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Using GIS to Identify the Best Location for Real Estate Investment

by Eric van Rees on Mar 9, 2021

Real estate investment professionals use travel time analysis to understand how properties are located relative to transport links and local amenities such as schools and supermarkets. These factors are important when choosing where to invest in real estate — and being able to analyse the proximity of different amenities to a property’s location is crucial to understanding its market value.

This tutorial shows GIS users how to use travel time analysis to identify the best location to invest in real estate and how this data can be used to evaluate property value.

We’ll use the concept of “15-minute cities”, which refers to areas inside traditional cities where housing, offices, restaurants, parks, hospitals and cultural venues can be accessed within a 15-minute time limit. We’ll analyse our test locations to see if they meet these accessibility requirements.

What you’ll learn:
  1. Using travel time data for real estate site selection
  2. Evaluating location accessibility by different transport modes
  3. The 15-minute city: which location has the most potential?
  4. Analysing the best location to invest in real estate
  5. Build your own real estate site selection analysis
What you'll need:

Using travel time data for real estate site selection

Our use case for this tutorial is a real estate consultancy who is helping an investor decide where to invest in property from a shortlist of areas in the UK. Using the TravelTime add-in for ArcGIS and ArcGIS Pro, we’ll show the steps needed to analyse how accessible the different locations are by different transport modes.

GIS is a great tool for real estate analysis: first, large quantities of addresses can be mapped out in a few clicks of a button, saving analysts time and money. Second, using the TravelTime add-in for ArcGIS Pro gives a realistic overview of accessibility, as it replicates the way people travel in cities: using multiple transport modalities such as walking, cycling and using public transport. This creates realistic and reliable results that property investors can rely on.

We’ll start our GIS real estate analysis by generating three random UK postal codes with a matching address using this website. We are interested in studying the area around these addresses and will use these addresses as the central points for the travel time analysis. The website generated the following street addresses, which are saved in a .CSV file with a header that indicates the multiple columns as follows:

Address, City, Country

46 Old Hillview Place, Cowdenbeath, UK

74 St Cuthberts Place, Birmingham, UK

75 St Brycedale Avenue, Kirkcaldy, UK

We can now geocode these addresses to point locations on the map in ArcGIS Pro. This is done by creating a new project and selecting “Map” on the ribbon interface, next “Add Data” and next “Address and Place Layer”. This opens up the Geocode Addresses geoprocessing tool that consumes ArcGIS credits. Running the tool results in a new feature class with the three UK addresses as points on the map:

real estate location analysis by travel timeThese three addresses will be our central points for running our real estate location analysis.

Evaluating location accessibility by different transport modes

The TravelTime plugin lets you create catchment areas to show all reachable areas within 15 and 30 minutes by different transport modes. This is important because this shows the accessibility of a property in all directions based on public transport data to calculate accurate travel times.

For the following analysis steps, we’ll use the TravelTime add-in for ArcGIS Pro. To replicate the analysis, you can sign up for the TravelTime add-in.

We’ll start by creating different catchment areas for public transport travel times. You can create catchment areas for multiple areas at once by using the TravelTime Platform toolbox, which is displayed by clicking the “Show the toolbox” button on the TravelTime Platform menu on the ribbon interface.

Next, head over to the Catalog pane and look for the TravelTime Platform toolbox under Toolboxes. We’ll now create catchment areas for 15 and 30 minutes using the “Time Map Simple” tool in the TravelTime Platform Toolbox. Double-click the tool and make sure you use the following parameters:

ArcGIS parameters

For the 30-minute catchment areas, repeat the same procedure by filling in “30” under “Travel time (in minutes)”. The different catchment areas are drawn and added to the map automatically.

By applying a yellow transparent fill colour for the 30-minute catchment area and a red transparent fill colour for the 15-minute catchment area, we get the following map view, which shows the two most northern addresses (#1 and #2):

travel time catchment areas

Here’s a close-up of the catchment areas for the third address, located in Birmingham, that show a strong north-south orientation. With regards to real estate investment, this means that our area of interest extends further to the north than it does to the east, west, or south:

travel time catchment area

How accessible are the identified sites by public transport?

With the different catchment areas being visualised, we can now answer the question of how accessible the different sites are by public transport. This gives us an idea of all locations that are accessible from a single property when public transport is used. The larger the catchment areas and the more amenities can be reached, the better its accessibility, which translates to a higher property value.

Comparing the two northern catchment areas, we can see that catchment area #2 covers a larger area than area #1. This means that catchment area #2 is more accessible by public transport than area #1, making it a better investment candidate.

Apart from covering a larger area, catchment area #2 also has five smaller, separate (yellow-coloured) isolated catchment areas that are relatively far from the centre of the catchment area.

These areas show that the street address location can be reached from further away, which enhances its accessibility. Catchment area #3 seems to have the largest catchment area of all three, which has something to with the fact that there are no natural borders as with catchment area #2. Again, this translates to a greater accessibility, higher property values and therefore a good investment candidate.

In addition to using current travel times, the TravelTime add-in offers the possibility to use travel times for future public transport lines, such as the London Crossrail line. The following map shows 15-, 30- and 45-minute public transport catchment areas which include the travel times for using the Crossrail extension, from a point location near Heathrow airport:

Travel time catchment areas for Crossrail extension

How accessible are the identified sites by driving?

Applying the same workflow, but now choosing “driving” for transport mode, we get the following map views showing the different catchment areas of the two northern addresses. Again, we chose a yellow transparent colour for the 30-minute driving catchment areas and a fire-red transparent colour for the 15-minute driving catchment areas. Comparing accessibility by different transport mode gives real estate developers a better understanding of who would be attracted to each site. This analysis will inform developers if they should target residents that own a car or use public transport.

drive time catchment areas

Note that the different catchment areas of both addresses partially overlap. You can use the Time Map Simple tool to visually separate the different catchment areas for both addresses, merge them or only show where they both intersect. Find these options under “result aggregation”, displayed below:

ArcGIS Time Map Simple tool

The option used in the driving maps above and below is “normal”, showing the overlapping boundaries for the different catchment areas. Here’s a map showing the 15- and 30-minute driving catchment areas for the Birmingham address (#3):

drive time catchment areas

Comparing the 15- and 30-minute driving catchment areas for this address, we can see that the accessibility grows significantly if we choose a maximum driving time of 30 minutes instead of 15 minutes.

As with the public transport catchment areas, the orientation of the driving time catchment areas here is more north-south than east-west in Birmingham. This accessibility growth from 15- to 30-minutes driving is less significant for the two northern addresses where the 30-minute catchment areas are not as large as in Birmingham.

The 15-minute city: which location has the most potential?

Finally, we’ll create 15-minute walking and cycling catchment areas for all three addresses. The 15-minute time limit corresponds with that of a new urban planning model called the “15-minute city”, which “requires minimal travel among housing, offices, restaurants, parks, hospitals and cultural venues”.

In such a city, each neighbourhood should fulfil six social functions: living, working, supplying, caring, learning and enjoying. Although this concept was developed long before the current pandemic, it has kickstarted a trend towards localisation.

For this analysis, we can quickly map different “15-minute cities”, taking the three street addresses as centre points and analyse how each one scores for all six social functions, for example by checking if different amenities can be reached within 15 minutes of walking or cycling.

In the map below, the blue-coloured areas show the cycling catchment areas, while the green areas show the walking catchment areas:

walking and cycling travel time catchment areas

walking and cycling travel time catchment areas

The catchment areas for walking and cycling are smaller than the ones for other transport modes that we created earlier in the tutorial and have a rounder shape than the driving and public transport catchment areas. Note the mushroom-shape of the cycling catchment area in Birmingham (address #3), that follows part of the M6 motorway.

For further site analysis of these catchment areas, we can bring in a layer of household income data and use the extract geoprocessing tool to get an idea of the mean household values inside the different catchment areas and compare them with each other.

Before we apply the extract geoprocessing tool, we right-click the new layer in the table of contents and choose “symbology”. We choose a color ramp that classifies that goes from yellow to red. This means that lower income values are yellow and higher income values have a darker, red color:

Household income layer in ArcGIS Pro

Applying the extract tool results in the following maps:

household income symbology in ArcGIS Pro

More income variation and higher incomes are found in Birmingham, showing a large red area (symbolising the highest incomes as displayed in the corresponding symbology in the table of contents, found on the left of the screen):

household income symbology in ArcGIS Pro

These differences in income levels are also important to take into account when selecting where to invest in real estate, apart from accessibility. For example, higher income levels will probably translate to higher property values/prices in the area.

Following a similar approach, we can overlay a layer with all UK hospital locations to see whether our “15-minute-city” in Birmingham includes a hospital. The map below shows all UK hospitals in red and blue dots:

Hospital access by travel time

Zooming into our Birmingham 15-minute cycling catchment area, we can see that indeed there is one NHS Sector hospital located inside it, represented by a red dot in the most western part:

Hospital access by travel time

This is another important piece of information that can help us to decide whether to invest in real estate and evaluate the value of a property based on the accessibility of amenities nearby.

Analysing the best location to invest in real estate

The following image shows the public transport catchment areas for all three locations:

public transport catchment areas

The next image shows the driving time catchment areas for all three locations:

drive time catchment areas

Finally, the next image shows the walking and cycling catchment areas for all three locations:

walking and cycling catchment areas

The different catchment areas of each address location can be compared to select the best site for investment.

For address #2, we can see that the catchment areas for all different transport modes are shaped by the presence of a geographical boundary. In terms of accessibility, this is the least accessible location of all three (although the 30-minute catchment area for public transport is remarkably large) and therefore not a good site for investment based on the criteria of location accessibility.

Similarly, for address location #1, the coastline also limits the size and shape of public transport and driving time catchment areas.

Looking at accessibility for only public transport and driving time catchment areas, address location #3 is the most accessible of the three locations, showing a particularly large catchment area for a 15-minutes cycling time. However, looking at the driving catchment areas, address #2 seems to have the largest catchment area, while for public transport the largest catchment areas is found for address #2.

As a first selection, this real estate data analysis helped to decide where best to invest based on accessibility.

Ready to build your own real estate site selection analysis?

This tutorial has shown how to use travel data for GIS real estate site selection. We evaluated the accessibility of three UK locations by different transport, namely public transport, driving, cycling and walking.

By analysing accessibility for different transport modes, we get a more refined overview than using only a single transport mode. Especially with regards to 15-minute cycling and walking times, it’s easy to map so-called “15-minute-cities” for individual street addresses to see whether they meet the requirements of such a city.

The key benefit of real estate location analysis in this example is that we’ve been able to identify the most profitable locations for real estate development based on catchment areas, proximity to key amenities (in this case, we analysed hospital locations) and target demographics such as mean income values.

Finally, while we used ArcGIS in this tutorial, you can also run a similar travel time analysis in several ways, using Alteryx, QGIS or the TravelTime API.

To get started with travel time analysis for real estate site selection, get a free TravelTime API key.

Topics:
Location data Tutorials ArcGIS