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spatial-operations

spatial-operations

Use when running GeoPandas spatial joins, nearest joins, overlays, clips, dissolves, spatial indexes, and Shapely-backed geometry analysis operations.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill-Dokumentation

GitHub

name: spatial-operations description: "Use when running GeoPandas spatial joins, nearest joins, overlays, clips, dissolves, spatial indexes, and Shapely-backed geometry analysis operations." disable-model-invocation: true metadata: disco-role: operating license: BSD 3-Clause

Spatial Operations

Use this sub-skill when the task combines, filters, aggregates, or transforms geometries with GeoPandas analysis APIs.

Read First

  • Operations reference: verified signatures and parameter notes for joins, overlay, clip, dissolve, spatial index, and common geometry methods.
  • Workflows: recipes for CRS-safe joins, nearest analysis, overlay/clip, dissolve, invalid-geometry repair, and metric operations.
  • Troubleshooting: fixes for CRS mismatch, unexpected join cardinality, invalid geometries, empty overlays, distance warnings, and spatial-index confusion.
  • spatial_operations_smoke.py: tiny deterministic check covering sjoin, overlay, clip, dissolve, and .sindex.

Route Here When

  • The task mentions sjoin, GeoDataFrame.sjoin, sjoin_nearest, predicate, lsuffix, rsuffix, distance_col, or spatial predicates.
  • The task asks for overlay, set operations (intersection, union, identity, symmetric_difference, difference), keep_geom_type, make_valid, or polygon validity repair.
  • The task uses clip, dissolve, explode, union_all, intersection_all, buffer, distance, dwithin, contains, within, intersects, nearest, or spatial index queries.
  • The user needs to choose a projected CRS for metric analysis, use a spatial index explicitly, or reason about output row/cardinality behavior.

Route Elsewhere

  • Use ../core-data-model/SKILL.md to create GeoDataFrames, repair active geometry columns, or understand CRS assignment versus reprojection basics.
  • Use ../io-formats/SKILL.md to read/write layers before or after operations.
  • Use ../mapping-geocoding/SKILL.md to visualize operation results.
  • Use ../validation-testing/SKILL.md for equality assertions or focused native tests.

Default Operating Rules

  1. Inspect .crs on every input before combining layers. Reproject, do not override, when coordinates need transformation.
  2. For metric operations (buffer, distance, dwithin, nearest thresholds), use a projected CRS with linear units.
  3. Validate polygon inputs before overlay or union. Use make_valid() when invalid geometry is an expected data-quality issue.
  4. Choose the predicate intentionally: intersects is broad; within/contains are directional; boundary-only relationships may surprise users.
  5. Expect join and overlay outputs to change row counts and add suffixes/index columns. Document cardinality and column naming.
  6. Use .sindex.valid_query_predicates to discover available spatial index predicates in the current environment.

Minimal Check

python scripts/spatial_operations_smoke.py

Expected high-level signal: the script reports successful spatial join, overlay, clip, dissolve, and spatial-index assertions on tiny in-memory geometries.

Handoff

  • Validate objects and CRS with core-data-model first when inputs are uncertain.
  • Persist operation outputs with io-formats only after verifying CRS and geometry validity.
  • Use mapping-geocoding for visualization and validation-testing for assertion-backed comparisons.
Gespeicherte Skills