Vector Operations¶

SudaPy provides a set of vector geoprocessing functions accessible from both the CLI and Python API. All functions accept GeoPackage (.gpkg), GeoJSON, and Shapefile (.shp) formats.

Reproject¶

Change the coordinate reference system of a vector dataset.

CLIPython

sudapy vector reproject --in regions.gpkg --out regions_utm.gpkg --to 32636

from sudapy.vector.ops import reproject

gdf = reproject("regions.gpkg", to_epsg=32636, out="regions_utm.gpkg")

Clip¶

Clip a vector dataset using another geometry as a mask.

CLIPython

sudapy vector clip --in parcels.gpkg --clip boundary.gpkg --out clipped.gpkg

from sudapy.vector.ops import clip

gdf = clip("parcels.gpkg", "boundary.gpkg", out="clipped.gpkg")

Note

If the clip geometry has a different CRS, SudaPy automatically reprojects it to match the input.

Dissolve¶

Merge geometries by an attribute field.

CLIPython

sudapy vector dissolve --in districts.gpkg --by state_name --out states.gpkg

from sudapy.vector.ops import dissolve

gdf = dissolve("districts.gpkg", by="state_name", out="states.gpkg")

Calculate area¶

Add an area column in square meters.

CLIPython

sudapy vector area --in parcels.gpkg --field area_m2 --out parcels_area.gpkg

from sudapy.vector.ops import calculate_area

gdf = calculate_area("parcels.gpkg", field="area_m2", out="parcels_area.gpkg")

Automatic UTM projection

If the input CRS is geographic (lat/lon), SudaPy temporarily projects to the estimated UTM zone for accurate metric area. A warning is emitted. For best accuracy, reproject your data to a projected CRS first.

Buffer¶

Create buffer zones around geometries. Distance is specified in meters.

CLIPython

sudapy vector buffer --in wells.gpkg --distance 500 --out wells_buffer.gpkg

from sudapy.vector.ops import buffer

gdf = buffer("wells.gpkg", distance_m=500, out="wells_buffer.gpkg")

If the input CRS is geographic, SudaPy auto-projects to UTM, applies the buffer in meters, then projects back to the original CRS.

Simplify¶

Reduce vertex count using the Douglas-Peucker algorithm. Tolerance is in meters.

CLIPython

sudapy vector simplify --in detailed.gpkg --tolerance 100 --out simplified.gpkg

from sudapy.vector.ops import simplify

gdf = simplify("detailed.gpkg", tolerance_m=100, out="simplified.gpkg")

Fix geometry¶

Repair invalid geometries using Shapely's make_valid.

CLIPython

sudapy vector fix-geometry --in broken.gpkg --out fixed.gpkg

from sudapy.vector.ops import fix_geometry

gdf = fix_geometry("broken.gpkg", out="fixed.gpkg")

Tip

Run sudapy report --in file.gpkg first to check how many invalid geometries exist before fixing.

Supported formats¶

Extension	Format	Read	Write
`.gpkg`	GeoPackage	Yes	Yes
`.geojson` / `.json`	GeoJSON	Yes	Yes
`.shp`	ESRI Shapefile	Yes	Yes

Working with GeoDataFrames directly¶

All functions accept either a file path or a geopandas.GeoDataFrame. The out parameter is optional -- omit it to get the result in memory without writing to disk:

import geopandas as gpd
from sudapy.vector.ops import buffer, calculate_area

gdf = gpd.read_file("parcels.gpkg")

# Chain operations in memory
gdf = calculate_area(gdf, field="area_m2")
gdf = buffer(gdf, distance_m=100)

# Write only at the end
gdf.to_file("result.gpkg", driver="GPKG")