 Hello, I'm Hans van der Kwasst, senior lecturer at IHE Delft Institute for Water Education. In previous videos I've showed how to install PC Raster within the Anaconda environment and to set all the environment variables. In another video I've demonstrated how to do catchment delineation using PC Raster Python. In this video I'm going to show you the first steps of setting up a model, which is to import your data and re-sample the data to the clone map. So PC Raster needs a clone map because all the rasters need to be of the same dimensions as the clone map, which means it needs to have the same origin projection and it needs to have the same rows and columns and the same cell size. So for this purpose I have downloaded Corrine land cover map, 100 meter resolution, and I'm going to use as a clone the catchment map that we created before, which has a spatial resolution of 30 meters and covers the raw catchment. So this land cover dataset covers Europe and what we're going to do is re-sample it to the area covered by our catchment that we delineated in a previous video. So I'm now in the Anaconda prompt and first I need to change the environment to the PC Raster environment that I created in a previous video. So we do conda, activate PC Raster, and there we are. Now I go to the folder where I saved my file. The file that we are going to work with is this CLC. So I'm going to do a GDAL info to see what the projection is. The projection is EPSG-3035, it's in ETRS-89. What I want is to have it in the projection of our project, that is UTM Zone 32 North on WGS-84. So I need to use GDAL Warp, maybe you remember that from last video. So GDAL Warp, if I just type the command I get here all the options and I'm going to re-project it to UTM and I'm going to crop it to catchment boundary or to the bounding box in a similar way as we did last time. So that will be GDAL Warp. So I'm going to use GDAL Warp to convert it to UTM Zone 32 North on WGS-84. And the command is GDAL Warp, the SRS EPSG 32632, and then the input file name CLC. And I will call it Corrine2018.tiff. We're getting this error because the file is simply too big to handle with a tiff. We need a special format pick tiff but that's unavailable in these tools. So therefore we're going to use this bounding box shapefile to crop it a little bit before we will go further in the steps. So we change the command to crop to the cutline with the shapefile and now it works and we see that it creates the new file cropped to the boundary of our shapefile. So the next step is to re-sample this to the clone. But first we need to put it in the PCRuster format. So we need to use GDAL Translate. So a land use or land cover map is a nominal map, discrete data. So it's integer 32 and we use the value scale nominal. We indicate that in GDAL Translate to be sure that in PCRuster it is seen as a nominal map. And now it's in PCRuster format. So we can visualize it using Aguila and there we see the map cropped to our boundary with all the land use classes, the levels of Corrine. Now we can use the re-sample command to make it the same size as our clone. So we use the command re-sample, the input is the Corrine2018.map file. I create an output which I call land cover map and I use as a clone the catchment map which means that the Corrine2018 map will be re-sampled using the same properties as our catchment of map. So it will have the same cell size, the same origin of the coordinates and the same number of rows and columns. And that's important because all the maps that we use in a PCRuster model with map algebra or dynamic modeling needs to have the same dimensions as the clone map. So with Aguila we can now visualize these three maps to see if they are visible and there are no problems with it. So Aguila, Corrine2018, land cover map and row catchment and we see the three maps now on the screen. We don't see much difference here between land cover and the Corrine one. So I'm going to look at the map properties. And the command for that is map attributes, map header, minus b for properties and then I can put a list of maps for which I want to have the properties on the screen. So I use the original Corrine 2018, the land cover map and the row catchment map. And what we see is that the original at 100 meters cell length a bit more because of the reprojection and we didn't say it has to be 100 meters. So that has less rows and columns and we re-assembled it to 30 meters. So when we look at landcover.map it has now the same properties as rowcatchment.map. And we can see that also the origin of the coordinates are exactly the same. So now this land cover map is suitable for use in your model and you should do this for all the raster files that you import from elsewhere and want to use in your PC raster model.