00:36:18,066 --> 00:36:20,899
So we will left-click and remove

569
00:36:20,900 --> 00:36:27,533
the slider. So we have the color set.

570
00:36:27,533 --> 00:36:29,033
Now, we can also export

571
00:36:29,033 --> 00:36:34,633
these, can apply to other bands, 

572
00:36:34,633 --> 00:36:39,366
or we can save the colors

573
00:36:39,366 --> 00:36:44,032
to a text palette. So, we click on this, 

574
00:36:44,033 --> 00:36:48,733
and you can save your

575
00:36:48,733 --> 00:36:51,933
colors. I already have it saved

576
00:36:51,933 --> 00:36:54,133
here, so you can go and give it

577
00:36:54,133 --> 00:37:01,033
a name, VegStatus. Then you can

578
00:37:01,033 --> 00:37:02,433
use it for other years. 

579
00:37:02,433 --> 00:37:08,466
Cancel

580
00:37:08,466 --> 00:37:11,332
So this is a classified vegetation

581
00:37:11,333 --> 00:37:14,233
status map. Normally, in

582
00:37:14,233 --> 00:37:14,533


583
00:37:14,533 --> 00:37:16,633
a classified map, we have

584
00:37:16,633 --> 00:37:18,433
thematic classes such as soil,

585
00:37:18,433 --> 00:37:20,999
grass, trees, etc. This is a

586
00:37:21,000 --> 00:37:22,233
biophysical classification,

587
00:37:22,233 --> 00:37:24,699
meaning, mapping a quantity of

588
00:37:24,700 --> 00:37:27,133
something, for example biomass.

589
00:37:27,133 --> 00:37:30,233
In this case, we are mapping the

590
00:37:30,233 --> 00:37:32,133
percent cover of live vegetation,

591
00:37:32,133 --> 00:37:34,999
more specifically, grasses and

592
00:37:35,000 --> 00:37:38,800
forbs per 10 by 10 meter pixel

593
00:37:38,800 --> 00:37:38,900
because it is 

594
00:37:38,900 --> 00:37:40,900
a Sentinel image. 

595
00:37:40,900 --> 00:37:43,633
For Landsat, it would be 

596
00:37:43,633 --> 00:37:45,333
30 meter by 30 meter. 

597
00:37:45,333 --> 00:37:48,433
We will create the legend in QGIS later,

598
00:37:48,433 --> 00:37:50,833
but what do the colors represent?

599
00:37:50,833 --> 00:37:52,999
The very bright green shows

600
00:37:53,000 --> 00:37:55,233
higher percent coverage of live

601
00:37:55,233 --> 00:37:57,233
vegetation. The lighter 

602
00:37:57,233 --> 00:37:58,033
shades of green 

603
00:37:58,033 --> 00:38:00,033
are low percent cover,

604
00:38:00,033 --> 00:38:00,333


605
00:38:00,333 --> 00:38:03,633
and the shades of brown are less

606
00:38:03,633 --> 00:38:07,233
cover or no vegetation cover at all. 

607
00:38:07,233 --> 00:38:08,033


608
00:38:08,033 --> 00:38:13,333
We can also, if we go to the World

609
00:38:13,333 --> 00:38:17,133
View, it shows us where we are.

610
00:38:17,133 --> 00:38:17,633


611
00:38:17,633 --> 00:38:21,133
This frame, you can zoom in. We

612
00:38:21,133 --> 00:38:23,299
see all the forest trees, very

613
00:38:23,300 --> 00:38:25,333
high trees. Forested area is

614
00:38:25,333 --> 00:38:27,833
appearing very bright. We have

615
00:38:27,833 --> 00:38:30,533
some cloud cover, which is shown

616
00:38:30,533 --> 00:38:35,633
by the brown. This is a

617
00:38:35,633 --> 00:38:38,233
vegetation status map. I've also

618
00:38:38,233 --> 00:38:39,533
displayed the false color

619
00:38:39,533 --> 00:38:43,699
composite. We will link

620
00:38:43,700 --> 00:38:49,133
both these images, and zoom in 

621
00:38:49,133 --> 00:38:55,433
to look at the landscape more

622
00:38:55,433 --> 00:39:00,933
closely. So you see, same variable.

623
00:39:00,933 --> 00:39:02,333


624
00:39:02,333 --> 00:39:04,799
It shows vegetation percent cover,  

625
00:39:04,800 --> 00:39:07,400
less vegetation, no

626
00:39:07,400 --> 00:39:08,433


627
00:39:08,433 --> 00:39:13,099
vegetation. You can see the

628
00:39:13,100 --> 00:39:15,000
bright. As we know in the

629
00:39:15,000 --> 00:39:15,100


630
00:39:15,100 --> 00:39:16,133
false color composite, the red

631
00:39:16,133 --> 00:39:19,866
represents vegetation.

632
00:39:19,866 --> 00:39:29,066
We can go into any area. And another thing 

633
00:39:29,066 --> 00:39:32,932
that we, I wanted to point out was 

634
00:39:32,933 --> 00:39:35,033
if we go for View Pixel

635
00:39:35,033 --> 00:39:45,199
Information, so these areas, you

636
00:39:45,200 --> 00:39:49,533
see high green. We have to

637
00:39:49,533 --> 00:39:50,733
remember we had stretched the

638
00:39:50,733 --> 00:39:54,233
image from 0 to 255. So when

639
00:39:54,233 --> 00:39:56,233
we are taking percent cover, 

640
00:39:56,233 --> 00:39:59,199
we need to divide it by 2.55 

641
00:39:59,200 --> 00:40:02,033
to get the percent from 0 to 100 percent. OK?

642
00:40:02,033 --> 00:40:03,366


643
00:40:03,366 --> 00:40:05,366


644
00:40:05,366 --> 00:40:14,532


645
00:40:14,533 --> 00:40:19,499
We will now create a color ramp for the 2019, '18 difference

646
00:40:19,500 --> 00:40:22,866
vegetation map with six

647
00:40:22,866 --> 00:40:25,066
colors. We'll use the break

648
00:40:25,066 --> 00:40:28,132
points given in the table of the

649
00:40:28,133 --> 00:40:31,233
handbook on page 15. We go

650
00:40:31,233 --> 00:40:31,933


651
00:40:31,933 --> 00:40:33,133
to the Color Manipulation. 

652
00:40:33,133 --> 00:40:38,333
We set the histogram to 100

653
00:40:38,333 --> 00:40:41,199
percent. As we said, we'll

654
00:40:41,200 --> 00:40:46,933
use six colors. We'll first add

655
00:40:46,933 --> 00:40:51,466
a new slider.

656
00:40:51,466 --> 00:40:58,199
[no speaking while sliders are being set up]

657
00:40:58,200 --> 00:41:02,633
OK... Now, we go to the table, 

658
00:41:02,633 --> 00:41:06,866
and we will set our positions and colors.

659
00:41:06,866 --> 00:41:17,166
First color. Off, Sorry!  

660
00:41:17,166 --> 00:41:18,099


661
00:41:18,100 --> 00:41:24,166
So, we will add a color. First color is blue. 

662
00:41:24,166 --> 00:41:25,099


663
00:41:25,100 --> 00:41:28,266
Go RGB, and we'll type the code. 

664
00:41:28,266 --> 00:41:29,266


665
00:41:29,266 --> 00:41:30,432


666
00:41:30,433 --> 00:41:31,099


667
00:41:31,100 --> 00:41:31,933


668
00:41:31,933 --> 00:41:33,333
One, two, three, four. f f

669
00:41:33,333 --> 00:41:33,666


670
00:41:33,666 --> 00:41:35,966


671
00:41:35,966 --> 00:42:36,032
And OK. Next color. [no speaking while colors are being selected] 

672
00:42:36,033 --> 00:42:46,766
Sure does look bad. We havn't sent the relative positions as yet. 

673
00:42:46,766 --> 00:43:21,232
I have zero zero. [no speaking while histogram colors are manipulated] 

674
00:43:21,233 --> 00:43:27,833
Now, we'll set the breakpoints. We start from the extreme level,

675
00:43:27,833 --> 00:43:38,499
the upper limit, which is 189.81

676
00:43:38,500 --> 00:43:41,300
Enter. 

677
00:43:41,300 --> 00:43:47,533
OK where is my red? [no speaking]

678
00:43:47,533 --> 00:44:58,066
[no speaking during color selections on the histogram]  

679
00:44:58,066 --> 00:45:04,032
OK, so we can go and right-click, and we can export the color

680
00:45:04,033 --> 00:45:08,433
legend as image. You can save it.

681
00:45:08,433 --> 00:45:11,033
I have it already, so I'll

682
00:45:11,033 --> 00:45:14,633
cancel it. Then, you can also

683
00:45:14,633 --> 00:45:21,866
save the color palette to a text file. 

684
00:45:21,866 --> 00:45:26,332
So, the difference veg map shows

685
00:45:26,333 --> 00:45:28,433
colors ranging from reds to

686
00:45:28,433 --> 00:45:31,399
yellows to greens to cyan 

687
00:45:31,400 --> 00:45:35,833
and blues. There is a mixture of

688
00:45:35,833 --> 00:45:37,733
colors. How do we represent it

689
00:45:37,733 --> 00:45:40,233
as far as the live vegetation

690
00:45:40,233 --> 00:45:40,533


691
00:45:40,533 --> 00:45:42,633
change from 2018 to 2019?

692
00:45:42,633 --> 00:45:46,233
The reds, for sure,

693
00:45:46,233 --> 00:45:49,899
have shown an increase in live

694
00:45:49,900 --> 00:45:51,733
vegetation from 2018 to 2019.

695
00:45:51,733 --> 00:45:54,533
The blue show a

696
00:45:54,533 --> 00:45:56,733
decrease from 2018 to 2019.

697
00:45:56,733 --> 00:45:59,766
That is live vegetation was

698
00:45:59,766 --> 00:46:02,032
higher in 2018 as compared

699
00:46:02,033 --> 00:46:04,433
to 2019. The science

700
00:46:04,433 --> 00:46:08,233
also show that the live

701
00:46:08,233 --> 00:46:11,633
vegetation in 2018 was higher

702
00:46:11,633 --> 00:46:15,599
than 2019, but not

703
00:46:15,600 --> 00:46:18,933
as much as the blues. On the

704
00:46:18,933 --> 00:46:22,433
other side, the yellows are

705
00:46:22,433 --> 00:46:22,533


706
00:46:22,533 --> 00:46:24,733
showing that the live vegetation

707
00:46:24,733 --> 00:46:25,733


708
00:46:25,733 --> 00:46:29,033
in 2019 was higher than

709
00:46:29,033 --> 00:46:34,433
2018. Then we have a big

710
00:46:34,433 --> 00:46:38,033
middle zone, which are the

711
00:46:38,033 --> 00:46:38,133


712
00:46:38,133 --> 00:46:40,733
greens. Here, there is actually

713
00:46:40,733 --> 00:46:43,733
a small increase as well as a

714
00:46:43,733 --> 00:46:45,433
decrease shown. We have to

715
00:46:45,433 --> 00:46:47,033


716
00:46:47,033 --> 00:46:51,333
really zoom into the areas to

717
00:46:51,333 --> 00:46:53,499
look at the shades of green. If

718
00:46:53,500 --> 00:46:55,633
there was an increase from 2018

719
00:46:55,633 --> 00:46:57,933
to 2019, all are decreased.

720
00:46:57,933 --> 00:46:59,733


721
00:46:59,733 --> 00:47:03,633
Shades of yellow green will show

722
00:47:03,633 --> 00:47:08,133
live vegetation high in 2019.

723
00:47:08,133 --> 00:47:09,133


724
00:47:09,133 --> 00:47:13,533
Shades of cyan and green

725
00:47:13,533 --> 00:47:14,233


726
00:47:14,233 --> 00:47:16,433
means lower in 2019 than in

727
00:47:16,433 --> 00:47:18,633
2018. If we

728
00:47:18,633 --> 00:47:23,133
zoom into an area,

729
00:47:23,133 --> 00:47:23,733


730
00:47:23,733 --> 00:47:35,699
we see the yellowish green areas.

731
00:47:35,700 --> 00:47:39,033
They show a very small increase

732
00:47:39,033 --> 00:47:42,333
from 2018 to '19. Areas

733
00:47:42,333 --> 00:47:45,533
of bluish green, which are

734
00:47:45,533 --> 00:47:49,833
around here, in this area and

735
00:47:49,833 --> 00:47:54,433
these areas, show a very small

736
00:47:54,433 --> 00:47:57,533
decrease from 2018 to '19. We

737
00:47:57,533 --> 00:48:02,933
should keep in mind also that

738
00:48:02,933 --> 00:48:05,766
middle zone has very low values.

739
00:48:05,766 --> 00:48:08,066
The increases and decreases are

740
00:48:08,066 --> 00:48:09,099
very small numbers. 

741
00:48:09,100 --> 00:48:21,933


742
00:48:21,933 --> 00:48:27,633
In this exercise we will process Sentinel-1 SAR image data. 

743
00:48:27,633 --> 00:48:30,933
We have already downloaded the data 

744
00:48:30,933 --> 00:48:35,866
so we will go to... Now we will import

745
00:48:35,866 --> 00:48:37,866
this downloaded data. Go to

746
00:48:37,866 --> 00:48:40,332
Import, SAR Sensors, Sentinel-1.

747
00:48:40,333 --> 00:48:41,233


748
00:48:41,233 --> 00:48:46,299
Go to the right folder. We have

749
00:48:46,300 --> 00:48:52,166
the SAR data in this folder 

750
00:48:52,166 --> 00:49:02,932
[no speaking] and import product. 

751
00:49:02,933 --> 00:49:04,333


752
00:49:04,333 --> 00:49:08,999
So we are there. Import Product. 

753
00:49:09,000 --> 00:49:13,033
As I had shown earlier, we can also

754
00:49:13,033 --> 00:49:14,999
directly drag and drop the

755
00:49:15,000 --> 00:49:16,933
products. We'll do the same. We

756
00:49:16,933 --> 00:49:24,233
go to this folder and drag

757
00:49:24,233 --> 00:49:25,166


758
00:49:25,166 --> 00:49:32,166
this Manifest file. 

759
00:49:32,166 --> 00:49:35,932
We have imported the four SAR images

760
00:49:35,933 --> 00:49:37,933
that cover the core and NRT   

761
00:49:37,933 --> 00:49:42,933
Conservancies. If we go and

762
00:49:42,933 --> 00:49:46,533
open the Product, see bands, so we

763
00:49:46,533 --> 00:49:46,633


764
00:49:46,633 --> 00:49:50,033
have amplitude as VH and VV.

765
00:49:50,033 --> 00:49:50,333


766
00:49:50,333 --> 00:49:52,599
What does that mean? 

767
00:49:52,600 --> 00:49:55,000
SAR satellites have an active sensor

768
00:49:55,000 --> 00:49:55,100


769
00:49:55,100 --> 00:49:58,233
on both. It sends a signal and

770
00:49:58,233 --> 00:50:00,166
then receives back the signal.

771
00:50:00,166 --> 00:50:04,032
Here, the VH, the signal is

772
00:50:04,033 --> 00:50:04,933
transmitted vertically and

773
00:50:04,933 --> 00:50:08,333
receives the signal back

774
00:50:08,333 --> 00:50:09,399
horizontally. The sensor

775
00:50:09,400 --> 00:50:12,033
receives the signal back

776
00:50:12,033 --> 00:50:14,533
horizontally. In VV, the signal

777
00:50:14,533 --> 00:50:17,433
is transmitted vertically and

778
00:50:17,433 --> 00:50:19,433
received vertically. SAR is

779
00:50:19,433 --> 00:50:20,133


780
00:50:20,133 --> 00:50:23,233
an active sensor, so it

781
00:50:23,233 --> 00:50:26,933
does not need any light 

782
00:50:26,933 --> 00:50:29,833
to record the image. Therefore, the

783
00:50:29,833 --> 00:50:31,933
data collections are not impeded 

784
00:50:31,933 --> 00:50:34,333
by any cloud cover. Also, the

785
00:50:34,333 --> 00:50:36,833
data can be collected day or night. 

786
00:50:36,833 --> 00:50:39,966
Here, we are going to

787
00:50:39,966 --> 00:50:43,599
mosaic these four images, for

788
00:50:43,600 --> 00:50:46,200
mosaicing. Before mosaicing, we

789
00:50:46,200 --> 00:50:46,533


790
00:50:46,533 --> 00:50:48,533
have to calibrate each product.

791
00:50:48,533 --> 00:50:51,833
We go to Radar,

792
00:50:51,833 --> 00:50:58,366
Radiometric, and Calibrate. So we

793
00:50:58,366 --> 00:51:03,832
will shorten our name. That is

794
00:51:03,833 --> 00:51:10,233
12, 1st of December. 

795
00:51:10,233 --> 00:51:17,033
We will take that away and then go

796
00:51:17,033 --> 00:51:17,466


797
00:51:17,466 --> 00:51:39,499
to the right folder... [no speaking during folder selection]

798
00:51:39,500 --> 00:51:42,733
and Select. The processing

799
00:51:42,733 --> 00:51:47,333
parameters, we have VH and VV.

800
00:51:47,333 --> 00:51:47,633


801
00:51:47,633 --> 00:51:50,133
The output will be sigma naught band, 

802
00:51:50,133 --> 00:51:50,733


803
00:51:50,733 --> 00:51:54,033
and we will hit Run. So our calibrated

804
00:51:54,033 --> 00:51:54,933


805
00:51:54,933 --> 00:51:57,966
file is done. It's opened in SNAP, 

806
00:51:57,966 --> 00:52:00,399
and we will go and display it.  

807
00:52:00,400 --> 00:52:01,333


808
00:52:01,333 --> 00:52:05,466
The bands, our VH and VV, and I have it. 

809
00:52:05,466 --> 00:52:08,532
It takes a little bit time to

810
00:52:08,533 --> 00:52:11,933
display the band, so I have it

811
00:52:11,933 --> 00:52:16,933
displayed. So this is the calibrate. 

812
00:52:16,933 --> 00:52:19,933
The next step is we will

813
00:52:19,933 --> 00:52:20,533


814
00:52:20,533 --> 00:52:25,033
go and do terrain correction. So we

815
00:52:25,033 --> 00:52:28,766
go to Radar, Geometric, and 

816
00:52:28,766 --> 00:52:31,232
Terrain Correction, Range

817
00:52:31,233 --> 00:52:31,933
Doppler terraine 

818
00:52:31,933 --> 00:52:34,299
Correction. 

819
00:52:34,300 --> 00:52:41,800
It's our file with an abbreviation

820
00:52:41,800 --> 00:52:43,933
terrain correction. Next, we

821
00:52:43,933 --> 00:52:46,933
select our folder. Go to the

822
00:52:46,933 --> 00:52:51,233
same folder. Locate the processing 

823
00:52:51,233 --> 00:52:51,566


824
00:52:51,566 --> 00:52:55,899
parameters, we have our source

825
00:52:55,900 --> 00:52:59,400
bands, the VH, VV. Then we will

826
00:52:59,400 --> 00:52:59,500


827
00:52:59,500 --> 00:53:03,033
select our map projection. We go

828
00:53:03,033 --> 00:53:08,733
to Predefined CRS. We select WGS

829
00:53:08,733 --> 00:53:16,866
Auto UTM. OK, OK, Hit Run.

830
00:53:16,866 --> 00:53:18,832
We have 

831
00:53:18,833 --> 00:53:20,899
our terrain corrected

832
00:53:20,900 --> 00:53:26,533
image. I have it displayed.

833
00:53:26,533 --> 00:53:31,599
Go and look at it. That

834
00:53:31,600 --> 00:53:33,833
is our terrain corrected image. 

835
00:53:33,833 --> 00:53:36,433
If we go to the one before it, just

836
00:53:36,433 --> 00:53:37,333
the calibrated image, that's

837
00:53:37,333 --> 00:53:41,199
what it looked like. Now it is 

838
00:53:41,200 --> 00:53:43,500
terraine corrected. 

839
00:53:43,500 --> 00:53:44,100


840
00:53:44,100 --> 00:53:48,766
Next, we are going to go ... (georeference entered incorrected), 

841
00:53:48,766 --> 00:53:52,232
to go and do speckle filtering.

842
00:53:52,233 --> 00:53:54,233
Speckle filtering helps remove

843
00:53:54,233 --> 00:53:57,833
the noise from the image.

844
00:53:57,833 --> 00:54:00,133
I'm not going to go into the

845
00:54:00,133 --> 00:54:01,733
details of it. It's not actually

846
00:54:01,733 --> 00:54:03,733
noise. That is also data, but

847
00:54:03,733 --> 00:54:05,333
here we do not require that.

848
00:54:05,333 --> 00:54:07,133
We go to Radar, Speckle

849
00:54:07,133 --> 00:54:08,799
Filtering, and Single Product. 

850
00:54:08,800 --> 00:54:15,800
Speckle Filter. And you see that it, then we have the 

851
00:54:15,800 --> 00:54:16,166


852
00:54:16,166 --> 00:54:19,332
Speckle Filter and then we will...

853
00:54:19,333 --> 00:54:22,933
our folder there. We go to

854
00:54:22,933 --> 00:54:25,099
Processing Parameters. We have

855
00:54:25,100 --> 00:54:27,833
the Source Bands and we are

856
00:54:27,833 --> 00:54:30,499
going to select the Lee filter,

857
00:54:30,500 --> 00:54:37,333
3x3, and hit Run. This is

858
00:54:37,333 --> 00:54:41,133
the result of our speckle filter.

859
00:54:41,133 --> 00:54:41,333


860
00:54:41,333 --> 00:54:45,033
This is before applying the

861
00:54:45,033 --> 00:54:46,833
speckle filter. Before speckle filter,  

862
00:54:46,833 --> 00:54:49,133
after speckle filter.  

863
00:54:49,133 --> 00:54:50,933
We really

864
00:54:50,933 --> 00:54:53,433
have to zoom into an area to know.

865
00:54:53,433 --> 00:55:01,299
So let's look at it again

866
00:55:01,300 --> 00:55:02,233
if...OK. Before speckle 

867
00:55:02,233 --> 00:55:08,333
filter. Next step is to 

868
00:55:08,333 --> 00:55:09,033


869
00:55:09,033 --> 00:55:10,999
create a mosaic. Before we do

870
00:55:11,000 --> 00:55:13,033
that, we have to apply the

871
00:55:13,033 --> 00:55:13,933
calibration to terraine correction

872
00:55:13,933 --> 00:55:16,733
and speckle filter to all

873
00:55:16,733 --> 00:55:19,633
the other three SAR images. Once

874
00:55:19,633 --> 00:55:24,933
all these images are processed

875
00:55:24,933 --> 00:55:26,899
with the speckle filter, we will

876
00:55:26,900 --> 00:55:29,800
use this for creating the mosaic.

877
00:55:29,800 --> 00:55:31,333
OK, 

878
00:55:31,333 --> 00:55:35,433
I have run the speckle filter on

879
00:55:35,433 --> 00:55:37,933
these other three images. We go

880
00:55:37,933 --> 00:55:41,499
to Radar, Geometric, and SAR

881
00:55:41,500 --> 00:55:50,000
Mosaic. Either you go and

882
00:55:50,000 --> 00:55:53,333


883
00:55:53,333 --> 00:55:55,733
add one image at a time that or

884
00:55:55,733 --> 00:55:59,033
you will add Add Opened. We'll

885
00:55:59,033 --> 00:56:01,633
just go and remove the files we

886
00:56:01,633 --> 00:56:03,633
don't need. We just need the

887
00:56:03,633 --> 00:56:05,833
files that have been processed

888
00:56:05,833 --> 00:56:08,099
with speckle filter for the

889
00:56:08,100 --> 00:56:14,933
mosaic. [no speaking] I just open this up so

890
00:56:14,933 --> 00:56:16,433
that we know what we are

891
00:56:16,433 --> 00:56:21,733
removing. We have the four

892
00:56:21,733 --> 00:56:24,033
images. All processed through speckle filter

893
00:56:24,033 --> 00:56:24,533


894
00:56:24,533 --> 00:56:27,499
Next is the SAR

895
00:56:27,500 --> 00:56:31,333
mosaic. It takes the VV and the

896
00:56:31,333 --> 00:56:33,933
VH bands, and we will not

897
00:56:33,933 --> 00:56:34,699


898
00:56:34,700 --> 00:56:38,000
normalize the image. Then, we

899
00:56:38,000 --> 00:56:42,000
will write it. We give it a name.

900
00:56:42,000 --> 00:56:42,233


901
00:56:42,233 --> 00:56:48,533
We go to the right folder, and

902
00:56:48,533 --> 00:56:54,633
OK and hit Run. Displayed is the mosaic. 

903
00:56:54,633 --> 00:56:55,833


904
00:56:55,833 --> 00:56:58,433
Once the mosaic is created, it

905
00:56:58,433 --> 00:57:01,733
takes about 20 minutes for it to

906
00:57:01,733 --> 00:57:04,033
display. We have the two to open

907
00:57:04,033 --> 00:57:05,133


908
00:57:05,133 --> 00:57:08,433
up the mosaic. You see, we have the two

909
00:57:08,433 --> 00:57:09,933


910
00:57:09,933 --> 00:57:12,599
bands, the VH and the VV.

911
00:57:12,600 --> 00:57:16,933
Next, we will create a subset.

912
00:57:16,933 --> 00:57:20,899
Before we create the subset, we

913
00:57:20,900 --> 00:57:25,633
will use the nine tile mosaic of

914
00:57:25,633 --> 00:57:28,399
optical data, and that of SAR

915
00:57:28,400 --> 00:57:31,333
2018, as a reference image, and

916
00:57:31,333 --> 00:57:34,433
we'll use the coordinates of

917
00:57:34,433 --> 00:57:36,533
that image of the SAR 2018 image.

918
00:57:36,533 --> 00:57:36,933


919
00:57:36,933 --> 00:57:41,633
I have already displayed the

920
00:57:41,633 --> 00:57:52,099
mosaic of SAR 2018. 

921
00:57:52,100 --> 00:57:55,500
This is my image. We need to use

922
00:57:55,500 --> 00:57:58,733
the geocoordinates of this image

923
00:57:58,733 --> 00:58:02,733
to subset our 2019 SAR image.

924
00:58:02,733 --> 00:58:05,566


925
00:58:05,566 --> 00:58:08,832
It is not straightforward way. 

926
00:58:08,833 --> 00:58:11,233
I have not yet seen in SNAP how

927
00:58:11,233 --> 00:58:14,933
to just bring in an image and

928
00:58:14,933 --> 00:58:17,566
use the coordinates of that

929
00:58:17,566 --> 00:58:20,532
image. We have to go first to

930
00:58:20,533 --> 00:58:22,333
get the coordinates of this. We will 

931
00:58:22,333 --> 00:58:24,933
go to Analysis and

932
00:58:24,933 --> 00:58:27,733
Geocoding. We will know the

933
00:58:27,733 --> 00:58:31,233


934
00:58:31,233 --> 00:58:34,833
upper-right latitude, upper-

935
00:58:34,833 --> 00:58:35,233


936
00:58:35,233 --> 00:58:40,133
right longitude, and lower-right

937
00:58:40,133 --> 00:58:42,133
latitude and lower-right

938
00:58:42,133 --> 00:58:42,833


939
00:58:42,833 --> 00:58:45,733
longitude. These are given in

940
00:58:45,733 --> 00:58:47,833


941
00:58:47,833 --> 00:58:52,233
degrees, minutes, seconds. 

942
00:58:52,233 --> 00:58:54,833
We have to convert these to decimal

943
00:58:54,833 --> 00:58:56,999
degrees to use in the subset.

944
00:58:57,000 --> 00:59:03,200
We'll use Excel and convert this.

945
00:59:03,200 --> 00:59:06,900
Next, we go to our subset.

946
00:59:06,900 --> 00:59:13,600
We go to Raster and Subset. 

947
00:59:13,600 --> 00:59:16,266


948
00:59:16,266 --> 00:59:25,032
It brings up the thumbnail image.

949
00:59:25,033 --> 00:59:27,633
We go to Geo Coordinates, bring

950
00:59:27,633 --> 00:59:30,799
up our Excel, and Copy-Paste.

951
00:59:30,800 --> 00:59:55,100
Backspace, then last one.

952
00:59:55,100 --> 01:00:02,566


953
01:00:02,566 --> 01:00:11,499
[no speaking] We put a negative, because it is 

954
01:00:11,500 --> 01:00:14,600
a south latitude here. Then we

955
01:00:14,600 --> 01:00:15,433


956
01:00:15,433 --> 01:00:18,633
just hit OK. It takes about

957
01:00:18,633 --> 01:00:18,833


958
01:00:18,833 --> 01:00:24,533
20 minutes to create the

959
01:00:24,533 --> 01:00:27,533
subset. Here we have displayed

960
01:00:27,533 --> 01:00:30,133
the subset of SAR image 2019.

961
01:00:30,133 --> 01:00:30,733


962
01:00:30,733 --> 01:00:35,233
Next, we will create a

963
01:00:35,233 --> 01:00:37,533
ratio band. That is VH over VV.

964
01:00:37,533 --> 01:00:37,933


965
01:00:37,933 --> 01:00:42,933
Simply we go to... and as soon as the

966
01:00:42,933 --> 01:00:46,066
product is created, you go right-click 

967
01:00:46,066 --> 01:00:47,832
and save the product as

968
01:00:47,833 --> 01:00:49,633
I have said before. We right-

969
01:00:49,633 --> 01:00:50,133


970
01:00:50,133 --> 01:00:56,899
click Band Math, give it a

971
01:00:56,900 --> 01:01:05,800
name, VH_VV. Then Edit

972
01:01:05,800 --> 01:01:07,033


973
01:01:07,033 --> 01:01:09,533
Expression. We want to

974
01:01:09,533 --> 01:01:15,499
create a ratio. We go here, VH

975
01:01:15,500 --> 01:01:22,100
over VV. I have already created

976
01:01:22,100 --> 01:01:22,633


977
01:01:22,633 --> 01:01:26,599
the band. You see that? Just hit

978
01:01:26,600 --> 01:01:31,533
OK. You see here that the ratio

979
01:01:31,533 --> 01:01:33,233
band is created, but I would

980
01:01:33,233 --> 01:01:34,633
like to see the ratio band is

981
01:01:34,633 --> 01:01:36,633
created as a virtual band. You

982
01:01:36,633 --> 01:01:38,733
will go right-click and convert

983
01:01:38,733 --> 01:01:43,133
band. It's grayed out because

984
01:01:43,133 --> 01:01:43,533


985
01:01:43,533 --> 01:01:44,833
it's already converted. Convert

986
01:01:44,833 --> 01:01:47,833
band, and then hit Save Product.

987
01:01:47,833 --> 01:01:49,433


988
01:01:49,433 --> 01:01:53,933
Once that is done, then we

989
01:01:53,933 --> 01:01:56,533
will again use Band Math and use

990
01:01:56,533 --> 01:02:00,133
the expression equation given in the

991
01:02:00,133 --> 01:02:02,499
handbook to calculate the final product.

992
01:02:02,500 --> 01:02:02,533


993
01:02:02,533 --> 01:02:02,833


994
01:02:02,833 --> 01:02:03,399