 Hello, this is Hans van der Kwas senior lecturer at IHG Delft Institute for Water Education. In this video, I will demonstrate how to visualize a point cloud using RGB values sampled from an orthophoto. In this example, we will use a recent orthophoto from the Netherlands, from Rotterdam, wherein in another video we have downloaded the AHN tile. So to access open data for the Netherlands, we install the PDockServices plugin. And there we can click this button and see the data and here the first one is the aerial photograph 25 centimeters RGB, that's what we need, and there it is. Now we need to zoom in to Rotterdam, we can use this geolocation, and there we are approximately in Rotterdam, and we zoom in to the area that we need for the processing matching the tile that we have downloaded from AHN, which I demonstrated in another video. Because this is a web surface and we can't use it, we need to convert it to a geotiff. So I export it by saving it as an image and I use the map canvas extent and we need to increase the resolution because later the RGB values will be sampled from the pixels in the geotiff. So let me put it in this case on 600 dpi and give it an output name and this will be a georeferenced geotiff of what I see on the screen. If you don't have access to a web service, you can also just load a tile of an orthophotograph that you have in TIFF format, or you generate it from the Google satellite images, which come with a quick map services plugin. The next step is to use the last tools, and you find under file processing tools, you find last color, that's the tool that we're going to use, and as our input last file, we use the ahn tile that we've downloaded previously, you can see that in a previous video, open data from the Netherlands, LiDAR data, and here we specify the orthophoto and the output file name, and it will save it in a new last or LAZ file. It will take a while to run here, I have cut it out of the video, now we need to convert it to the pottery format that can be read by the QGIS23JS plugin, so I open an anaconda prompt, I go to the correct environment that we also created in a previous video, and I give this command, and I can only use the tab completion if I use the slashes like this, and I specify the output, this is to generate the pottery compatible format. There's an error because those slashes need to go the other way, and because I wanted to use tab completion, I used the normal slashes, but then you need to replace it with the forward slashes, and then you see it works, that will also take a lot of time, I have cut it out of the video. When the conversion is done, we go back to QGIS, and we will use now the QGIS23JS plugin, which I already installed, here you can find it, and we click that button to access the plugin screen, and we can then add the point cloud, we browse to our generated file, and then we click add, and by default it will read the RGB values, so we don't have to do anything else. We see that the area that we sampled from is a bit smaller than the whole tile, so therefore the outside will get black dots, which have no data, and here we can see that the texture is taken from the orthophotograph and added to the points, so basically we see now our points from the point cloud in colors from the orthophoto. Now there is also some sparse data where we don't have so many points, and we can do this trick to replace it with the color of water, because normally it's water, and that will give a more homogeneous view without those gaps. So I hope you've enjoyed this video, you've learned how to add RGB data to your point cloud data, and if you like these videos, please subscribe to my YouTube channel to receive also updates, and if you want more free materials have a look at IHE Delft OpenCourseWare at JISOpenCourseWare.org