[GIS] Calculate land cover for grid cells in QGIS

intersectionland-coverland-useqgis

I have a raster containing information on the land cover type in a region.
I also have an ESRI shapefile consisting of a grid composed of 2500 cells. I would like to calculate the percentage cover of each land cover type in each cell.

To do this, I vectorized my raster and dissolved the polygons to obtain a shapefile where each polygon is a land cover type. I then tried to use the intersection tool to obtain a shapefile with polygons for each land cover type in each cell. This procedure takes too much time however (days by my calculation). I have also tried to split the grid into smaller grids but still faced the same problem.

Is there a more effective way of obtaining what I want?

Best Answer

You can use Raster layer zonal statistics in which you can select the land cover raster layer as input file, and use the shapefile as zone layer. It will calculate the area (in the raster unit) of each land cover within each zone in the shapefile. Then it will be easy to calculate the percentage.

The tool is available from Processing toolbox -> Raster Analysis -> Raster layer zonal statistics.

Check the help above for more information.

I am using QGIS 3.10.4.

Related Solutions

[GIS] How to extract percentage of land cover from a raster according to multiple shapefiles

One solution would be to convert each of your polygons to rasters. Then take the portion of cell counts in each landcover class by the total cell count from the clip. Here is an example function:

    PortionClassInPoly <- function(MySingleShape, MainRaster) {

    # Start with one shape from your list
    # Rasterize this shape according to the parameters of your background raster
       mini_rast <- rasterize(MySingleShape, MainRaster, fun='last')  
    # divide by itself - to make new set new raster values to 1 (NA values stays as NA). 
       mini_rast <- mini_rast/mini_rast
    # get the total number of cells for this shape (save for below)
       total_cells <- cellStats(mini_rast, 'sum')

    # multiply by original - to make a mask layer from your original raster
       my_cutout <- MainRaster*mini_rast
    # Count the number of cells for each discrete landcover class
       in_this_poly_unit <- freq(my_cutout)
    # Divide the cell count for each of these classes by the total 
    # number of cells in your current shape
       class_percents <- in_this_poly_unit[,2]/total_cells

    # make the function return a dataframe with
    # % landcover in each class for each shape
       output <- data.frame(myclass=in_this_poly_unit[,1], portion=class_percents)

       return(output)
    }

With your data, copy and paste the above & then try this function in your loop:

    PortionClassInPoly(MySingleShape=list.shape[[k]], MainRaster=r.landcover)

    # you should get something like this:
    # percentage of every land cover for a shapefile 

      myclass   portion
    1       1 0.1726333
    2       2 0.1662689
    3       3 0.1718377
    4       4 0.1789976
    5       5 0.1662689
    6       6 0.1439936

[GIS] land Use land cover classification

If you use QGIS, there is a plugin named "semi automatic classification". It may not take too much time to utilize the plugin because you might be familiar with the RS analysis methods. I have used it for 1 week and have been pleased. The plugin is also capable of downloading landsat's photos. Here's the link of classification tutorial. https://youtu.be/nZffzX_sMnk

Best Answer

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[GIS] How to extract percentage of land cover from a raster according to multiple shapefiles

[GIS] land Use land cover classification

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