I want to create a raster file (.tif) from a points file using a geopandas.geodataframe.GeoDataFrame object.
My dataframe has two columns: [geometry] and [Value]. The goal is to make a 10m resolution raster in [geometry] point with the [Value] value.
My dataset is:
geometry | Value
0 | POINT (520595.000 5720335.000) | 536.678345
1 | POINT (520605.000 5720335.000) | 637.052185
2 | POINT (520615.000 5720335.000) | 1230.553955
3 | POINT (520625.000 5720335.000) | 944.970642
4 | POINT (520635.000 5720335.000) | 1094.613281
5 | POINT (520645.000 5720335.000) | 1123.185181
6 | POINT (520655.000 5720335.000) | 849.37634
7 | POINT (520665.000 5720335.000) | 1333.459839
8 | POINT (520675.000 5720335.000) | 492.866608
9 | POINT (520685.000 5720335.000) | 960.957214
10 | POINT (520695.000 5720335.000) | 539.401978
11 | POINT (520705.000 5720335.000) | 573.015625
12 | POINT (520715.000 5720335.000) | 970.386536
13 | POINT (520725.000 5720335.000) | 390.315094
14 | POINT (520735.000 5720335.000) | 642.036865
I have tried before and so, I know that with from geocube.api.core import make_geocube I could do it, but due to some libraries I have a limitation and I cannot use make_geocube.
Any idea?
Assign x and y columns, convert to xarray, then export to tiff using rioxarray:
# do this before sending to xarray
# to ensure extension is loaded
import rioxarray
# assuming your GeoDataFrame is called `gdf`
gdf["x"] = gdf.x
gdf["y"] = gdf.y
da = (
gdf.set_index(["y", "x"])
.Value
.to_xarray()
)
da.rio.to_raster("myfile.tif")
In order for this to work, the points must make up a full regular grid, with values of x and y each repeated for each combination. If this is instead just a collection of arbitrary points converting to xarray with x and y as perpendicular dimensions will explode your memory and the result will be almost entirely NaNs.