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# GeoDataFrame.invalid_coverage_edges

> Return edges causing invalid polygonal coverage for each geometry.

Return edges causing invalid polygonal coverage for each geometry.

The result preserves every input row and index level. Polygon candidate
neighbours are discovered with a native spatial join over envelopes
expanded by `gap_width` and aggregated on Spark executors; geometry
rows are not collected to the driver.

## Signature

```python theme={"system"}
invalid_coverage_edges(*, gap_width=0.0)
```

## Parameters

<ParamField path="gap_width" type="float" default="0.0">
  Finite, non-negative maximum width of gaps to report as coverage
  invalidities.
</ParamField>

## Returns

<ResponseField name="return" type="GeoSeries">
  Invalid `LineString` or `MultiLineString` edges for each input
  geometry. Rows without invalid edges or polygonal components
  contain an empty line, missing geometries remain missing, and the
  returned GeoSeries is unnamed.
</ResponseField>

<Note>
  Executor memory for an individual source row scales with the number of
  polygon candidates whose envelopes fall within `gap_width`.
</Note>

**See also**

* `GeoSeries.is_valid_coverage`: test whether the full geometry column is
* `a coverage`

## Examples

```python theme={"system"}
>>> from shapely.geometry import box
>>> from sedona.spark.geopandas import GeoSeries
>>> overlapping = GeoSeries(
...     [box(0, 0, 1, 1), box(0.5, 0, 1.5, 1)]
... )
>>> edges = overlapping.invalid_coverage_edges()
>>> edges.to_geopandas().is_empty.tolist()
[False, False]
```


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