 Hello, welcome back on my YouTube channel. In this video I'm going to show how to prepare a project for precision agriculture with high-resolution spatial data that is freely available for the Netherlands. We'll use the PDock Services plugin to load orthophotos in RGB and infrared, to load soil maps, elevation data and parcels with crop information. Let's first find our study area. I'll drag the OpenStreetMap layer from the browser panel to the map canvas and I've received a coordinate of the study area in latitude-longitude coordinates. I can simply paste that into the locator bar at the bottom of the QJS window and it will then zoom into that point. I'll zoom a little bit out to have more context here on the OpenStreetMap. I'm also changing here the projection of the project to the one of the Netherlands, which is Amazon's RdNew or EPSG 28992. To be able to find back this extent later, I'm going to create a spatial bookmark. Here you can give a name for the bookmark and you can add the bookmark to a self-defined group. I'll create a new group Precision Agriculture. Then I can use the map canvas extent as the extent to be stored and I can choose a user or a project bookmark. Project bookmarks are stored in projects. User bookmarks you can use across projects. So I store it as a user bookmark and click Save. You can find the spatial bookmarks in your browser panel and I'm just going to zoom in and click on Larger Study Area and then see that it's back to the extent that I've defined. We can load three layers for this area and for the rest of the Netherlands from the PDock Services plugin. Go to the Plugins Manager and search for PDOK. Install the PDOK Services plugin. With the plugin you can get access to WMS, WMTS, WFS and WCS layers directly in QJS. After installation you'll find a new toolbar. Click this icon to open the PDOK Services plugin dialog where you find in Dutch Lachna, which means layer name, type, which shows the OGC service and service, more explanation about the service. Let's start with loading an actual orthophoto at 8 centimeter resolution in RGB. If you click a layer you can find links to the metadata. There are three buttons there with standard. You just open the layer with boven, it means above your active layer and under at the bottom of your layers panel. So here I chose boven so it ends up above. Here you can see now the RGB aerial photograph and when I zoom in you can see all the details that are visible with this resolution and that's quite detailed. So now let's load also a near infrared orthophoto where with red colors you can see the vegetation. So we can also see which parcels have crops and which don't have crops. Here you see the result and when I zoom in you see that this one has 25 centimeter resolution which is already very fine for us and we can see in bright red which parcels have vegetation, have crops. Let's export the layer to a geotiff which is more useful if we are with our laptop in the field without an internet connection. I'm going to save it as a rendered image. I uncheck create VRT and I call it infrared. I use our bookmark for the extent and for the resolution I use 5 meters. I use a courseware resolution here than the original layer just to save disk space but it's up to you to choose a higher resolution if you need that for your purpose. But for detection of vegetated and non-fegitated parcels this is already good enough. There we see the result and if I zoom in you see at some point it gets a bit pixelated and there you see the difference with the more crisp online layer which has a higher resolution. You can also in the layer styling panel see that we have now three bands so we can change the order of bands and use this for further analysis. You can also export anything that we have in the map canvas to a geo-referenced image and therefore we use the export tool from the project menu and we can choose the extent and it appends the geo-reference information to the file. Let's call it infrared map canvas and save it to a geo-tiff. Here we see that it takes the full extent and if you want a higher resolution you need to zoom in because you will get exactly a picture of the map canvas. A better way of exporting online layers, raster layers is using XYZ layers from the processing toolbox and create MB tiles. The MB tiles will create tiles at different zoom levels in one file so you will have similar experiences with the online layers. Here I will use zoom range from 12 to 17 and I will use the bookmark for the extent. Keep the other things default which have to do with compression and save this as infrared MB tiles. After running close the dialog and then you can add the file to the map canvas from the browser panel and when you zoom in you see that it has the more detailed tiles visible. Now let's add elevation data. I'm first going to load 0.5 meter 50 centimeter digital surface model in the WCS type so a real raster. We have the whole country available at 50 centimeter raster pixels and here it is. Before it is useful and fast it's better to export it immediately to the extent for which we need it instead of having the whole country. Export it to the map canvas extent. Click OK. There it loads. I can remove the online layer and I can now style the surface model. Use single vamp pseudo color and choose a ramp. I'll choose a ramp with a lot of different colors and then I can play with the minimum maximum settings to get a bit more contrast in the scene. Then I can also play with the other settings here like a combative count which works very well with extreme values. Now you see there are patterns here in the landscape. There are some depressions, ditches, former parcels. That's all visible now. Often we are not interested in the human and natural objects at the surface and need a digital terrain model. So I'm now going to add the digital terrain model at 50 centimeter resolution to our project. And I follow the same procedure to export it. Call it DTM. I'm going to use the same extent as the DSM. And there is the result. I can remove the online layer and then copy the style from the DSM. Here you can see the difference and you can see a bit more easily the contrast in the fields because the higher objects are removed. These raster elevation models are derived from point cloud data and if you want to filter and analyze it to yourself from the source you can also download the point cloud data directly from this website geotiles.nl Our study area spread over a few tiles but I'm going to demonstrate just for one tile. So we're going to download this one and then the newest version so we have the most recent data available for four different years. So the most recent one is AHN4. After downloading you can find the LAZ file with the point cloud data in your folder. And if you drag it to the map canvas you just start processing it so first it will show you the extent. After processing it will show you the RGB colors in the data. You zoom in we can see that these are indeed points from the point cloud and it's not an aerial photograph. And we can use the layer styling panel to choose different ways of visualization so the extent only or use a classification. It has a built-in classification, it's a bit coarse. There are also other attributes available that you can use. I'm switching it back to RGB. There's also styling for the 3D view which I'm going to demonstrate. You can choose to follow the 2D symbology or do it differently for the 3D view. I'm going to add aerial photograph in the background so we have a bit of context when I go to the 3D view. I add a new 3D map view and it immediately recognizes that the point cloud is elevation data. So I can simply navigate there and we can see the trees and the windmill clearly at the surface. I could also use a color ramp for elevation. There's also a nice newer tool in QGIS, the elevation profile. It adds a panel and it recognizes that the point cloud is elevation data so it will be added. I can use this button to create a transect. With the right mouse button I can close the line and it will show me the points of the point cloud. If I increase the tolerance it will look in a buffer area around it and it gives a nicer image of objects that we encounter along the transect. These can be trees, crops, but also that windmill. We also have other elevation data like the terrain from the DTM. If you go to the layer properties there's a new tab, their elevation. You can check a box and say that this represents the elevation surface. You can change the color on how it will show up in the profile tool. There I can switch it on, switch off the point cloud and if I zoom in I can see more details. I can use a pen and zoom and then you can see the more subtle differences in elevation here in the area. The cursor is also followed on the map. I can plug different elevation models on top of each other in this profile. A very useful layer for agriculture is a layer with parcels. The Netherlands has parcel data every year with a crop. You can load it also directly here in a WFS format, a real-factor format. Here it's loaded. Make sure that you're zoomed to a small area otherwise it will load all the polygons of the country. The first thing that we're going to do is clip this to our study area. I export this to a geopackage that's most efficient. We'll call the geopackage form data and let's call the layer parcels. I check the box for extent. I use our bookmark and there's our clips layer in a local file. I can check the attribute table and there I see different attributes. Gewas means crop and it has a year. That's useful information to know what crops are growing where in this area. Let's style this map with a categorized renderer. I choose the crops. Gewas. Click classify and you get a random color. That's a lot of different crops in the Netherlands. It's a whole legend that I can filter to only show what is in this view. That's already a lot of different crops but gives a much more comprehensive view on it. Let's zoom to our study area and we see that this has a lot of small sub-parcels there. For studies I'm going to bookmark also this more detailed location for later. Smaller study area. I choose precision agriculture and make it also available for all projects linked to my user profile. The last layer that I want to add is a soil map. That's a bottom flocking. It's only available as WMS. I only get a picture. I add it here and you see when we are zoomed into this area. There are just two classes. When I zoom out I can see much more. It's an interesting map to look at for the whole of the Netherlands. You see the different soil types. The one in the area that we were looking at is reclaimed land. These are very young soils. It's also useful to see the parcel boundaries on top of the soil map. I'm going to duplicate the farm data parcels layer. I'm going to style the duplicate with a simple symbol. A simple line. Make it thicker black and then I zoom to the smaller study area. You can see which parcel is spread over the different soils. I hope this video was useful. Now you know how to get access to very nice high-resolution spatial data sets to the PDOX Services plugin.