You are on the right track and the geopandas GeoDataFrame is a good choice for rasterization over Fiona. Fiona is a great toolset, but I think that the DataFrame is better suited to shapefiles and geometries than nested dictionaries.
import geopandas as gpd
import rasterio
from rasterio import features
Set up your filenames
shp_fn = 'cb_2013_us_county_20m.shp'
rst_fn = 'template_raster.tif'
out_fn = './rasterized.tif'
Open the file with GeoPANDAS read_file
counties = gpd.read_file(shp_fn)
Add the new column (as in your above code)
for i in range (len(counties)):
LSAD = counties.at[i,'LSAD']
if LSAD == 00 :
counties['LSAD_NUM'] == 'A'
elif LSAD == 03 :
counties['LSAD_NUM'] == 'B'
elif LSAD == 04 :
counties['LSAD_NUM'] == 'C'
elif LSAD == 05 :
counties['LSAD_NUM'] == 'D'
elif LSAD == 06 :
counties['LSAD_NUM'] == 'E'
elif LSAD == 13 :
counties['LSAD_NUM'] == 'F'
elif LSAD == 15 :
counties['LSAD_NUM'] == 'G'
elif LSAD == 25 :
counties['LSAD_NUM'] == 'I'
else :
counties['LSAD_NUM'] == 'NA'
Open the raster file you want to use as a template for feature burning using rasterio
rst = rasterio.open(rst_fn)
copy and update the metadata from the input raster for the output
meta = rst.meta.copy()
meta.update(compress='lzw')
Now burn the features into the raster and write it out
with rasterio.open(out_fn, 'w+', **meta) as out:
out_arr = out.read(1)
# this is where we create a generator of geom, value pairs to use in rasterizing
shapes = ((geom,value) for geom, value in zip(counties.geometry, counties.LSAD_NUM))
burned = features.rasterize(shapes=shapes, fill=0, out=out_arr, transform=out.transform)
out.write_band(1, burned)
The overall idea is to create an iterable containing tuples of (geometry, value), where the geometry is a shapely geometry and the value is what you want to burn into the raster at that geometry's location. Both Fiona and GeoPANDAS use shapely geometries so you are in luck there. In this example a generator is used to iterate through the (geometry,value) pairs which were extracted from the GeoDataFrame and joined together using zip().
Make sure you open the out_fn file in w+ mode, because it will have to be used for reading and writing.
To write to GeoJSON:
dataframe.to_file("output.json", driver="GeoJSON")
To write to GeoPackage:
dataframe.to_file("output.gpkg", driver="GPKG")
Documentation is here, though somewhat sparse.
Best Answer
As with Fiona where you can specify the driver when you save a layer, you can do the same thing with GeoPandas (Writing Spatial Data)
In my case:
The OpenFileGDB driver is Read-only ('r', provides only read access to File Geodatabases)
If you want read and write access, you need to use the FileGDB driver ('raw')
If the driver is not installed, a solution is given in How to add support for FileGDB (Esri file gdb API) driver in fiona?