Layered map composition: base grid, network, density and points
Overview
The map has to answer the question at a glance
Most business maps fail for the same three reasons: too many layers competing at once, a colour scheme that implies a pattern the data does not support, and a payload heavy enough that the map has already lost the reader before it renders.
We design for the question. One primary layer carries the message, context recedes, and the classification is chosen deliberately rather than accepting a default that puts the break in a flattering place.
Performance is treated as a design constraint. Large layers become vector tiles, heavy interactive maps sit behind a static preview until the reader asks for them, and nothing blocks the rest of the page from rendering.
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.
Layered map composition: base grid, network, density and points
Scope
What we build
From a single embedded map to a full analytical interface.
Interactive web maps
Pan, zoom, filter and inspect, built on MapLibre, Leaflet or deck.gl depending on data volume.
Choropleth maps
Value-by-area maps with classification chosen and justified, not left to a default.
Point and cluster maps
Large point sets rendered legibly through clustering, binning or tiled rendering.
Heatmap layers
Density surfaces styled with a perceptually uniform ramp and an honest legend.
Flow and route maps
Origin–destination and movement visualisation without the spaghetti effect.
Time-enabled maps
Animated or stepped views for change over time, with a scrub control.
Dashboards
Maps combined with charts and tables that filter together from one selection.
Vector tiles
MBTiles or PMTiles generation so million-feature layers stay fast in a browser.
Print cartography
High-resolution PDF and SVG for reports, planning documents and presentations.
Embeddable components
React components that drop into your existing site or product.
Output formats
Delivered the way your stack expects
Deployed web map
Hosted on your infrastructure or ours, with source and build instructions handed over.
React component
A typed, documented component you can drop into an existing application.
Vector tiles
PMTiles or MBTiles plus the style specification used to render them.
Static exports
PNG, SVG and PDF at print resolution with legends and attribution.
Style specification
The map style as data, so it can be reused and version-controlled.
Sample project data. We set a transfer budget per layer before building, because performance decisions are much cheaper to make at design time.
Sample project · Layer performance budget for an interactive map
Layer
Features
Delivery
Transfer size
First paint
Basemap
—
Vector tiles
180 KB
0.4 s
Boundaries
412
GeoJSON
62 KB
0.5 s
POI points
23,517
PMTiles
310 KB
0.7 s
Heatmap surface
—
Raster tiles
240 KB
0.9 s
Labels
1,840
Vector tiles
48 KB
0.9 s
Delivered work
This service on a real project
Sample projects built on this service, with the numbers they produced and what each one settled.
Heatmap AnalysisGIS AnalysisMap Visualization
Urban Heatmap Data Analysis
Turning a scattered point dataset into a normalised density surface that separates real activity clusters from population artefacts.
Input records
48,600
Records corrected
9.1%
Hotspots confirmed
2 of 5
What it showed
Central had by far the largest raw count and by far the largest visual hotspot, but ranked third on activity per resident. The original map had been describing population distribution, not activity.
Harbourside, which barely registered on the unnormalised map, was the strongest genuine hotspot at 99% confidence. It has a small residential population and a high concentration of activity, precisely the pattern raw-count heatmaps hide.
Measuring the physical character of streets at scale using semantic segmentation, object detection and colour analysis on street-level imagery.
Network analysed
310 km
Images processed
24,800
Indicators per segment
7
What it showed
Green view index across the network ranged from 4.1% to 38.9%, and the distribution followed district boundaries far more closely than the team expected. Two adjacent districts differed by more than twenty points with no change in street type.
Enclosure ratio and green view were only weakly related. Several streets scored well on greenery while feeling open and exposed, which matters because those two qualities are often treated as one in streetscape policy.
Share the data and the single question the map has to answer for its audience.
Step 02
We define the data scope
We agree layers, interactions, performance budget and accessibility requirements.
Step 03
We collect and process the data
Data is prepared, simplified appropriately and tiled where volume demands it.
Step 04
We validate the dataset
We test on mobile, on throttled connections, with keyboard navigation and with a screen reader.
Step 05
We deliver the final result
Deployed map or component, plus source, styles and documentation.
Quoted on layer count, how much interactivity is needed and the volume of data behind the map. Tell us where it has to live — a report, a dashboard or your own product — and you get a fixed price against a written scope.
FAQ
Questions we get asked
Which mapping libraries do you use?
MapLibre GL for most interactive work, Leaflet when a lighter footprint matters more than styling control, deck.gl for very large point and flow datasets, and D3 or plain SVG for bespoke non-slippy maps. The choice follows the data volume and the interaction, not habit.
Will the map slow down our website?
Not if it is built properly. Map libraries load only when a reader chooses to interact, with a static preview shown first. Layers are tiled and budgeted, so a heavy map never blocks the rest of the page from rendering.
Can you match our brand?
Yes. We build the basemap style from your palette and typography, and we check colour choices for contrast and for colour-vision deficiency, which most brand palettes have never been tested against.
Do you handle very large datasets?
Yes. Beyond roughly fifty thousand features, we move to vector tiles or GPU rendering rather than pushing GeoJSON to the browser. That keeps interaction smooth on a laptop and usable on a phone.
Are the maps accessible?
We provide keyboard navigation, meaningful text alternatives, a data table view of the same information, and colour ramps that remain distinguishable for common colour-vision deficiencies. A map that only works with a mouse and perfect colour vision is an incomplete deliverable.
Can you hand the project over to our developers?
Yes. Deliverables include source code, the style specification, build instructions and a walkthrough session. There is no runtime dependency on us.
Tell us the geography, the fields and the cadence you need for map visualization. You get a scoped plan, a sample and a fixed price before any work starts.