Geospatial · Areas and surfaces

Trade Areas

Builds catchment areas around each location: distance rings, drive-time bands, areas traced from demand, or rings cut into sectors.

Also known as: Catchment, market area

How it works

Choose a Method. Radius (buffer rings), the default, draws the Ring radii (1000, 3000, 5000 by default, in Metres or CRS units) around the Point geometry column. Drive time (isochrone bands) routes from the Origin latitude and Origin longitude columns with the Travel mode and Budget bands (5, 10, 15 minutes by default, or metres) and needs routing tiles. Density trace (demand hotspots) bins a second input of demand points into H3 cells at the H3 resolution (8), weighted by an optional Weight column, keeps the cells above the Density threshold (Absolute or Percentile of cells) and traces them into one polygon, or one per location. Pie slice (directional wedges) cuts the rings into Sectors (4), turned by Rotation or aligned to the demand points.

Rings are cumulative unless you tick Donut bands, which subtracts each ring from the next. Radius, Drive time and Pie slice rows carry ring_min and ring_label (such as "0-5000") beside the upper bound, so you can group by band; Radius rows also carry ring_index, radius, method and ring_area. Density trace rows have no rings: they carry method, h3_resolution, threshold_kind, threshold, density_cutoff, cell_count, demand_total and ring_area. For the Radius method a blank Ring column replaces the geometry; a name adds it as a column, keeping the location point unless you untick Keep the location geometry.

Inputs and outputs

Settings

{
  method: "radius"|"drive-time"|"heatmap-trace"|"pslice"
  geometryColumn: string
  radii: number[]
  unit: "meters"|"crsUnits"
  donut: boolean
  lat: string
  lon: string
  costing: "auto"|"bicycle"|"pedestrian"|"truck"
  budgets: number[]
  budgetType: "minutes"|"metres"
  demandGeometryColumn: string
  resolution: number (0-15)
  weightColumn: string
  threshold: number
  thresholdKind: "absolute"|"percentile"
  perLocation: boolean
  sectorCount: number (2-36)
  rotationDeg: number
  alignToDemand: boolean
  outputColumn: string
  keepSource: boolean
}

Example

For 1, 3 and 5 km bands around stores, pick Radius, Unit Metres, Ring radii 1000, 3000, 5000 and tick Donut bands, then Spatial Join population points and group by ring_label.

More in Areas and surfaces

• Gravity Model — Splits each area's demand between the locations in range by their attractiveness and distance (the Huff model). Gives the demand each location captures, such as a new store's sales and what it takes from the others, the top location per area, or a probability for every area and location.
• Calibrate Gravity Model — Fits the Gravity Model's attractiveness and distance-decay settings to what customers actually did, such as loyalty-card visits per area and store, and reports how well the fit reproduces each store.
• Voronoi — Draws one area per point covering everywhere closer to it than to any other point, such as the nearest-store territory for every shop.
• H3 Aggregate — Puts features into hexagon cells of a chosen size and summarizes each cell, for an even grid on density maps.
• Spatial Interpolate — Estimates a smooth surface from measured sample points, on a hexagon or square grid. For example, a pollution surface from sensors.