 Hello, this is Hans van der Klaas Senior Lecturer at IHE Delft Institute for Water Education. In this video I'm going to test the new MSI installer for QGIS, and I'm also going to test the new point cloud functionality. Most of my videos are done with the LTR versions, which I can also recommend you to use for operational use and in the courses, but the newer versions are always great to test the new functionality. Normally you will download the installers from the download sections of the site you can choose between the OSGO 4W and the standalone installer, but here we will use another installer. In this video we are going to test the experimental MSI installer, which will be the future way of installing QGIS on Windows. The link has been provided through the user mailing list of QGIS, and I also posted in the description of this video. When we run the installer, we get this pop-up wizard, which looks really great and simple. We click Next, and here it provides us the user license, and if you accept it, you can click Next. You can keep the default locations and start installing. They will take some time. I have done a fast forward here. When the wizard is done, we can click Finish to exit the setup wizard, and we can find QGIS in the Windows Start menu, and we will use here the QGIS desktop 3.18. As you see, it starts up perfectly well without errors. Let's first download the data that we are going to use, and I am going to demonstrate the point cloud functionality using the dutch elevation model, AHM, which we can download from the paid-off website. I will put the link in the description of this video, and we download the point cloud LAZ file and save it to our disk. It is a big file, so it will take a bit to download. In the browser panel, I look for the folder where I downloaded the point cloud, and I do not see it there. That is the first bug that I encountered, and it has to do with the file extension. I found out that if your file extension is in capitals, like in this case, you need to rename it to the lower case to be detected as a point cloud by the browser panel. Here we see that it is recognized. Now we can drag it to the map canvas, and this is a great feature that it shows us the extent of the point cloud and not all the millions of points immediately for this large file. While it is processing, we can still do other things. In fact, I want to reduce the size, and I am going to use an aerial photograph for reference that I downloaded from PDock. It is a great plugin that gives access to many free data sources for the Netherlands, and I download the aerial photograph. Go to the layers panel, and there I see that the projection of the point cloud is not detected. Maybe the PDock does not recognize the dutch projection. I'm going to set the on-the-fly reprojection to the dutch one, and I click on the question mark to also change the projection of the point cloud, and let's zoom to the layer, and we need to, of course, drag the point cloud extent to the top to see where it is, and there we are in the Netherlands, and as we see it covers quite a large area around Rotterdam, and I am going to clip it to only the part in the center. So around this area I am going to clip the point cloud, and then later I am going to sample the RGB values also from this ortho-photo, because the point cloud that we downloaded doesn't have the RGB attribute. In order to clip our point cloud, we need to define a polygon with the extent of the area. I use the create layer from extent tool from the processing toolbox to clip it to the extent of the map canvas. I define the output file name, it's a shape file that we need, and you see here a folder has been created while it is processing, it's still processing our point cloud file that we downloaded, so I'm going to remove it because we really want to work with the smaller one, and here we see our polygon, zoom a bit out so you see the area that it covers, and then I need the last tools plugin to further process the point cloud, because the native processing tools for point clouds are not yet developed, and we need last tools to do things like clipping or sampling RGB values that we do later. We need to set the path of the last tools where we have downloaded and installed it, and that's explained in another video. It's important to choose the correct path so it can find the tools, so we see that it's still processing our original file, so I click on it and cancel the processing, otherwise QGIS will be affected by that and it will consume a lot of memory. So under last tools I go to processing points and I choose last clip, and I choose the original file, and I choose the polygon that is used to clip it to the correct extent that we want, you can use this tool to clip and to classify, we use clip so it ignores the classify option there, I give it an output file name, let's call it clipped.laz, let's run the tool, it takes a lot of time, here I cut it a bit and it's done, and if we refresh our browser panel we see the clipped last file and it shows us the extent and it starts processing immediately this file and you see it goes much faster because it's much smaller. Let's also set the projection to the dodge system, here unfortunately QGIS is crashing which always can happen in these test versions, so I'll restart and continue from here, so I've restarted QGIS and here I find the files that we created and I'm dragging the clipped last file to the map canvas and it detects automatically now the attribute of the classification, let's also set the projection to the dodge one, it doesn't remember those projections, always make sure that you have your project and the layer in the correct projection, now I lost where it was but I also load now my aerial photograph, there it is, drag it to the top, I still don't see it, so let's see if that's a problem with refreshing, everything seems okay, so it looks like a little bug there, let's just add it again, there it is and now it's in the correct position, I set the projection, just to be sure and let's have a look at the layer styling panel and there we see that it uses the classification attribute and it has a few classes here that were in the attributes of the original point cloud and if you go to the properties of the layer, you see here the attributes of the point cloud but what is not included here is the RGB color and what we're going to do is first look at this in 3D with a single color to just see if it has the Z values there and we can make a bit sense out of that, so I open a new 3D view and it knows automatically that this is a point cloud so we don't need to choose it, it just takes it automatically and here we see indeed that these are all our points, you can play with the size of the points and I can play with the colors but we don't have the RGB there and if you see that there's a renderer for the 2D and for the 3D, I've switched off the 2D renderer to have only the extent so the 3D renderer comes out better, so I'm going to export now the map canvas view with the ortho photo to a geotiff because that's what we need to sample the values from in our point cloud and there's a nice tool from last tools to do that, it's called last color and I choose the last file that is our clipped one, I'll choose the input ortho photo and I choose the output file name and let's call it ahnrotogamcenterRGB.laz and let's run this, it also take a lot of time and it will sample for each of those points the RGB color from the ortho photo. It's done, you see here a note that because of not having the license it will not process all the points and have some other tricks but it's good enough for our purpose here and I'm going to add our new layer to the map canvas, it shows the extent, I indicate the projection, I can remove the clipped one and it's processing, converting it to another format that it uses so creating that extra folder with the data. Now it's done and we see here our RGB colors automatically on the screen so after the processing is done it will take that and we see the difference and we can remove there the aerial photograph from the background and let's look at it in the 3D view and here in the layer styling panel we see that it uses RGB for the 2D but for the 3D we need to choose also that it needs to use the RGB attribute and then here in the 3D view points are visible with the nice colors from the ortho photo sampled and we can here recognize the buildings of the city, the marked hall, the cube buildings and other strange shapes of the city. So in this video I've explained how to use the QDS 318 MSI installer which will be a future way of installing QDS and I showed how to import point clouds in QDS and do some treatment of the data sample RGB values using the last tools plugin and then visualize it in the 3D view.