Location Intelligence with Isochrones: A Complete Guide

What Are Isochrones and Why They Matter for Location Intelligence

Isochrones are polygons showing areas reachable within specific travel times from a location. They help businesses make data-driven decisions about site selection, risk assessment, and resource allocation by accounting for actual road networks and travel constraints—unlike simple radius-based approaches.

You can now accelerate, scale, and improve the effectiveness of risk-based and location-based decisions using new isochrone functions for SQL and Python in Wherobots. These functions are specifically designed to generate isochrones for location intelligence, enabling data teams to make data-driven decisions with greater accuracy and speed. Additionally we are announcing a free and open source isochrones-extended Overture Places dataset, to make it easy for you to make data-driven risk assessments and location decisions based on travel time at scale.

Click here to launch this interactive notebook

Launch Notebook

ST Functions for Isochrones
The new functions (ST_Isochrones, ST_Isochrone) are purpose-built for generating isochrones for analytical scenarios at scale and high speed. Running on Wherobots’ cloud-parallel compute, they are capable of generating tens of thousands of travel isochrones per minute, from or to points of interest, at a very low cost. These functions are best used inline with Wherobots’ 300+ SQL and Python spatial functions operating on various data types, enabling the generation of isochrones for location intelligence at scale. Most notably are the Wherobots’ GeoStats functions that identify geospatial data clusters and hot spots. When combined, these capabilities make it easy for any data team to streamline risk and location-finding decisions on a continental scale. We’ll show you how in a US-wide fire department site selection analysis later in this blog.

---Generating 30 min travel isochrones using Overture Places
SELECT *, ST_Isochrone(geometry, 30, 'car', false) AS isochrone
FROM wherobots_open_data.overture_maps_foundation.places_place
WHERE ST_Intersects(geometry, ST_GeomFromWKT('<Insert WKT>'))

Overture Places with Isochrones
We dogfooded ST_Isochrones in WherobotsDB to create a free and open version of the Overture Places dataset extended with 53.2 million precomputed travel isochrones for 5, 10, 15 and 20 minute car travel times, for all 13.3 million US places in the dataset. The isochrone extended Overture Places dataset is now hosted in the Wherobots Spatial Catalog for anyone to use under the CDLA Permissive 2.0 license. This dataset makes it very easy for anyone to create location intelligence from isochrones, and is ready for experimentation and production use.

---Joining isochrones to buildings in Overture
SELECT *
FROM wherobots_open_data.overture_maps_foundation.buildings_building AS buildings
JOIN wherobots_pro_data.overture_maps_foundation.overture_places_with_isochrones AS isochrones
ON ST_Intersects(buildings.geometry, isochrones.geometry

Getting Started
The new isochrone functions along with the Overture Places dataset extension are offered at no additional cost in the Professional Edition of Wherobots. You can use these features after subscribing to the Wherobots Professional Edition through the AWS Marketplace.

How Travel Isochrones Work

Travel isochrones are polygons that define how far something can travel from or to a given location within a specified time and travel mode. This forms an area also known as reach. Unlike traditional radius or point-to-point based heuristics that ignore real-world conditions, isochrones can account for the actual travel constraints of road networks, transportation modes, and even congestion.

Why Data-Driven Location Decisions Beat Intuition

Where you invest has a long-term impact on a location’s overall profitability. The mantra of “location, location, location” is absolutely still alive. But unlike 20 years ago, you now have the ability to let off-the-shelf data and modern geospatial engines like Wherobots tell you where the ideal physical locations are to invest in, across hundreds of thousands of options, using a few lines of SQL.

Isochrones help you forecast network travel costs that cling to locations over time, and can burden a location’s profitability. These can be actual – like fuel, electricity, and labor expenses, or they are costs that weigh on your ability to sell, reflect risk, and take share of a market opportunity. As an example, if you are looking to expand your business via a new location, know where clusters of your target customers are or may be, and where your competitors are, you’ll naturally gravitate to picking locations that minimize travel costs for these customers and choose areas where you know you can be competitive. If you have hundreds or thousands of customer clusters to possibly serve, you’ll want to use Wherobots to help you find the right locations to invest in, and create a competitive advantage via location intelligence.

6 Industries Using Isochrone Analysis

No matter your industry, location and speed determines your market reach. The following are typical industries and use cases better enabled via isochrones.

• Retail: Identify prime brick and mortar locations with high customer density, low travel costs, and minimal competition.
• Logistics & Supply Chain: Optimize distribution network design and reduce delivery costs.
• Insurance & Real Estate: Actuarial analyses assess emergency coverage to influence policy pricing and property valuation.
• Service Coverage: Identify strategic locations for healthcare and emergency services based on demographic accessibility.
• Advertising and Marketing: Identify prime locations for billboards, advertising campaigns, while identifying underserved audiences to reach.  
• Infrastructure: Select the ideal location for capital investments that optimize for long-term results.

Case Study: Nationwide Fire Department Site Selection in 30 Minutes

The goal of this example is to show you how easy it is to complete a nation-scale site selection analysis using Wherobots. In this example, we will narrow down logical options for new fire departments across the entire US, based on clusters of higher risk places. A place was arbitrarily deemed “high risk” if it took more than 30 minutes for a fire truck to reach the place based on the location of the nearest fire department. For a total compute cost of less than $110, and in less than 30 minutes of compute time, using Wherobots you can answer and automate nationwide questions on-demand, like “where is risk” and “where should my [investment or asset] be located in a country?”

Site Selection Example

In this example we used an Wherobots XL runtime, and started by computing 30 minute travel isochrones for all 29,777 US fire departments in the original Overture Places dataset in 20 minutes. This step cost $98.

isochrones = sedona.sql(f'''
    SELECT *, ST_Isochrone(geometry, 30, 'car', false) AS isochrone
    FROM wherobots_open_data.overture_maps_foundation.places_place 
    WHERE categories.primary = 'fire_department' 
    AND ST_Intersects(geometry, ST_GeomFromWKT('<Insert USA WKT>'))
''')

Then we joined 13.3 million places to the 30 min isochrones (one for each 29,777 fire department) to classify places as high risk when fire trucks cannot reach them within 30 min of travel time. This join took 51 seconds to complete using the following query.

fire_risk = sedona.sql('''
    SELECT places.*, iso.isochrone
    FROM wherobots_open_data.overture_maps_foundation.places_place as places
    LEFT JOIN isochrones AS iso
      ON ST_Intersects(iso.isochrone, places.geometry)
    WHERE iso.isochrone IS NULL
    AND ST_Intersects(places.geometry, ST_GeomFromWKT('<Insert USA WKT>'))
''')

Finally, we applied the popular clustering algorithm DBSCAN, available in Wherobots’ GeoStats, to identify 688 high risk clusters of places. The clustering step took 90 seconds to complete. In a real example, you may want to rank these clusters, based on some characteristic like total asset value in a cluster, to finalize your site selection analysis.

clustered_fire_risk = sedona.sql('''
    SELECT *, ST_DBSCAN(geometry, 10000, 25, true) AS dbscan_result
    FROM fire_risk
''')

The join and clustering step took ~140 seconds, for a cost of $11.41. In total, the nation-wide analysis cost less than $110, took less than 30 minutes to complete, and required 12 lines of SQL.

Alternatively, if you utilize the new Overture Places with Isochrones dataset instead of generating isochrones in the query, the total query time in this example was 10 minutes, for a total cost of $37 (~66% less). You can run the same analysis using alternative datasets too, such as Foursquare’s Places dataset.

Here’s a visual showing the clusters of potentially “high risk” places from a perspective of fire response coverage. You can also explore these results in our online PM tile viewer.

You can start with a smaller scale, lower cost version of this example yourself using the “Isochrones” notebook in Wherobots, or explore how easy it is offline in GitHub. You can easily scale it up to fit your needs, and automate these results using Wherobots Job Runs. 

Traditional Isochrone Methods vs. Modern Solutions

Until now, if you wanted to perform a site selection analysis like the one above, you’d need to generate thousands of isochrones using rate limited APIs like those offered by Esri and others. Isochrone APIs like these are designed to generate isochrones for online, interactive applications like a map, but by nature they are not designed for integrating isochrones into offline decision-making processes at-scale. For example, it would take many hours just to generate isochrones in the previous fire response example using these APIs vs 20 minutes in Wherobots. Developers may also need to push these results from isochrone APIs into another system that may not be as optimized for spatial analytics, adding on undifferentiated expense. 

Pre-Computed Isochrones Dataset for Overture Places

The precomputed isochrones dataset for Overture Places is available in the Wherobots Pro Spatial Catalog, which is available to Professional Edition subscribers.

wherobots_pro_data.overture_maps_foundation.overture_places_with_isochrones

The table contains a US-wide version of the Overture Places dataset extended with four outbound car travel isochrone geometries per place.

Schema Updates:

The following columns are in addition to the base Overture Places schema, release version 2025-03-19.0

All geometries were generated using the ST_Isochrones function with inbound = false and mobility_type = ‘car’.

Dataset Specifications:

• Geographic coverage: All 50 US states and territories
• Number of places: 13.3 Million
• Total isochrones generated: 52.3 Million
• Mode of travel: car
• Direction: outbound (from each place)
• Time thresholds: 5, 10, 15 and 20 minutes
• CRS: EPSG:4326 (WGS84)

Costs
Like all other Wherobots functions, when you use ST_Isochrones you pay for the serverless computation you use, measured by spatial units. And its capability scales with the runtime size you choose. Use is not limited by requests, and your costs will scale with the computational complexity of the isochrones you are requesting. As previously mentioned, the Wherobots version of the Overture Places dataset is free to use. 

Key Takeaways

• Isochrones show reachable areas based on actual travel time, not simple distance
• Wherobots can generate tens of thousands of isochrones per minute
• Free Overture Places dataset includes 53.2M pre-computed isochrones for 13.3M US locations
• Use cases span retail, logistics, insurance, healthcare, and emergency services
• Complete US-wide site selection analysis costs under $110 and takes 30 minutes

How to Get Started to Generate Isochrones

1. Start enhancing your location intelligence by subscribing to the Professional Edition of Wherobots via the AWS Marketplace. This gives you access to the new version of the Overture Places dataset and the ST Isochrones function.
2. After subscribing, create and open a runtime. Then open the “Isochrones” example notebook and run all cells. You can explore the Isochrone functions in more detail in the product documentation.
3. We welcome feedback on the functions and dataset. Please reach out to product@wherobots.com to share what you need and what you build. We are eager to learn how to improve future enhancements.