Available Capabilities

Capabilities are the unit operations GISPulse can apply to spatial datasets. They are invoked inside JSON rules via the capability field.

bash

# List all capabilities
gispulse capabilities

Each rule calls a capability and passes it a config block. The parameters below are the keys of that block.

json

{
  "capability": "<name>",
  "ref_layer": "<optional>",
  "config": { "...": "..." }
}

Source of truth

The code is authoritative. For the exact schema of a capability (parameters, types, defaults):

python

from capabilities.registry import REGISTRY
REGISTRY.get("buffer")().get_schema()

Total registered capabilities: 117 — across 18 categories.

Vector — selection & join (Community)

Available in every tier. Capabilities tagged DuckDB / PostGIS go through the multi-backend Strategy pattern (dispatch by input size).

`buffer`

Metric buffer around geometries. Automatically reprojects to a metric CRS when needed.

Engines: Python (GeoPandas), DuckDB (ST_Buffer, > 50,000 features), PostGIS (server-side).

json

{
  "capability": "buffer",
  "config": { "distance": 100, "crs_meters": "EPSG:3857" }
}

Parameter	Type	Default	Description
`distance`	float	`0.0`	Distance in meters
`crs_meters`	string	`EPSG:3857`	Intermediate metric projection
`cap_style`	string	`round`	`round`, `flat`, `square`
`join_style`	string	`round`	`round`, `mitre`, `bevel`

`filter`

Filters features by attribute expression and/or spatial predicate. Supports cross-layer references.

Engines: Python (gdf.query + Shapely), DuckDB (SQL), PostGIS.

json

{
  "capability": "filter",
  "config": {
    "expression": "surface > 500 and usage == 'residential'",
    "spatial_predicate": "intersects",
    "ref_layer": "flood_zones",
    "buffer_distance": 50
  }
}

Parameter	Type	Description
`expression`	string	Python expression evaluated against columns
`spatial_predicate`	string	`intersects`, `within`, `contains`, `crosses`, `overlaps`, `touches`, `dwithin`
`ref_layer`	string	Reference layer for the spatial predicate
`ref_wkt` / `ref_geojson`	string / object	Explicit WKT or GeoJSON reference geometry
`buffer_distance`	float	Buffer (meters) applied to the reference geometry

`intersects`

Keeps features intersecting a reference geometry or layer (shortcut for a spatial filter).

json

{ "capability": "intersects", "config": { "ref_layer": "flood_zones" } }

`clip`

Clips features to the extent of a reference layer.

json

{ "capability": "clip", "config": { "ref_layer": "study_area" } }

`spatial_join`

Spatial join between the processed layer and a reference layer. Attaches reference attributes to matching features.

json

{
  "capability": "spatial_join",
  "config": { "ref_layer": "municipalities", "how": "left", "op": "intersects" }
}

Parameter	Type	Default	Description
`ref_layer`	string	required	Reference layer
`how`	string	`left`	`left`, `inner`, `right`
`op`	string	`intersects`	`intersects`, `contains`, `within`

`nearest_neighbor`

Joins attributes from the k nearest features of a reference layer, with optional max_distance.

json

{
  "capability": "nearest_neighbor",
  "config": { "ref_layer": "schools", "k": 1, "max_distance": 2000, "distance_col": "dist_school_m" }
}

Parameter	Type	Default	Description
`ref_layer`	string	required	Reference layer
`k`	int	`1`	Number of neighbours
`max_distance`	float	none	Max distance in meters
`distance_col`	string	`distance`	Name of the emitted distance column

`spatial_aggregate`

Aggregates values from a reference layer via a spatial predicate (count, sum, mean, min, max).

json

{
  "capability": "spatial_aggregate",
  "config": {
    "ref_layer": "households",
    "aggregations": { "population": "sum" },
    "predicate": "contains"
  }
}

`reproject`

Reproject to a target CRS.

json

{ "capability": "reproject", "config": { "target_crs": "EPSG:2154" } }

Vector — overlay & combine (Community)

Combine multiple layers into one — either geometrically (FME / QGIS-style overlay) or by concatenation.

Capability	Description	Key parameters
`overlay_intersection`	Geometric intersection of two layers — attributes inherited from both sides.	`ref_layer`, `keep_geom_type`, `suffix_left`, `suffix_right`
`overlay_union`	Geometric union — keeps A-only, B-only and A∩B fragments.	`ref_layer`, `keep_geom_type`, `suffix_left`, `suffix_right`
`erase`	Geometric difference — removes from A whatever is covered by B (A attributes preserved).	`ref_layer`, `keep_geom_type`
`merge_layers`	Concatenates the primary layer with a list of `ref_layers`.	`ref_layers` (array)
`classify_by_ring`	Classifies every feature by the smallest containing ring (concentric isochrones / buffers) — emits `value` / `class` / `color`.	`ref_layers`, `ring_field`, `outside_value`, `palette`

json

{
  "capability": "overlay_intersection",
  "config": { "ref_layer": "zoning_plu", "suffix_right": "_plu" }
}

json

{
  "capability": "classify_by_ring",
  "config": {
    "ref_layers": ["iso_500", "iso_1000", "iso_1500"],
    "ring_field": "cost_budget",
    "palette": "YlGnBu"
  }
}

Vector — derived geometry (Community)

Capability	Description	Key parameters
`centroid`	Replaces each geometry with its centroid.	—
`envelope`	Axis-aligned bounding box.	—
`oriented_bbox`	Minimum rotated rectangle (buildings, parcels).	—
`min_bounding_circle`	Minimum bounding circle (Shapely ≥ 2.1).	—
`convex_hull`	Convex hull. Supports `by_group` / `dissolve`.	`by_group`, `dissolve`
`concave_hull`	k-nearest concave hull.	`k`, `ratio`
`alpha_shape`	Alpha-shape (generalised concave hull).	`alpha`
`delaunay_triangulation`	Delaunay triangulation of vertices.	—
`voronoi_polygons`	Voronoi tessellation of input points.	`bounds`
`polygonize`	Builds polygons from a noded line network.	`snap_tolerance`

json

{ "capability": "convex_hull", "config": { "by_group": "municipality" } }

Vector — editing & metrology (Community)

Capability	Description	Key parameters
`area_length`	Adds `area_m2` / `length_m` columns.	`area_column`, `length_column`
`calculate`	Evaluates an expression to build a new column (sum, avg, min, max, median, std, ...).	`expression`, `output_field`
`dissolve`	Dissolves features by attribute (GROUP BY + ST_Union).	`by`
`union`	Merges every feature into a single geometry.	—
`symmetric_difference`	XOR between each feature and the union of a reference layer.	`ref_layer`
`vector_diff`	Compares two layers by id and flags `added` / `removed` / `modified` / `unchanged`.	`ref_layer`, `id_col`, `geometry_tolerance`
`make_valid`	Repairs invalid geometries (self-intersections, duplicate rings).	—
`simplify`	Simplification (Douglas-Peucker, Visvalingam-Whyatt, topology-preserving).	`tolerance`, `algorithm`
`chaikin_smooth`	Iterative corner-cutting smoother.	`iterations`
`densify_vertices`	Inserts vertices at a target spacing.	`max_distance`, `n_segments`
`snap_to_grid`	Snaps vertex coordinates onto a grid.	`grid_size`
`offset_curve`	Parallel line at a signed distance.	`distance`
`line_merge`	Merges touching line segments.	—
`line_substring`	Line substring between two measures.	`start_measure`, `end_measure`
`line_locate_point`	Projects points onto the nearest reference line + computes the measure.	`ref_layer`
`extract_vertices`	Emits one `Point` per vertex with indices.	—
`extract_segments`	Splits each line / polygon boundary into 2-point segments.	—

json

{ "capability": "simplify", "config": { "tolerance": 5.0, "algorithm": "vw" } }

json

{
  "capability": "calculate",
  "config": { "output_field": "price_m2", "expression": "price / surface_m2" }
}

Vector — attribute manipulation (Community)

Non-spatial schema operations — add, drop, rename, join, lookup table, null fallback.

Capability	Description	Key parameters
`add_field`	Adds one or more columns with a default value.	`fields`, `overwrite`
`drop_field`	Drops columns (geometry is protected).	`fields`, `ignore_missing`
`select_columns`	Keeps only the listed columns (geometry always preserved).	`fields`
`rename_field`	Renames columns via `{old: new}` mapping.	`mapping`, `ignore_missing`
`cast_field`	Casts columns to a target dtype.	`casts`, `errors`
`attribute_join`	Non-spatial join on a key column (left / right / inner / outer).	`ref_layer`, `left_on`, `right_on`, `how`, `columns`, `prefix`, `suffix`
`lookup_table`	Maps a column through a dict with default fallback.	`source_col`, `target_col`, `mapping`, `default`
`coalesce_fields`	First non-null value across a list of columns.	`sources`, `target_col`
`case_when`	SQL-style conditional column.	`target_col`, `cases`, `else_`
`describe`	Schema introspection report (dtype, nulls, unique, geom_type, bounds) — stored under `gdf.attrs["__schema_describe__"]`, layer returned unchanged.	`sample_size`, `include_geometry`

json

{
  "capability": "case_when",
  "config": {
    "target_col": "tier",
    "cases": [
      { "when": "population > 100000", "value": "A" },
      { "when": "population > 10000", "value": "B" }
    ],
    "else_": "C"
  }
}

json

{
  "capability": "attribute_join",
  "config": { "ref_layer": "communes_insee", "left_on": "code_insee", "how": "left" }
}

Vector — pivot / unpivot (Community)

Long ↔ wide reshape (pandas semantics), geometry preserved.

Capability	Description	Key parameters
`pivot`	Long → wide: `columns` becomes new columns, `values` populates the cells.	`index`, `columns`, `values`, `aggfunc`, `fill_value`, `geom_strategy`
`unpivot`	Wide → long: emits `(variable, value)` pairs from `value_vars`.	`id_vars`, `value_vars`, `var_name`, `value_name`

json

{
  "capability": "pivot",
  "config": {
    "index": "municipality_id",
    "columns": "year",
    "values": "population",
    "aggfunc": "sum",
    "geom_strategy": "first"
  }
}

geom_strategy (first, union, centroid) controls how geometries collapse when several rows in the same group carry different geometries.

Vector — ordered selection & sampling (Community)

Sort, deduplicate, random sample, top-N — purely attribute operations.

Capability	Description	Key parameters
`sort`	Orders by one or more columns.	`by`, `ascending`, `na_position`
`deduplicate`	Drops duplicates by attribute key (compare with `duplicate_geometry` which dedupes on geometry).	`keys`, `keep`, `order_by`, `ascending`
`random_sample`	Random sample (`n` or `fraction`, reproducible via `seed`).	`n`, `fraction`, `seed`, `replace`
`top_n`	Keeps the top-N features ordered by a column.	`n`, `by`, `ascending`

json

{ "capability": "top_n", "config": { "n": 100, "by": "rdm_m2", "ascending": false } }

Vector — multipart & Z/M dimensions (Community)

Multipart ↔ singlepart conversion and Z (elevation) / M (measure) dimension management.

Capability	Description	Key parameters
`multipart_to_singleparts`	Explodes `Multi*` features — one row per part, attributes duplicated.	`reset_index`, `drop_empty`
`singleparts_to_multipart`	Collects single-parts into `Multi*`, optionally grouped by attributes.	`by`, `agg`
`add_z`	Adds a Z dimension (constant or `from_column`).	`z`, `from_column`
`drop_z`	Strips the Z dimension → 2D layer.	—
`add_m`	Adds an M dimension (constant or column).	`m`, `from_column`
`drop_m`	Strips the M dimension.	—

json

{ "capability": "add_z", "config": { "from_column": "ground_elevation" } }

Vector — geometric transforms (Community)

Affine transforms, axis swap, line reversal — fast operations that don't touch the CRS.

Capability	Description	Key parameters
`affine_transform`	Translate / rotate / scale / skew (declared order, configurable origin).	`translate`, `rotate`, `scale`, `skew`, `origin`
`swap_xy`	Swaps X and Y on every vertex (rescue mis-exported lat/lon files).	—
`reverse_lines`	Reverses vertex order for `LineString` / `MultiLineString`.	`ignore_non_lines`

json

{
  "capability": "affine_transform",
  "config": { "rotate": 30, "origin": "centroid" }
}

Vector — boundary & projection (Community)

Boundary extraction, hole handling, geometry-type coercion, CRS declaration without transform.

Capability	Description	Key parameters
`boundary`	Topological boundary of every geometry.	`drop_empty`
`extract_holes`	Extracts interior rings (holes) as polygon features.	`parent_id_col`, `hole_index_col`
`force_geometry_type`	Coerces to a target type (Multi → single via explode, etc.).	`target`, `on_multi`, `on_invalid`
`assign_projection`	Sets the layer CRS without reprojecting (use `reproject` to transform).	`crs`, `allow_override`

json

{ "capability": "force_geometry_type", "config": { "target": "Polygon", "on_multi": "explode" } }

assign_projection ≠ reproject

assign_projection only changes the CRS metadata — it does not touch the coordinates. Use it to fix a layer with a wrong or missing CRS.

Temporal (Community)

Filters and joins on datetime columns.

Capability	Description	Key parameters
`temporal_filter`	Filters by a `[start, end]` window on a datetime column. Inversion supported.	`time_col`, `start`, `end`, `include_start`, `include_end`, `invert`
`temporal_join`	Exact or as-of join (`backward` / `forward` / `nearest`) with tolerance.	`ref_layer`, `left_on`, `right_on`, `strategy`, `by`, `tolerance`, `columns`

json

{
  "capability": "temporal_join",
  "config": {
    "ref_layer": "weather_hourly",
    "left_on": "ts_observation",
    "strategy": "nearest",
    "tolerance": "30min",
    "by": "station_id"
  }
}

Validation (Community)

Data quality controls. Validation capabilities return a violations layer (one row per issue detected).

Capability	Description
`topology_check`	Invalid geometries, self-intersections, overlapping polygons.
`duplicate_geometry`	Exact or tolerance-based duplicate detection.
`attribute_validation`	Types, nullability, value ranges, regex, uniqueness.
`completeness_check`	Null ratio per column, spatial coverage relative to a reference extent.

json

{
  "capability": "topology_check",
  "config": { "check_overlaps": true, "check_self_intersections": true }
}

json

{
  "capability": "attribute_validation",
  "config": {
    "schema": [
      { "field": "population", "type": "integer", "min": 0 },
      { "field": "code_insee", "unique": true, "pattern": "^[0-9]{5}$" }
    ]
  }
}

Classification & styling (Community)

Prepares data for thematic cartography: bucketing, colour ramps, style generation.

Capability	Description	Key parameters
`classify`	Buckets a numeric column into N classes (`quantile` / `equal_interval` / `manual` / `jenks` / `pretty` / `std_dev`).	`column`, `method`, `k`, `palette`
`classify_categorical`	Classification by unique values with optional `other` bucket.	`column`, `palette`, `other_threshold`
`head_tail_breaks`	Head/Tail breaks (Jiang 2013) — number of classes driven by the distribution.	`column`
`normalize`	Normalisation (`minmax` / `zscore` / `log` / `log1p` / `rank` / `percent`).	`column`, `method`, `denom`
`continuous_ramp`	Continuous colour gradient (no classification).	`column`, `palette`
`graduated_size`	Proportional symbol size driven by a numeric column.	`column`, `min_size`, `max_size`
`choropleth`	Classification + `LayerStyleDef` + legend (QML/SLD export).	`column`, `method`, `k`, `palette`
`bivariate_choropleth`	Bivariate choropleth (two columns × palette grid).	`column_x`, `column_y`, `n`, `palette`

json

{
  "capability": "choropleth",
  "config": {
    "column": "pop_density",
    "method": "jenks",
    "k": 5,
    "palette": "YlOrRd"
  }
}

Spatial statistics (Community)

Cluster detection, autocorrelation, hot / cold spot analysis.

Capability	Description	Key parameters
`spatial_weights`	Builds spatial weights (queen / rook / k-NN / distance band) and adds `n_neighbours`.	`method`, `k`, `threshold`
`morans_i`	Global Moran's I with permutation-based pseudo p-value. Returns a summary row.	`column`, `weights`, `n_permutations`
`getis_ord_g`	Getis-Ord Gi* z-score per feature (hot / cold spots).	`column`, `weights`

json

{
  "capability": "morans_i",
  "config": { "column": "price_m2", "weights": { "method": "queen" }, "n_permutations": 999 }
}

Density & tessellation (Community)

Grid builders and density surfaces.

Capability	Description	Key parameters
`grid_create`	Regular square fishnet over a ref_layer or explicit bounds.	`cell_size`, `bounds`, `ref_layer`
`hexgrid_create`	Flat-top hexagonal grid.	`cell_size`, `bounds`, `ref_layer`
`kde_heatmap`	KDE sampled on a regular grid → points with `density`.	`bandwidth`, `cell_size`, `bounds`

json

{
  "capability": "hexgrid_create",
  "config": { "cell_size": 500, "ref_layer": "study_area" }
}

Clustering (Community — optional scikit-learn)

Install via pip install "gispulse[cluster]". Each capability adds a cluster column (-1 = noise for DBSCAN / HDBSCAN).

Capability	Description	Key parameters
`cluster_kmeans`	K-Means on geometry centroids.	`k`, `random_state`
`cluster_dbscan`	Density-based DBSCAN.	`eps`, `min_samples`
`cluster_hdbscan`	Hierarchical HDBSCAN, varying densities.	`min_cluster_size`, `min_samples`

json

{ "capability": "cluster_dbscan", "config": { "eps": 200, "min_samples": 5 } }

Line-network topology (Community)

Cleans a line network before running network analysis.

Capability	Description	Key parameters
`network_snap_endpoints`	Snaps near-coincident endpoints together.	`tolerance`
`network_extend_dangles`	Extends dangling endpoints to the closest line.	`tolerance`
`network_node_lines`	Splits each line at every intersection → planar graph.	—
`network_remove_duplicates`	Drops geometric duplicates (direction-agnostic).	`tolerance`
`network_remove_pseudo_nodes`	Merges segments meeting at degree-2 nodes.	—

json

{ "capability": "network_snap_endpoints", "config": { "tolerance": 0.5 } }

Polygon topology (Community)

Repairs a polygon coverage (gaps, overlaps, slivers).

Capability	Description	Key parameters
`polygon_fix_gaps`	Detects gaps below `max_area` and merges them into the neighbour with the longest shared border.	`max_area`
`polygon_fix_overlaps`	Removes overlaps following a rule (`smallest`, `largest`, `first`).	`rule`
`polygon_remove_slivers`	Removes long / thin polygons (`min_area` or `max_shape_index`).	`min_area`, `max_shape_index`
`polygon_snap_borders`	Snaps vertices onto a grid → adjacent borders land on the same coordinates.	`grid_size`

json

{ "capability": "polygon_fix_gaps", "config": { "max_area": 10.0 } }

3D Pointcloud (Community — `pip install "gispulse[pointcloud]"`)

Loading and processing of LAS / LAZ pointclouds (ASPRS). Requires laspy (and lazrs for LAZ).

Capability	Description	Key parameters
`pointcloud_load_las`	Loads a `.las` / `.laz` file into a `GeoDataFrame` of `Point Z`.	`path`, `crs`, `max_points`, `classifications`
`pointcloud_filter_classification`	Filters points by ASPRS classification codes (keep / drop).	`keep`, `drop`, `col`
`pointcloud_zonal_height`	Per-polygon Z statistics (building heights, canopy).	`ref_layer`, `stats`, `prefix`, `ground_col`
`pointcloud_grid_summary`	Bins Z values into a regular grid → polygons with per-cell stats.	`cell_size`, `stats`, `drop_empty`

json

{
  "capability": "pointcloud_load_las",
  "config": {
    "path": "data/lidar/tile_1234.laz",
    "crs": "EPSG:2154",
    "classifications": [2, 6]
  }
}

json

{
  "capability": "pointcloud_zonal_height",
  "config": {
    "ref_layer": "lidar_points",
    "stats": ["max", "mean", "p95"],
    "ground_col": "ground_elevation",
    "prefix": "h_"
  }
}

Common ASPRS class codes

2 = ground, 5 = high vegetation, 6 = building, 9 = water. See the LAS 1.4 spec.

Raster (Pro — `pip install "gispulse[raster]"`)

Requires rasterio + rasterstats and a Pro license (GISPULSE_TIER=pro).

Pro tier

Raster capabilities call check_tier("pro") at runtime.

Capability	Description	Key parameters
`zonal_stats`	Raster statistics (min/max/mean/std/sum/count) per polygon.	`raster_path`, `stats`
`raster_clip`	Clips a raster to a vector extent.	`raster_path`, `output_path`
`ndvi`	NDVI = (NIR − RED) / (NIR + RED) from a multi-band raster.	`raster_path`, `nir_band`, `red_band`
`raster_reproject`	Raster reprojection.	`raster_path`, `target_crs`, `output_path`
`raster_merge`	Merges multiple rasters into one.	`raster_paths`, `output_path`
`change_detection`	Polygonises changed areas between two rasters.	`raster_before`, `raster_after`, `threshold`

json

{
  "capability": "zonal_stats",
  "config": {
    "raster_path": "data/ndvi.tif",
    "stats": ["min", "max", "mean", "std", "sum", "count"]
  }
}

Network analysis (Pro — `pip install "gispulse[network]"`)

Requires networkx and a Pro license.

Capability	Description	Key parameters
`shortest_path`	Dijkstra shortest path between two points.	`origin`, `destination`, `weight_col`
`isochrone`	Reachable area within a budget (distance / time).	`origin`, `max_distance`, `weight_col`
`od_matrix`	Origin-destination matrix in long format.	`origins_layer`, `destinations_layer`, `weight_col`
`mst`	Minimum spanning tree of a line network.	`weight_col`
`network_allocation`	Allocates demand points to the nearest supply node on the network.	`supply_layer`, `weight_col`, `max_cost`
`connectivity_check`	Ensures the network forms a connected graph and returns connected components.	—

json

{
  "capability": "isochrone",
  "config": { "origin": [2.3522, 48.8566], "max_distance": 1000, "weight_col": "length_m" }
}

PostGIS SQL (Pro)

`postgis_sql`

Runs a parameterised SQL query directly on PostGIS for advanced operations not covered by the other capabilities.

json

{
  "capability": "postgis_sql",
  "config": {
    "sql": "SELECT *, ST_Area(geom::geography) AS area_geo FROM {input_table} WHERE ST_IsValid(geom)",
    "geom_col": "geom",
    "params": {}
  }
}

Parameter	Type	Description
`sql`	string	Query using `{input_table}` as placeholder
`params`	object	Named parameters (`$name`) for the query
`geom_col`	string	Geometry column (default: `geom`)
`input_table`	string	Input table (auto-created if missing)

Security

The DSN is never read from config — it is resolved from GISPULSE_POSTGIS_DSN. SQL identifiers are validated (operation_executor.py). Do not expose this capability to untrusted users.

Tier summary

Category	Caps	Tier	Optional extra
Vector — selection & join	8	Community	—
Vector — overlay & combine	5	Community	—
Vector — derived geometry	10	Community	—
Vector — editing & metrology	17	Community	—
Vector — attribute manipulation	9	Community	—
Vector — pivot / unpivot	2	Community	—
Vector — ordered selection & sampling	4	Community	—
Vector — multipart & Z/M dimensions	6	Community	—
Vector — geometric transforms	3	Community	—
Vector — boundary & projection	4	Community	—
Temporal	2	Community	—
Validation	4	Community	—
Classification & styling	8	Community	`mapclassify` (for jenks)
Spatial statistics	3	Community	—
Density & tessellation	3	Community	—
Clustering	3	Community	`gispulse[cluster]` (`scikit-learn`, `hdbscan`)
Line-network topology	5	Community	—
Polygon topology	4	Community	—
3D Pointcloud	4	Community	`gispulse[pointcloud]` (`laspy`, `lazrs`)
Raster	6	Pro	`gispulse[raster]` (`rasterio`, `rasterstats`)
Network analysis	6	Pro	`gispulse[network]` (`networkx`)
PostGIS SQL	1	Pro	`gispulse[postgis]` + DSN
Total	117

Build your own capability

See Developing a plugin for the entry-point publication flow.

python

from capabilities.base import Capability
from capabilities.registry import register

@register
class MyCapability(Capability):
    name = "my_cap"
    description = "Short description of my capability."

    def execute(self, gdf, my_parameter=1.0, **_):
        # business logic here
        return gdf

    def get_schema(self):
        return {
            "type": "object",
            "properties": {
                "my_parameter": {"type": "number", "default": 1.0}
            },
            "required": ["my_parameter"],
        }

A distributed capability can self-register via the gispulse.capabilities entry-point group (see the pyproject.toml in sdk/).

Available Capabilities ​

Vector — selection & join (Community) ​

buffer ​

filter ​

intersects ​

clip ​

spatial_join ​

nearest_neighbor ​

spatial_aggregate ​

reproject ​

Vector — overlay & combine (Community) ​

Vector — derived geometry (Community) ​

Vector — editing & metrology (Community) ​

Vector — attribute manipulation (Community) ​

Vector — pivot / unpivot (Community) ​

Vector — ordered selection & sampling (Community) ​

Vector — multipart & Z/M dimensions (Community) ​

Vector — geometric transforms (Community) ​

Vector — boundary & projection (Community) ​

Temporal (Community) ​

Validation (Community) ​

Classification & styling (Community) ​

Spatial statistics (Community) ​

Density & tessellation (Community) ​

Clustering (Community — optional scikit-learn) ​

Line-network topology (Community) ​

Polygon topology (Community) ​

3D Pointcloud (Community — pip install "gispulse[pointcloud]") ​

Raster (Pro — pip install "gispulse[raster]") ​

Network analysis (Pro — pip install "gispulse[network]") ​

PostGIS SQL (Pro) ​

postgis_sql ​

Tier summary ​

Build your own capability ​

Available Capabilities

Vector — selection & join (Community)

`buffer`

`filter`

`intersects`

`clip`

`spatial_join`

`nearest_neighbor`

`spatial_aggregate`

`reproject`

Vector — overlay & combine (Community)

Vector — derived geometry (Community)

Vector — editing & metrology (Community)

Vector — attribute manipulation (Community)

Vector — pivot / unpivot (Community)

Vector — ordered selection & sampling (Community)

Vector — multipart & Z/M dimensions (Community)

Vector — geometric transforms (Community)

Vector — boundary & projection (Community)

Temporal (Community)

Validation (Community)

Classification & styling (Community)

Spatial statistics (Community)

Density & tessellation (Community)

Clustering (Community — optional scikit-learn)

Line-network topology (Community)

Polygon topology (Community)

3D Pointcloud (Community — `pip install "gispulse[pointcloud]"`)

Raster (Pro — `pip install "gispulse[raster]"`)

Network analysis (Pro — `pip install "gispulse[network]"`)

PostGIS SQL (Pro)

`postgis_sql`

Tier summary

Build your own capability