Geospatial data preparation
Geospatial Data Services
Location, road, boundary and geographic datasets, delivered in the projection, schema and format your stack expects.
Overview
Most spatial problems are data problems first
Analysts lose more time to broken geometry than to analysis. Self-intersecting polygons, mismatched projections, boundaries that do not tile, road networks that look continuous but are not connected at the junctions: none of it is visible on a screenshot, and all of it changes the answer.
We prepare geospatial data so that the first thing you do with it is analysis, not repair. Geometry is validated, topology is checked, projections are stated explicitly and coordinate precision is appropriate to the source.
Where a national mapping agency or an open dataset already publishes what you need, we say so and help you use it. Paying for data that already exists in the public domain is the most common avoidable cost in this field.
Sample output
The same data, mapped
A static preview rather than an embedded map SDK, so the page stays fast. Interactive maps are built on request as part of a visualization project.
Scope
Datasets we prepare
Layers are delivered individually or as a coherent, joined package.
Administrative boundaries
Countries, regions, municipalities, census units and postcode areas, cleaned so they tile without gaps or overlaps.
Custom zones
Trade areas, delivery zones, sales territories and catchments built to your definition.
Road networks
Routable geometry with classification, one-way flags and validated junction connectivity.
Point layers
POIs, assets, stops or events as validated point features with attributes.
Building and parcel footprints
Polygon layers with area, and height or storey counts where the source provides them.
Land use and land cover
Classified polygons for context, constraint mapping and suitability analysis.
Population and demographic grids
Statistical values disaggregated onto grids or apportioned to your custom zones.
Isochrones and catchments
Drive-time, transit-time and walking-time polygons generated on a road network.
Address datasets
Geocoded address points with match quality and confidence recorded per record.
Raster products
Density surfaces, interpolations and derived grids at a stated resolution.
Output formats
Delivered the way your stack expects
- GeoJSON
- EPSG:4326, right-hand-rule compliant, suitable for web mapping and APIs.
- Shapefile
- Delivered with .prj, .cpg and a field name mapping, since shapefiles truncate long names.
- GeoPackage
- Single-file, multi-layer delivery with preserved field types and no name limits.
- PostGIS
- Direct load with spatial indexes and geometry constraints already applied.
- CSV with WKT
- For tools that expect tabular input but still need geometry.
- Vector tiles
- MBTiles or PMTiles for fast rendering of large layers in a browser.
Use cases
What clients use it for
- Territory designBuild balanced sales or service territories from real boundaries and travel times.
- Catchment analysisDefine who can actually reach a location, on the road network rather than as the crow flies.
- Coverage and gap analysisFind where a network is thin by comparing service areas against population.
- Routing and logisticsPrepare a network dataset that a routing engine can actually traverse.
- Map productionSupply clean, styled layers to a design or engineering team.
Sample dataset
What you actually receive
Sample project data. Every layer states its coordinate reference system, its source type and its vintage, because mixing those silently is how spatial analysis goes wrong.
| Layer | Geometry | Features | CRS | Source type | Updated |
|---|---|---|---|---|---|
| admin_boundaries | Polygon | 412 | EPSG:4326 | Open government | 2026-06 |
| road_network | LineString | 128,940 | EPSG:4326 | Open mapping | 2026-07 |
| poi_points | Point | 23,517 | EPSG:4326 | Collected | 2026-08 |
| population_grid | Polygon | 9,864 | EPSG:3857 | Statistical agency | 2026-01 |
| drive_time_15min | Polygon | 48 | EPSG:4326 | Derived | 2026-08 |
How it works
Five steps, every project
- Step 01
Tell us what data you need
Describe the study area, the layers and the tools the data has to work in.
- Step 02
We define the data scope
We identify sources, licences, projections and the schema each layer will use.
- Step 03
We collect and process the data
Layers are acquired, reprojected, clipped to the study area and given consistent field names.
- Step 04
We validate the dataset
Geometry validity, topology, connectivity and attribute completeness are all checked.
- Step 05
We deliver the final result
A documented package with a layer manifest, CRS notes and licence attributions.
Quoted on feature counts, the number of layers, source complexity and validation depth. Tell us the layers and coverage you need and you get a fixed price against a written scope.
FAQ
Questions we get asked
What is geospatial data?
Any data with a location attached: a point, a line, a polygon or a grid cell tied to coordinates on the Earth. What makes it geospatial rather than tabular is that distance, containment and adjacency between records carry meaning.
Which coordinate systems do you work in?
We deliver in EPSG:4326 by default and reproject to whatever your workflow needs, including national grids and local projected systems. Any measurement of distance or area is done in an appropriate projected system, never in degrees.
Can you work with open data such as OpenStreetMap?
Yes, and we recommend it where it fits. We extract, clean and validate it for your study area, and we include the required attribution. Where open data has known gaps for your use case, we say so and propose how to fill them.
Can you build custom boundaries?
Yes. Trade areas, delivery zones, sales territories and catchments can be built from drive times, postcode groupings, population targets or rules you define, and delivered as clean, non-overlapping polygons.
Do you handle large datasets?
Yes. National road networks and multi-million-feature layers are handled with tiled processing and delivered as GeoPackage, PostGIS or vector tiles rather than shapefiles, which are not suited to that size.
Can you fix a dataset we already have?
Often the fastest option. We run a validity and topology audit, report what is wrong, and repair geometry, projections, field types and joins in place so your existing analysis keeps working.
More services
Often combined with
Street View Data
Large-scale street view imagery collection, processing and structured dataset delivery.
Learn MoreSemantic Segmentation
Pixel-level image analysis that turns imagery into counted, measured classes.
Learn MorePOI Data
Business and point-of-interest records with categories, coordinates and attributes.
Learn MoreKeep exploring
Where to go next
Related services
- GIS AnalysisSpatial analysis and geographic data processing, from overlays to network models.
- POI DataBusiness and point-of-interest records with categories, coordinates and attributes.
- Map VisualizationInteractive maps and data visualization built for clarity and fast loading.
- Data CollectionCustom data collection and structured datasets built around one specific question.
Related reading
- What Is Geospatial Data?Geospatial data is any data with a location attached. What makes it different is that distance, containment and adjacency between records carry meaning.
- CSV vs GeoJSON vs ShapefileFour formats, four sets of limitations. Choosing the wrong one loses data silently, which is the worst way to lose it.
Next step
Have a specific data requirement?
Tell us the geography, the fields and the cadence you need for geospatial data. You get a scoped plan, a sample and a fixed price before any work starts.