Modified row2cell function from https://geographicdata.science/book/notebooks/03_spatial_data.html#one-pixel-at-a-time

rioxarray_polygonize.py

import pandas
import geopandas
import rioxarray
from shapely.geometry import box

def _polygonize(rioxarray_obj):
    
    """"""
    
    poly_ls = []
    
    #crs = clipped.rio.crs #TO DO - get crs from clipped.spatial_ref
    
    # Convert to Pandas Series
    series = rioxarray_obj.to_series().reset_index(drop=False).rename(columns={0: "Value"})
    
    # Affine transformation
    af = clipped.rio.transform()
    # Return non-negative x and y resolution
    xres, yres = abs(af[0]), abs(af[4])
    
    # Loop through each row and create grid cell
    for row in range(len(series)):
        row = series.loc[row, :]
        # Define poly bounds
        xmin = row["x"] - (xres / 2)
        xmax = row["x"] + (xres / 2)
        ymin = row["y"] + (yres / 2) 
        ymax = row["y"] - (yres / 2)
        # Create poly
        cell = box(xmin, ymin, xmax, ymax)
        poly_ls.append(cell)
    
        
    # Create GeoDataFrame
    gdf = pd.concat([series["Value"], geopandas.GeoSeries(poly_ls).to_frame("geometry")], axis=1).crs=4326
    
    return gdf

The row2cell function from https://geographicdata.science/book/notebooks/03_spatial_data.html#one-pixel-at-a-time creates vectorized cells that are off centre from the actual raster. The _polygonize function vectorizes each raster cell and returns a GeoDataFrame with the accompanying raster value.

Original function;

def row2cell(row, res_xy):
    res_x, res_y = res_xy
    minX = row["x"]
    maxX = row["x"] + res_x
    minY = row["y"] + res_y
    maxY = row["y"]
    poly = box(minX, minY, maxX, maxY)
    return poly