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pythongeopandaspython-xarraygeotiffrasterio
emax
emax

Reputation: 7245

Python: how to convert geotiff to geopandas?

I have a geotiff file.

import xarray as xr
urbanData = xr.open_rasterio('myGeotiff.tif')
plt.imshow(urbanData)

Here the link to the file.

I can convert the file as a dataframe with coordinates as points

ur  = xr.DataArray(urbanData, name='myData')
ur  = ur.to_dataframe().reset_index() 
gdfur  = gpd.GeoDataFrame(ur, geometry=gpd.points_from_xy(ur.x, ur.y))

However I would like to get a dataframe that contains the geometry of the pixels as polygons and not as points. Is it possible?

Upvotes: 3

Views: 5008

Answers (2)

snowman2
snowman2

Reputation: 711

With geocube 0.4+:

import rioxarray
from geocube.vector import vectorize

data = rioxarray.open_rasterio("myGeotiff.tif").squeeze()
data.name = "myData"
gdf = vectorize(data)

Upvotes: 0

Huite Bootsma
Huite Bootsma

Reputation: 481

Somewhat to my surprise, I haven't really found a package which wrap rasterio.features to take DataArrays and produce GeoDataFrames.

These might be very useful though:

https://corteva.github.io/geocube/stable/

https://corteva.github.io/rioxarray/stable/

I generally use something like this:

import affine
import geopandas as gpd
import rasterio.features
import xarray as xr
import shapely.geometry as sg


def polygonize(da: xr.DataArray) -> gpd.GeoDataFrame:
    """
    Polygonize a 2D-DataArray into a GeoDataFrame of polygons.

    Parameters
    ----------
    da : xr.DataArray

    Returns
    -------
    polygonized : geopandas.GeoDataFrame
    """
    if da.dims != ("y", "x"):
        raise ValueError('Dimensions must be ("y", "x")')

    values = da.values
    transform = da.attrs.get("transform", None)
    if transform is None:
        raise ValueError("transform is required in da.attrs")
    transform = affine.Affine(*transform)
    shapes = rasterio.features.shapes(values, transform=transform)

    geometries = []
    colvalues = []
    for (geom, colval) in shapes:
        geometries.append(sg.Polygon(geom["coordinates"][0]))
        colvalues.append(colval)

    gdf = gpd.GeoDataFrame({"value": colvalues, "geometry": geometries})
    gdf.crs = da.attrs.get("crs")
    return gdf

Note that you should squeeze the band dimensions from your xarray first to make it 2D, after reading it with xr.open_rasterio:

urbanData = xr.open_rasterio('myGeotiff.tif').squeeze('band', drop=True)

Upvotes: 2

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