Heatmap Visualization
spot patterns, density & hotspots in spatial data
GLOBEIR builds custom heatmap visualizations that reveal density patterns, hotspots, and clusters in any location-based dataset — from customer concentration and crime patterns to disease outbreaks and footfall analysis.
What we deliver
Kernel Density Estimation (KDE)
Mathematically rigorous KDE heatmaps with adjustable bandwidth, kernel functions, and edge correction for accurate density representation.
Hotspot Detection (Getis-Ord Gi*)
Statistical hotspot identification using Getis-Ord Gi*, Moran's I, and LISA — reveal statistically significant clusters in your data.
Interactive Heatmap Dashboards
Pan, zoom, filter by date/category, time-slider playback, and side-by-side comparison — all in browser, no downloads needed.
Temporal Heatmaps
Animated heatmaps showing how density changes over time — perfect for traffic patterns, event monitoring, or seasonal trends.
Multi-Variable Bivariate Heatmaps
Combine two variables (e.g., density & intensity) in a single visualization with bivariate colour schemes.
Export & Reporting
High-DPI PNG/PDF export for reports, GeoJSON output for further analysis, and embeddable iframe for websites.
Real-world applications
Trusted across industries to solve location-based challenges with precision and scale.
Powered by modern technology
Mapbox GL Heatmap Layer
Leaflet.heat
Deck.gl HexagonLayer
Python (scipy KDE)
PySAL (PySAL ESDA)
GeoPandas + Matplotlib
ArcGIS Spatial Analyst
R (spatstat, KernSmooth)
Frequently asked questions
What is a heatmap in GIS?
A GIS heatmap is a graphical representation that shows the density or intensity of geographic data using colour gradients — typically warmer colours (red/orange) for high density and cooler colours (blue/green) for low density.
What kind of data can be turned into a heatmap?
Any point-based location data: customer addresses, GPS pings, crime incidents, accidents, ATM transactions, social media check-ins, sensor readings, wildlife sightings, disease cases — anything with latitude/longitude coordinates.
What is the difference between a heatmap and a hotspot map?
A heatmap shows density patterns visually using colour gradients. A hotspot map uses statistical tests (like Getis-Ord Gi*) to identify locations where high values cluster together significantly more than random — providing scientific confidence in the patterns.
Can heatmaps be made for time-series data?
Yes. We build animated time-slider heatmaps that show how density patterns change over hours, days, months, or years — perfect for tracking traffic patterns, disease spread, or seasonal customer behaviour.
How accurate are heatmaps?
Heatmap accuracy depends on input data quality and kernel bandwidth selection. We use rigorous bandwidth optimization (Silverman's rule, cross-validation) and statistical validation to ensure results are defensible.
Can you integrate heatmaps into our existing dashboard?
Yes. We deliver heatmaps as embeddable web components, REST APIs, or as integrated views within Tableau, Power BI, ArcGIS Dashboards, or custom-built portals.
Turn your location data into insights
From a one-off heatmap to a real-time density-monitoring dashboard — we design the right visualization for your decisions.