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Go beyond simple map visualisations by integrating location data into your analysis. Answer spatial questions using the most comprehensive set of analytical methods and algorithms available. Use multiple data formats, sizes and scales. Perform site selection, find clusters, make predictions and quantify how patterns change over time. Create sophisticated statistical and machine learning models that unlock the full potential of your data.

Pattern detection


Dive deeper than traditional pattern mining, such as heat maps, know that patterns are real with spatial statistics. Use analysis tools that quantify the spatial patterns you see in a defensible, reproducible way. Apply data mining, machine learning, and statistics to find natural spatial and multivariate data clusters.

Before map: thousands of purple dots along a road network. After map: points now clustered by coloured groups to identify having similar attributes.

Space-time analytics


Understand the immediate and long-term impact of your decisions. Integrate the temporal aspect of your data alongside the spatial. Find out when and where things are happening. See how the social, economic, and environmental aspects of the landscape are changing over time and the influence it has on decisions made now and in the future. Use historic trends and additional information to uncover trends and patterns and make spatiotemporal forecasts.

Map showing space-time analytics (hex-bins displayed above ground and ranging from red to dark blue to indicate hot spots).

Predictive analytics


Make accurate predictions using powerful statistical and machine learning methods, as well as specialised spatial modelling approaches. Model interaction, flow and movement in space and time. Create prediction surfaces using sophisticated geostatistical techniques. Examine and quantify data relationships and forecast spatial outcomes. 

Moving gif displaying points at differing depths in an underwater trench.

Suitability modeling and location optimisation


Make the right decisions. Use spatial tools and algorithms to find the best location, allocate resources effectively, meet demand and minimise cost. Combine domain expertise and organisational practices to model suitability and optimise location decisions.  

Map showing the analysis of land parcels and calculating the suitability for wind farms in Arizona.

Route planning and logistics


Graduate from simple point-to-point routing. Find the path of least resistance, understand the cost of getting from one location to another and plan routes for an entire fleet. Use ready-to-use networks or build your own using custom data. Calculate travel times, locate facilities and solve other complex network-related problems. 

Moving gif showing route analysis by tracking deliveries that are following the best calculated routes across Los Angeles.

Terrain analysis


Understand the earth’s topographic features. Model and visualise the earth’s surface as digital 2D and 3D models to calculate slope and curvature, delineate watersheds and compute visibility. Use results to perform analysis and support decision making for a variety of applications.  

Moving gif showing where canal flooding takes place over time and highlighting which areas are at risk.

Scale up your analysis


Improve efficiency and reduce work time. Harness distributed computing to scale up your analysis and process massive data collections. Identify data patterns that were previously hidden in noise. Analyse suitability, detect change and model the earth’s surface at scale. Use spatial machine learning to find relationships and predict future events.    

Map displaying 3D stacked cubes from turquoise to dark purple across New York city indicating volume.

Case Study

Using Drones to Protect Vulnerable Species


The RSPB use the ArcGIS platform to process, analyse and share imagery captured by drones to help improve habitats and protect endangered bird species

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