GIS and spatial analysis
GIS Analysis Services
Spatial analysis and geographic data processing, delivered as reproducible workflows rather than one-off outputs.
Overview
Spatial analysis that someone else can reproduce
A GIS result that exists only as an exported image is a dead end. Six months later nobody can say which version of the boundary file was used, whether the buffer was 500 metres or 500 feet, or why two runs disagree.
We deliver analysis as code: a documented, parameterised workflow built on PostGIS, GDAL, GeoPandas and QGIS, with inputs pinned and outputs regenerable. Change one parameter, re-run, and get a new answer you can trace.
That approach costs slightly more on the first project and considerably less on every one after it, because the second question is usually a variation on the first.
Real output
From operational GIS outputs to advanced spatial models
The first examples use one open dataset of 8,628 Manhattan businesses. The research figures that follow show the analytical range beyond point mapping: network accessibility, geostatistical interpolation, space syntax, significant clusters and trajectory mining.
Continuous density against aggregated density
Kernel density gives a smooth surface and finds the true peaks, but the bandwidth you pick decides how many peaks there are — so we state it. Hexagonal binning gives exact counts per equal-area cell, which is what you want when districts must be compared or joined to other data. Neither is more correct; they answer different questions.
Catchment analysis around candidate sites
A 400 m walking catchment around three candidate locations, with every POI inside each one counted and direct competitors counted separately. The three sites look similar on a map and are not: one carries more than twice the competition of another within the same radius.
Network accessibility changes with time and congestion
Isochrones model where a facility can actually be reached within a time threshold along a network. This published emergency-service study compares 10- and 8-minute coverage and separates peak from midnight conditions, revealing overlaps and service gaps that a circular buffer cannot represent.
Interpolation surfaces and space-syntax networks
Kriging turns sparse samples into a continuous prediction surface and reports uncertainty; space syntax treats streets as a graph and measures integration, choice and connectivity. One estimates an unknown field, the other explains how urban configuration channels movement.
Significant spatial clusters and movement trajectories
Hotspot analysis tests whether high or low values form statistically significant clusters and exposes how neighbourhood definitions change the result. Trajectory clustering groups complete movement paths, separates normal route families and flags anomalous behaviour rather than treating millions of GPS points as unrelated dots.
Operational examples: data © OpenStreetMap contributors under ODbL. Research figures are reproduced from the linked open-access papers under CC BY 4.0; each figure retains its original source and figure number.
Scope
Analysis we perform
Core GIS operations for clear questions, plus advanced spatial models for problems where distance, networks, uncertainty or time all matter.
Core spatial analysis
Overlay and spatial joins
Intersect, union, clip and attribute transfer to answer what lies inside, overlaps or connects to what.
Proximity and buffers
Distance bands, nearest-neighbour joins and influence zones measured in an appropriate projected CRS.
Accessibility and isochrones
Walking, driving or transit catchments, service coverage and population reached within a stated travel time.
Routing and OD matrices
Shortest paths, route optimisation and origin–destination travel-time matrices on real transport networks.
Terrain and raster analysis
Slope, aspect, viewshed, hydrology, zonal statistics and map algebra from elevation or imagery.
Geocoding and data engineering
Address matching, coordinate repair, topology checks, projection and repeatable multi-format conversion.
Advanced spatial modelling
Spatial interpolation
IDW, spline, ordinary or co-kriging, variograms, prediction surfaces and uncertainty maps from sampled points.
Spatial clustering and hotspots
Global and Local Moran’s I, Getis–Ord Gi*, DBSCAN and cluster/outlier analysis with significance testing.
Space syntax
Axial, segment and visibility-graph analysis using integration, choice and connectivity to model movement potential.
Trajectory data analysis
GPS/AIS track cleaning, map matching, stay-point detection, route clustering, flow extraction and anomaly detection.
Spatial econometrics
Spatial lag/error models, geographically weighted regression and diagnostics for spatial dependence.
Suitability and MCDA
Constraint screening and sensitivity-tested weighted scoring across environmental, market and network criteria.
Spatiotemporal change
Panel, raster and event comparisons that quantify where a pattern changed, when it changed and by how much.
Automated geoprocessing
Versioned Python, SQL or model workflows that rerun as new data arrives, with validation and audit logs built in.
Output formats
Delivered the way your stack expects
- Processed layers
- Result geometry as GeoPackage, GeoJSON, Shapefile or PostGIS tables.
- Tabular results
- Summary statistics by zone as CSV or Excel, ready for reporting.
- Maps
- Print-ready cartographic output with legends, scale bars and source notes.
- Workflow code
- The Python or SQL that produced the result, documented so you can re-run it.
- Methodology note
- Assumptions, parameters, data vintages and limitations, written for a reviewer.
Use cases
What clients use it for
- Service coverage analysisMeasure what share of the population is inside an acceptable travel time of a facility.
- Territory balancingDesign territories with comparable workload and contiguous geography.
- Site suitabilityCombine constraints and opportunity layers into a single scored surface.
- Routing and logisticsBuild travel-time matrices and coverage models for planning and costing.
- Environmental and planning studiesQuantify overlaps with protected areas, flood zones or land-use constraints.
- Spatial data auditsDiagnose why an existing analysis produces results nobody trusts.
Sample dataset
What you actually receive
Sample project data. Coverage is computed on the road network, so it reflects how far people can actually travel rather than a circle drawn on a map.
| Zone | Population | Covered | Coverage % | Nearest site (min) | Priority |
|---|---|---|---|---|---|
| Zone 01 · Central | 184,200 | 184,200 | 100.0 | 4.2 | Low |
| Zone 02 · North | 96,700 | 78,410 | 81.1 | 9.8 | Medium |
| Zone 03 · East | 112,400 | 61,320 | 54.6 | 14.1 | High |
| Zone 04 · South | 74,900 | 22,180 | 29.6 | 21.7 | High |
| Zone 05 · West | 58,300 | 51,940 | 89.1 | 7.4 | Low |
How it works
Five steps, every project
- Step 01
Tell us what data you need
Describe the spatial question and any layers you already hold.
- Step 02
We define the data scope
We specify the method, the parameters and how the result will be validated.
- Step 03
We collect and process the data
Inputs are prepared and the workflow is built as reproducible, parameterised code.
- Step 04
We validate the dataset
Results are tested for sensitivity to parameters and checked against known ground truth.
- Step 05
We deliver the final result
Layers, tables, maps, the workflow itself and a methodology note.
Quoted on complexity and data volume: how many layers the model needs, whether network analysis is involved and whether the workflow has to be repeatable. Tell us the decision it has to support and you get a fixed price first.
FAQ
Questions we get asked
Which GIS tools do you use?
PostGIS for analytical work at scale, Python with GeoPandas, Shapely and rasterio for processing, GDAL/OGR for conversion, and QGIS for cartography and review. We can deliver results that open cleanly in ArcGIS if that is your environment.
Can you work with our existing data?
Yes. We start with a validity and topology audit so problems surface before they contaminate the analysis, and we report anything we had to repair rather than fixing it silently.
Do you deliver the code as well as the result?
Yes, on request and at no extra cost. Scripts are documented and parameterised so your team can re-run them with new inputs. We think reproducibility is part of the deliverable, not an upsell.
Can you handle national or continental datasets?
Yes. Large jobs are processed in tiles with spatial indexing and, where appropriate, parallel execution. We size the approach to the data rather than pushing everything through a desktop tool.
How do you validate spatial results?
Geometry validity and topology checks first, then sensitivity testing across parameter values, then comparison against ground truth where any exists. Anything that cannot be validated is stated as an assumption in the methodology note.
Can you train our team to maintain the workflow?
Yes. A handover session plus documented code is included in most projects, and we can run longer training if your team intends to own the workflow from then on.
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
- Geospatial DataLocation, road, boundary and land-use datasets, cleaned and projected correctly.
- Heatmap AnalysisDensity, distribution and hotspot analysis that stands up to statistical scrutiny.
- Location IntelligenceLocation-based market, catchment and competitor analysis that ends in a recommendation.
- Map VisualizationInteractive maps and data visualization built for clarity and fast loading.
Related reading
- GIS Data Analysis for Market ResearchSurvey research tells you what people say. Spatial analysis tells you what is actually there. The two answer different halves of the same question.
- How to Build a Geospatial Data PipelineMost spatial pipelines work perfectly once. The design decisions that matter are the ones that keep them working on run twenty.
Next step
Have a specific data requirement?
Tell us the geography, the fields and the cadence you need for gis analysis. You get a scoped plan, a sample and a fixed price before any work starts.