Maptitude Cluster Mapping Software

Maptitude Online, a GIS mapping software, includes a powerful cluster map feature that automatically creates clusters for your data. With Maptitude cluster maps, you can visualize patterns that would be hard to spot on a normal pin map. The software dynamically recalculates clusters as you navigate the map, ensuring that you always see an optimal grouping of points at each zoom level.

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What are Maptitude Online Cluster Maps?

Cluster maps in Maptitude help you make sense of densely plotted locations, whether you're analyzing customers, facilities, or any large set of points on a map, all while maintaining clarity and context.

Cluster maps:

Are interactive thematic maps
Group many nearby points into a single symbol (or "cluster")
Simplify complex geographic data

Instead of displaying hundreds or thousands of overlapping markers, a cluster map consolidates points based on proximity and labels each cluster with the number of points it contains. This makes it much easier to interpret dense location data at a glance, because you immediately see where concentrations of data are highest without losing the ability to drill down for details as you zoom in.

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Try an Interactive Cluster Map

This interactive cluster map shows the locations of earthquakes of magnitude 2.0 or higher

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Key Features and Benefits of Cluster Maps

Simplified Visuals for Dense Data:
Cluster maps reduce map clutter by aggregating points that are close together into one marker. This simplification makes patterns in heavy datasets immediately visible. For example, instead of hundreds of overlapping dots in a city, you might see a single cluster labeled "150," instantly conveying that 150 data points are in that area. This approach makes it easier to spot trends and outliers without manually sifting through noise.
Dynamic Clustering on Zoom:
Maptitude Online cluster maps are fully dynamic and scalable. As you zoom in or out, clusters automatically recalibrate, zooming in reveals smaller clusters or individual points, while zooming out combines points into larger clusters. This scalable analysis means you can seamlessly transition from a high-level overview to a detailed view, all on one map. The map clusters update in real time, so you're always viewing an appropriate level of detail for the current map scale.
Quantitative Insight at a Glance:
Each cluster symbol is labeled with a number to indicate how many points it represents. In addition, the size or color of cluster symbols can reflect the quantity or magnitude of data in that cluster, providing instant visual cues about density. For instance, a larger or more prominently colored cluster might indicate a higher concentration of points (or a higher total value, if you choose to weight clusters by an attribute like sales volume). This quantitative representation helps you quickly identify hotspots and compare different regions.
Category Breakdown with Pie Cluster Symbols:
Maptitude also supports clustered pie chart themes, allowing you to visualize composition within clusters. If your points have categories or multiple data fields (e.g. customer types or product mix), you can choose a pie chart theme and enable chart clustering. The map will then show pie chart clusters, each pie represents the grouped data, with slices for each category, and is labeled with the total count in that cluster. This feature is especially useful for understanding the makeup of clusters (for example, a cluster of sales might be broken down by product category in the pie chart). It combines the benefits of clustering with multi-variable charting.
Interactive Exploration:
Cluster maps encourage users to interact. You can click on or hover over a cluster to get more details (for example, to see a list of included locations), or simply zoom in for a closer look. Because clusters are dynamically generated, they effectively guide you to areas of interest, when you see a cluster with a high number, you might zoom in there to investigate further. This interactive drill-down capability turns your map into an exploratory tool, where broad patterns lead you to finer analysis. In an interactive setting, cluster maps excel at helping users navigate large datasets.
Built-In Demographic Context:
Maptitude comes with extensive demographic data and map layers that you can overlay under or alongside your clusters. This means you can view your clustered data points in context, for example, seeing customer clusters against a background of population density or income levels by region. By overlaying boundaries (like ZIP Codes or territories) with demographic shading, you gain insights such as "Are my customer clusters located in high-income areas?" or "This service request cluster overlaps with a densely populated region." Maptitude makes it easy to add these layers, and even calculate demographic summaries for the areas around your clusters. This integration of cluster maps with demographic and geographic context helps you not only see where things are happening, but also understand why and who is in those areas.

Cluster theme with underlying demographics on ZIP Codes

By layering a cluster theme of earthquakes with population data on ZIP Codes, you can see that West Texas earthquakes are centered away from high population areas

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Industry Applications of Cluster Maps

Cluster mapping is a versatile technique that delivers value in many fields. Here are some industry applications and examples of how cluster maps can be used:

Business Intelligence & Sales:
Companies with large customer datasets or sales records use cluster maps to identify regional concentrations of customers and prospects. For instance, a business can map all its customer addresses and use a cluster map to see which metropolitan areas have the highest customer counts. This helps with targeted marketing and sales strategies, sales teams can focus on "hotspot" regions indicated by large clusters of customers. Cluster maps also assist in spotting underserved areas (places with few or no clusters) for business expansion.
Retail Planning:
In retail, cluster maps help visualize where stores, shoppers, or competitors are clustered. A retailer might plot all its store locations and use a cluster map to see clusters of stores in high-density markets, ensuring they haven't over-saturated an area. Likewise, mapping all customer purchase locations can reveal clusters of high demand, guiding decisions on where to open a new store or target a local promotion. By showing overlapping trade areas or clusters of transactions, retail planners can optimize store placement and inventory distribution.
Logistics & Service Delivery:
Delivery companies and service providers often deal with thousands of addresses (for deliveries, pickups, service calls, etc.). Cluster maps can highlight groups of stops or clients in close proximity. For example, a logistics manager might see that deliveries naturally form a cluster in a particular suburb, indicating an opportunity to assign those to the same route or depot. By identifying clusters of delivery points, companies can plan more efficient routes (servicing one cluster at a time) and even decide where to position warehouses or fulfillment centers to best serve those clusters. This leads to improved route optimization and resource allocation.
Public Sector & Safety:
Government agencies and public safety officials use cluster maps to analyze incidents and resource needs. For instance, law enforcement can create a cluster map of crime incidents or 911 calls to see where incidents are concentrated. Large clusters might indicate crime hotspots or neighborhoods that need increased patrols. City officials could cluster citizen service requests (like pothole reports or permits) to identify areas with higher demand for city services. In emergency management, cluster maps of incident reports (fires, medical calls, etc.) help in strategizing where to station emergency response teams. By visualizing these clusters, the public sector can allocate police, fire, medical, or maintenance resources more effectively to the communities that need them most.
Healthcare & Epidemiology:
In healthcare analysis, cluster maps are valuable for mapping patient data, disease outbreaks, or healthcare facilities. Epidemiologists can plot disease case locations and use cluster maps to quickly spot outbreak clusters, revealing areas of high infection that might warrant targeted interventions. Healthcare networks might map all their clinics or hospital admissions; clustering shows which regions have the most patients seeking care. This can highlight gaps in coverage (areas with many patients but no nearby clinic) or help in planning new facilities. Similarly, public health officials might cluster maps of vaccination rates or chronic illness cases to identify communities that need outreach or additional services. The cluster map provides an intuitive view of health data distribution, supporting data-driven decisions in health policy and resource deployment.

"We believe Maptitude is a promising suite of capabilities that would likely yield the greatest opportunities for scalable clustering analysis. We believe the capabilities of Maptitude are promising when compared to Microsoft Excel–based mathematical clustering because Maptitude provides greater information integration, including the ability to layer information.”

Austin Clark & Corey M. Arruda
Naval Postgraduate School
Monterey, California

“Maptitude is user friendly and economical. The software makes it easy to show key components in your data. It pinpoints the location and is visually appealing. I used it for a cancer cluster investigation and also use it in another industry to show sales.”

Debbie Pullen
Data Research Analyst, Kristen Renee Foundation
Tampa, Florida

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How to Create a Cluster Map in Maptitude Online

Creating a cluster map in Maptitude is straightforward. You can turn a raw dataset of locations into an insightful cluster visualization in just a few steps:

Map Your Data Points:
Start by importing or plotting your location data in Maptitude. You can use the built-in Create-a-Map Wizard or add data to an existing map. For example, load a spreadsheet of addresses (customers, stores, incident locations, etc.), Maptitude will geocode the addresses and display them as points on the map.
Apply the Cluster Theme:
Once your points are on the map, it only takes a few clicks to create a cluster map. In the map's Display Manager or layer settings, click "Add Theme" and choose Cluster Theme for your point layer. You don't even need to pick a field, clustering is based on location only. After you click Finish, Maptitude will automatically group densely located points into clusters and label each cluster with the number of points it contains. Immediately, your map will transform from a scattering of individual dots to a cleaner view with numbered cluster symbols.
Explore the Clusters:
With the cluster theme applied, take advantage of the interactive map to explore. Zoom in to break clusters apart into smaller clusters or individual data points. Zoom out to see broader patterns as points aggregate into larger clusters. You can pan around to examine different regions, the clusters will update on the fly. Use the dynamic nature of cluster maps to dive deeper: large cluster over a city? Zoom in to see which neighborhoods contribute to it. Sparse coverage in an area? Pan around or zoom out to see if those points form a cluster.
Add Context (Optional):
To get more insight from your cluster map, you can overlay additional data. For instance, add a boundary layer such as ZIP Codes, counties, or sales territories, and include some demographic or statistical data for those areas. Maptitude lets you shade these areas (using a color theme or heat map) or label them with values. By doing this, you can observe how your clusters relate to external factors (e.g., do customer clusters align with high-population areas or high-income ZIP Codes?). You could also add other point layers (like competitor locations or service centers) to see them in relation to your clusters. Maptitude layering and theming capabilities are flexible, so you can combine cluster maps with other map themes (heat maps, pie charts, territory boundaries, etc.) for a richer analysis.

That's it, with these steps, you have a cluster map! You can now save your map, export it as an image for a report, or even share it interactively using Maptitude Online. The result is a clean, informative visualization that conveys both the big picture and the fine details of your location data.

Try Cluster Maps in Maptitude

Cluster mapping is a powerful capability, and the best way to appreciate it is to try it with your own data. Maptitude offers a free 1-month trial of the full software, so you can experiment with cluster maps firsthand (no credit card required). We encourage you to sign up for the free trial and use this guide to create a cluster map step-by-step.

If you'd like a guided tour, you can request a live demo from the Maptitude team, we'll be happy to show you how cluster maps and other features can meet your needs. Whether you're dealing with sales data, epidemiological data, or service locations, cluster maps in Maptitude will help you turn that raw data into actionable insights. Get started today and see how clustering can reveal the story in your map data!

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Frequently Asked Questions about Cluster Maps:

What is a cluster map?

A cluster map is a type of map that groups close-together points into a single symbol for easier visualization. In a cluster map (sometimes called a bubble map), each cluster represents a set of individual locations that are near each other. The cluster is usually drawn as a circle (or bubble) and labeled with a number indicating how many points it contains. This technique helps prevent overlapping markers on a map. For example, if you have 500 customer addresses in one city, a cluster map might show a single circle labeled "500" rather than 500 tiny dots on top of each other. As you zoom into that city, the single cluster would gradually break apart into smaller clusters or individual point markers, revealing more detail. In summary, a cluster map allows you to see patterns in dense data by consolidating points and is especially useful when mapping large datasets (hundreds or thousands of locations).

How does Maptitude Online create map clusters?

Maptitude creates map clusters automatically using its built-in Cluster Theme functionality. When you apply the Cluster Theme to a point layer, Maptitude examines the geographic distribution of your data and groups points that are within a certain proximity into clusters. Each cluster is displayed as a colored circle (with semi-transparent sizing) and a label showing the number of points in that cluster. The clustering in Maptitude is dynamic: it recalculates as the map view changes. Technically, as you zoom or pan, the software adjusts which points are grouped together based on the current scale, so the clusters always reflect an appropriate grouping for the view. You don't need to set any parameters for distance or number of clusters, Maptitude algorithms handle it. The result is an interactive map where nearby points are replaced by a cluster symbol labeled with their count, giving you an instant sense of density. If you need to see the individual points, you can just zoom in and Maptitude will dissolve the cluster into the actual locations. This on-the-fly clustering makes it very convenient to visualize large datasets without manual intervention.

How is a cluster map different from a heat map?

Both cluster maps and heat maps are techniques to visualize dense point data, but they work in different ways and are used for different purposes. A cluster map uses discrete symbols (clusters) with counts to represent groups of points. In contrast, a heat map (or density map) creates a continuous color-coded surface to indicate the intensity of points in an area.

Here are some key differences:

Visualization style: Cluster maps show distinct circles with numbers, whereas heat maps show smooth color gradients (for example, blue-to-red shades) over areas. A heat map might color an area red if many points are nearby, versus blue for fewer points. There are no counts or discrete groupings shown in a basic heat map, just intensity of color.
Interpretation: In a cluster map, you can see exact counts per cluster (e.g., "20 incidents in this cluster"). A heat map is more about visual density, you infer relative intensity by color shade, but you don't get an exact number unless you use a legend or query the data. Heat maps are great for spotting general hotspots and gradients, while cluster maps are great for keeping track of actual totals and precise cluster locations.
Interactivity: Cluster maps are inherently interactive with zoom (clusters split apart as you zoom in). Heat maps typically remain the same when zooming (they just focus on a smaller area), although you can change their radius or intensity settings.
Use cases: Use a cluster map when you want to maintain a link to actual data points and counts, for example, showing how many customers are in each city area, or how many incidents in each neighborhood, with the ability to drill down. Use a heat map when you want to emphasize the continuous spread or influence of points, for example, seeing the gradient of event intensity or customer density across a region, without needing exact figures per spot.

In practice, Maptitude supports both methods. You could even use them together: for example, a heat map underlay to show general density, with cluster markers on top showing specific counts in key locations. Both are useful, it just depends on whether you need precise cluster information (choose cluster map) or an overall smooth density visualization (choose heat map).